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Batting_10_Teams_Final.csv

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+Test,103.0,176.0,7195.0,16217.0,206.0,43.61,44.37,11.0,863.0,16.0,12.0,35.0,19.0,3.0,0.0,0.0,Cheteshwar Pujara,India
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+ODI,16.0,14.0,510.0,512.0,108.0,56.67,99.61,5.0,34.0,22.0,0.0,3.0,1.0,0.0,0.0,0.0,Sanju Samson,India
+T20,42.0,38.0,861.0,565.0,111.0,25.32,152.39,4.0,71.0,49.0,6.0,2.0,3.0,0.0,0.0,0.0,Sanju Samson,India
+IPL,168.0,164.0,4485.0,3217.0,119.0,30.93,139.42,19.0,359.0,210.0,11.0,26.0,3.0,0.0,0.0,0.0,Sanju Samson,India
+Test,40.0,56.0,1353.0,2973.0,117.0,29.41,45.51,10.0,129.0,14.0,6.0,6.0,3.0,0.0,0.0,0.0,Wriddhiman Saha,India
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+IPL,170.0,145.0,2934.0,2300.0,115.0,24.25,127.57,24.0,296.0,87.0,7.0,13.0,1.0,0.0,0.0,0.0,Wriddhiman Saha,India
+Test,43.0,75.0,2948.0,4005.0,159.0,42.11,73.61,5.0,321.0,73.0,3.0,15.0,6.0,0.0,0.0,0.0,Rishabh Pant,India
+ODI,31.0,27.0,871.0,820.0,125.0,33.5,106.22,1.0,91.0,26.0,3.0,5.0,1.0,0.0,0.0,0.0,Rishabh Pant,India
+T20,76.0,66.0,1209.0,949.0,65.0,23.25,127.4,14.0,111.0,44.0,4.0,3.0,0.0,0.0,0.0,0.0,Rishabh Pant,India
+IPL,112.0,111.0,3284.0,2211.0,128.0,34.94,148.54,17.0,296.0,154.0,5.0,18.0,1.0,0.0,0.0,0.0,Rishabh Pant,India
+Test,64.0,89.0,750.0,1005.0,56.0,11.9,74.63,26.0,83.0,25.0,18.0,2.0,0.0,0.0,0.0,0.0,Mohammed Shami,India
+ODI,108.0,49.0,225.0,273.0,25.0,7.76,82.42,20.0,17.0,9.0,6.0,0.0,0.0,0.0,0.0,0.0,Mohammed Shami,India
+T20,25.0,5.0,7.0,10.0,7.0,3.5,70.0,3.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,Mohammed Shami,India
+IPL,111.0,25.0,74.0,79.0,21.0,5.69,93.68,12.0,6.0,2.0,4.0,0.0,0.0,0.0,0.0,0.0,Mohammed Shami,India
+Test,45.0,69.0,332.0,741.0,34.0,7.06,44.81,22.0,35.0,11.0,25.0,0.0,0.0,0.0,0.0,0.0,Jasprit Bumrah,India
+ODI,89.0,26.0,91.0,159.0,16.0,7.58,57.24,14.0,10.0,1.0,5.0,0.0,0.0,0.0,0.0,0.0,Jasprit Bumrah,India
+T20,70.0,8.0,8.0,14.0,7.0,2.67,57.15,5.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,Jasprit Bumrah,India
+IPL,133.0,30.0,68.0,78.0,16.0,9.71,87.18,23.0,5.0,1.0,5.0,0.0,0.0,0.0,0.0,0.0,Jasprit Bumrah,India
+Test,13.0,17.0,199.0,698.0,40.0,13.27,28.52,2.0,18.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,Kuldeep Yadav,India
+ODI,113.0,42.0,207.0,407.0,19.0,9.86,50.86,21.0,14.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,Kuldeep Yadav,India
+T20,40.0,7.0,46.0,59.0,23.0,11.5,77.97,3.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,Kuldeep Yadav,India
+IPL,85.0,34.0,188.0,221.0,35.0,14.46,85.07,21.0,17.0,3.0,5.0,0.0,0.0,0.0,0.0,0.0,Kuldeep Yadav,India
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Yuzvendra Chahal,India
+ODI,72.0,14.0,77.0,141.0,18.0,8.56,54.61,5.0,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Yuzvendra Chahal,India
+T20,80.0,6.0,6.0,13.0,3.0,3.0,46.16,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Yuzvendra Chahal,India
+IPL,161.0,20.0,37.0,86.0,8.0,5.29,43.03,13.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Yuzvendra Chahal,India
+Test,2.0,3.0,8.0,27.0,5.0,4.0,29.63,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Navdeep Saini,India
+ODI,8.0,5.0,107.0,137.0,45.0,53.5,78.11,3.0,9.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,Navdeep Saini,India
+T20,11.0,3.0,12.0,11.0,11.0,0.0,109.1,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Navdeep Saini,India
+IPL,32.0,7.0,33.0,37.0,12.0,8.25,89.19,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Navdeep Saini,India
+Test,57.0,68.0,460.0,883.0,31.0,11.22,52.1,27.0,42.0,24.0,9.0,0.0,0.0,0.0,0.0,0.0,Umesh Yadav,India
+ODI,75.0,24.0,79.0,134.0,18.0,7.9,58.96,14.0,8.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,Umesh Yadav,India
+T20,9.0,2.0,22.0,21.0,20.0,22.0,104.77,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Umesh Yadav,India
+IPL,148.0,52.0,208.0,201.0,24.0,9.9,103.49,31.0,16.0,9.0,8.0,0.0,0.0,0.0,0.0,0.0,Umesh Yadav,India
+Test,36.0,49.0,131.0,356.0,16.0,4.85,36.8,22.0,14.0,2.0,11.0,0.0,0.0,0.0,0.0,0.0,Mohammed Siraj,India
+ODI,44.0,17.0,55.0,129.0,9.0,7.86,42.64,10.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Mohammed Siraj,India
+T20,16.0,5.0,14.0,16.0,7.0,7.0,87.5,3.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Mohammed Siraj,India
+IPL,94.0,25.0,109.0,119.0,14.0,10.9,91.6,15.0,10.0,4.0,2.0,0.0,0.0,0.0,0.0,0.0,Mohammed Siraj,India
+Test,47.0,89.0,2586.0,5548.0,189.0,29.39,46.62,1.0,326.0,23.0,10.0,17.0,3.0,0.0,0.0,0.0,Martin Guptil,NewZeland
+ODI,198.0,195.0,7346.0,8414.0,237.0,41.5,87.31,18.0,751.0,187.0,16.0,39.0,18.0,1.0,0.0,0.0,Martin Guptil,NewZeland
+T20,122.0,118.0,3531.0,2602.0,105.0,31.81,135.71,7.0,310.0,173.0,3.0,20.0,2.0,0.0,0.0,0.0,Martin Guptil,NewZeland
+IPL,13.0,13.0,270.0,196.0,50.0,22.5,137.76,1.0,24.0,15.0,1.0,1.0,0.0,0.0,0.0,0.0,Martin Guptil,NewZeland
+Test,112.0,196.0,7684.0,12957.0,290.0,44.16,59.31,22.0,932.0,55.0,14.0,35.0,19.0,3.0,0.0,0.0,Ross Taylor,NewZeland
+ODI,236.0,220.0,8602.0,10331.0,181.0,47.52,83.27,39.0,712.0,147.0,9.0,51.0,21.0,0.0,0.0,0.0,Ross Taylor,NewZeland
+T20,102.0,94.0,1909.0,1560.0,63.0,25.45,122.38,19.0,122.0,71.0,6.0,7.0,0.0,0.0,0.0,0.0,Ross Taylor,NewZeland
+IPL,55.0,54.0,1017.0,822.0,81.0,25.43,123.73,14.0,66.0,46.0,3.0,3.0,0.0,0.0,0.0,0.0,Ross Taylor,NewZeland
+Test,105.0,186.0,9276.0,17913.0,251.0,54.89,51.79,17.0,1031.0,27.0,11.0,37.0,33.0,6.0,0.0,0.0,Kane Williamson,NewZeland
+ODI,173.0,165.0,7236.0,8853.0,148.0,48.89,81.74,17.0,666.0,60.0,5.0,47.0,15.0,0.0,0.0,0.0,Kane Williamson,NewZeland
+T20,93.0,90.0,2575.0,2094.0,95.0,33.01,122.98,12.0,245.0,58.0,4.0,18.0,0.0,0.0,0.0,0.0,Kane Williamson,NewZeland
+IPL,79.0,77.0,2128.0,1694.0,89.0,35.47,125.62,17.0,185.0,64.0,2.0,18.0,0.0,0.0,0.0,0.0,Kane Williamson,NewZeland
+Test,1.0,2.0,15.0,26.0,15.0,7.5,57.7,0.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Colin Munro,NewZeland
+ODI,57.0,53.0,1271.0,1214.0,87.0,24.92,104.7,2.0,137.0,36.0,7.0,8.0,0.0,0.0,0.0,0.0,Colin Munro,NewZeland
+T20,65.0,62.0,1724.0,1102.0,109.0,31.35,156.45,7.0,132.0,107.0,5.0,11.0,3.0,0.0,0.0,0.0,Colin Munro,NewZeland
+IPL,13.0,12.0,177.0,141.0,40.0,14.75,125.54,0.0,19.0,8.0,2.0,0.0,0.0,0.0,0.0,0.0,Colin Munro,NewZeland
+Test,56.0,87.0,2973.0,5922.0,200.0,37.16,50.21,7.0,322.0,9.0,6.0,12.0,9.0,1.0,0.0,0.0,Henry Nicholls,NewZeland
+ODI,78.0,76.0,2116.0,2616.0,124.0,35.27,80.89,16.0,193.0,19.0,6.0,15.0,1.0,0.0,0.0,0.0,Henry Nicholls,NewZeland
+T20,10.0,9.0,100.0,112.0,36.0,12.5,89.29,1.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Henry Nicholls,NewZeland
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Henry Nicholls,NewZeland
+Test,12.0,22.0,709.0,1069.0,137.0,33.76,66.33,1.0,88.0,11.0,2.0,4.0,2.0,0.0,0.0,0.0,James Neesham,NewZeland
+ODI,76.0,65.0,1495.0,1496.0,97.0,28.21,99.94,12.0,128.0,38.0,3.0,7.0,0.0,0.0,0.0,0.0,James Neesham,NewZeland
+T20,83.0,66.0,955.0,627.0,48.0,21.22,152.32,21.0,73.0,51.0,6.0,0.0,0.0,0.0,0.0,0.0,James Neesham,NewZeland
+IPL,14.0,10.0,92.0,93.0,22.0,10.22,98.93,1.0,6.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,James Neesham,NewZeland
+Test,29.0,44.0,1432.0,1780.0,120.0,38.7,80.45,7.0,141.0,41.0,6.0,8.0,2.0,0.0,0.0,0.0,Colin de Grandhomme,NewZeland
+ODI,45.0,35.0,742.0,699.0,74.0,26.5,106.16,7.0,58.0,29.0,2.0,4.0,0.0,0.0,0.0,0.0,Colin de Grandhomme,NewZeland
+T20,41.0,39.0,503.0,365.0,59.0,15.72,137.81,7.0,27.0,30.0,6.0,3.0,0.0,0.0,0.0,0.0,Colin de Grandhomme,NewZeland
+IPL,25.0,21.0,303.0,225.0,40.0,18.94,134.67,5.0,18.0,18.0,3.0,0.0,0.0,0.0,0.0,0.0,Colin de Grandhomme,NewZeland
+Test,30.0,43.0,1066.0,2270.0,126.0,26.0,46.97,2.0,119.0,32.0,3.0,4.0,1.0,0.0,0.0,0.0,Mitchell Santner,NewZeland
+ODI,118.0,86.0,1438.0,1584.0,67.0,26.15,90.79,31.0,105.0,41.0,3.0,3.0,0.0,0.0,0.0,0.0,Mitchell Santner,NewZeland
+T20,109.0,74.0,725.0,603.0,77.0,16.86,120.24,31.0,55.0,24.0,5.0,1.0,0.0,0.0,0.0,0.0,Mitchell Santner,NewZeland
+IPL,19.0,12.0,81.0,84.0,22.0,11.57,96.43,5.0,5.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,Mitchell Santner,NewZeland
+Test,88.0,158.0,5835.0,12283.0,264.0,38.39,47.51,6.0,665.0,19.0,13.0,31.0,13.0,2.0,0.0,0.0,Tom Latham,NewZeland
+ODI,157.0,144.0,4361.0,5090.0,145.0,34.61,85.68,18.0,364.0,60.0,14.0,26.0,8.0,0.0,0.0,0.0,Tom Latham,NewZeland
+T20,26.0,23.0,516.0,474.0,65.0,25.8,108.87,3.0,42.0,8.0,1.0,3.0,0.0,0.0,0.0,0.0,Tom Latham,NewZeland
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tom Latham,NewZeland
+Test,40.0,69.0,2138.0,4013.0,138.0,34.48,53.28,7.0,259.0,16.0,6.0,11.0,5.0,0.0,0.0,0.0,Tom Blundell,NewZeland
+ODI,12.0,12.0,266.0,307.0,68.0,29.56,86.65,3.0,28.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,Tom Blundell,NewZeland
+T20,9.0,8.0,91.0,94.0,30.0,15.17,96.81,2.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tom Blundell,NewZeland
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tom Blundell,NewZeland
+Test,78.0,94.0,759.0,1264.0,52.0,15.81,60.05,46.0,82.0,30.0,13.0,1.0,0.0,0.0,0.0,0.0,Trent Boult,NewZeland
+ODI,114.0,52.0,216.0,279.0,21.0,9.0,77.42,28.0,20.0,7.0,2.0,0.0,0.0,0.0,0.0,0.0,Trent Boult,NewZeland
+T20,61.0,15.0,58.0,64.0,16.0,8.29,90.63,8.0,3.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,Trent Boult,NewZeland
+IPL,104.0,28.0,84.0,80.0,17.0,9.33,105.0,19.0,5.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,Trent Boult,NewZeland
+Test,30.0,42.0,649.0,834.0,72.0,18.03,77.82,6.0,87.0,20.0,9.0,4.0,0.0,0.0,0.0,0.0,Matt Henry,NewZeland
+ODI,91.0,38.0,270.0,290.0,48.0,10.38,93.11,12.0,22.0,11.0,7.0,0.0,0.0,0.0,0.0,0.0,Matt Henry,NewZeland
+T20,21.0,7.0,24.0,27.0,12.0,6.0,88.89,3.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,Matt Henry,NewZeland
+IPL,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Matt Henry,NewZeland
+Test,107.0,155.0,2245.0,2715.0,77.0,15.48,82.69,10.0,215.0,98.0,21.0,7.0,0.0,0.0,0.0,0.0,Tim Southee,NewZeland
+ODI,161.0,96.0,742.0,771.0,55.0,12.16,96.24,35.0,59.0,26.0,13.0,1.0,0.0,0.0,0.0,0.0,Tim Southee,NewZeland
+T20,125.0,50.0,303.0,218.0,39.0,11.22,139.0,23.0,20.0,18.0,6.0,0.0,0.0,0.0,0.0,0.0,Tim Southee,NewZeland
+IPL,54.0,20.0,120.0,107.0,36.0,9.23,112.15,7.0,8.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,Tim Southee,NewZeland
+Test,21.0,31.0,561.0,1194.0,65.0,20.78,46.99,4.0,68.0,7.0,5.0,4.0,0.0,0.0,0.0,0.0,Ish Sodhi,NewZeland
+ODI,55.0,27.0,217.0,291.0,35.0,9.86,74.58,5.0,8.0,11.0,6.0,0.0,0.0,0.0,0.0,0.0,Ish Sodhi,NewZeland
+T20,123.0,39.0,197.0,194.0,19.0,7.3,101.55,12.0,12.0,9.0,6.0,0.0,0.0,0.0,0.0,0.0,Ish Sodhi,NewZeland
+IPL,8.0,2.0,7.0,17.0,6.0,3.5,41.18,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Ish Sodhi,NewZeland
+Test,1.0,2.0,1.0,9.0,1.0,0.0,11.12,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Lockie Ferguson,NewZeland
+ODI,65.0,30.0,122.0,235.0,19.0,7.18,51.92,13.0,6.0,3.0,4.0,0.0,0.0,0.0,0.0,0.0,Lockie Ferguson,NewZeland
+T20,43.0,15.0,29.0,36.0,14.0,3.63,80.56,7.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,0.0,Lockie Ferguson,NewZeland
+IPL,45.0,10.0,68.0,46.0,24.0,22.67,147.83,7.0,6.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,Lockie Ferguson,NewZeland
+Test,45.0,82.0,2857.0,4803.0,152.0,35.71,59.49,2.0,412.0,14.0,6.0,13.0,7.0,0.0,0.0,0.0,Aiden Markram,South Africa
+ODI,77.0,73.0,2371.0,2436.0,175.0,37.05,97.34,9.0,236.0,55.0,4.0,12.0,3.0,0.0,0.0,0.0,Aiden Markram,South Africa
+T20,57.0,53.0,1367.0,950.0,70.0,30.38,143.9,8.0,123.0,56.0,2.0,9.0,0.0,0.0,0.0,0.0,Aiden Markram,South Africa
+IPL,45.0,43.0,1010.0,780.0,68.0,29.71,129.49,9.0,74.0,36.0,2.0,5.0,0.0,0.0,0.0,0.0,Aiden Markram,South Africa
+Test,4.0,4.0,19.0,39.0,9.0,9.5,48.72,2.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Andile Phehlukwayo,South Africa
+ODI,85.0,57.0,884.0,1027.0,69.0,23.26,86.08,19.0,77.0,36.0,5.0,2.0,0.0,0.0,0.0,0.0,Andile Phehlukwayo,South Africa
+T20,42.0,25.0,166.0,153.0,27.0,9.22,108.5,7.0,16.0,5.0,7.0,0.0,0.0,0.0,0.0,0.0,Andile Phehlukwayo,South Africa
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Andile Phehlukwayo,South Africa
+Test,1.0,2.0,9.0,18.0,5.0,9.0,50.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Beuran Hendricks,South Africa
+ODI,10.0,4.0,24.0,45.0,18.0,8.0,53.34,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Beuran Hendricks,South Africa
+T20,19.0,5.0,18.0,23.0,12.0,6.0,78.27,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,Beuran Hendricks,South Africa
+IPL,7.0,3.0,1.0,3.0,1.0,1.0,33.34,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Beuran Hendricks,South Africa
+Test,4.0,7.0,173.0,362.0,69.0,24.71,47.8,0.0,25.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,Chris Morris,South Africa
+ODI,42.0,27.0,468.0,465.0,62.0,20.35,100.65,4.0,36.0,15.0,0.0,1.0,0.0,0.0,0.0,0.0,Chris Morris,South Africa
+T20,23.0,13.0,133.0,102.0,55.0,14.78,130.4,4.0,12.0,5.0,3.0,1.0,0.0,0.0,0.0,0.0,Chris Morris,South Africa
+IPL,81.0,51.0,618.0,398.0,82.0,22.07,155.28,23.0,41.0,35.0,9.0,2.0,0.0,0.0,0.0,0.0,Chris Morris,South Africa
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,David Miller,South Africa
+ODI,178.0,154.0,4611.0,4447.0,139.0,42.3,103.69,45.0,342.0,144.0,9.0,24.0,7.0,0.0,0.0,0.0,David Miller,South Africa
+T20,130.0,114.0,2593.0,1842.0,106.0,33.24,140.78,36.0,168.0,130.0,3.0,8.0,2.0,0.0,0.0,0.0,David Miller,South Africa
+IPL,131.0,125.0,2951.0,2119.0,101.0,36.43,139.27,44.0,208.0,136.0,4.0,13.0,1.0,0.0,0.0,0.0,David Miller,South Africa
+Test,3.0,6.0,83.0,163.0,37.0,13.83,50.93,0.0,13.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,Dwaine Pretorius,South Africa
+ODI,27.0,13.0,192.0,224.0,50.0,16.0,85.72,1.0,14.0,5.0,1.0,1.0,0.0,0.0,0.0,0.0,Dwaine Pretorius,South Africa
+T20,30.0,17.0,261.0,159.0,77.0,21.75,164.16,5.0,22.0,15.0,2.0,1.0,0.0,0.0,0.0,0.0,Dwaine Pretorius,South Africa
+IPL,7.0,5.0,44.0,28.0,22.0,11.0,157.15,1.0,3.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,Dwaine Pretorius,South Africa
+Test,69.0,118.0,4163.0,8986.0,199.0,40.03,46.33,14.0,516.0,21.0,9.0,21.0,10.0,0.0,0.0,0.0,Faf du Plessis ,South Africa
+ODI,143.0,136.0,5507.0,6218.0,185.0,46.67,88.57,18.0,495.0,66.0,3.0,35.0,12.0,0.0,0.0,0.0,Faf du Plessis ,South Africa
+T20,50.0,50.0,1528.0,1137.0,119.0,35.53,134.39,7.0,140.0,50.0,0.0,10.0,1.0,0.0,0.0,0.0,Faf du Plessis ,South Africa
+IPL,146.0,139.0,4600.0,3370.0,96.0,35.94,136.5,11.0,424.0,168.0,7.0,37.0,0.0,0.0,0.0,0.0,Faf du Plessis ,South Africa
+Test,20.0,23.0,130.0,235.0,29.0,9.29,55.32,9.0,18.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,Imran Tahir,South Africa
+ODI,107.0,36.0,157.0,225.0,29.0,7.85,69.78,16.0,21.0,1.0,6.0,0.0,0.0,0.0,0.0,0.0,Imran Tahir,South Africa
+T20,38.0,4.0,19.0,18.0,9.0,19.0,105.56,3.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,Imran Tahir,South Africa
+IPL,59.0,9.0,33.0,37.0,13.0,8.25,89.19,5.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Imran Tahir,South Africa
+Test,46.0,74.0,2103.0,4544.0,166.0,32.86,46.29,10.0,251.0,13.0,9.0,8.0,6.0,0.0,0.0,0.0,Jean-Paul Duminy,South Africa
+ODI,199.0,179.0,5117.0,6050.0,150.0,36.81,84.58,40.0,347.0,75.0,7.0,27.0,4.0,0.0,0.0,0.0,Jean-Paul Duminy,South Africa
+T20,81.0,75.0,1934.0,1532.0,96.0,38.68,126.25,25.0,138.0,71.0,6.0,11.0,0.0,0.0,0.0,0.0,Jean-Paul Duminy,South Africa
+IPL,83.0,77.0,2029.0,1636.0,78.0,39.78,124.03,26.0,126.0,79.0,1.0,14.0,0.0,0.0,0.0,0.0,Jean-Paul Duminy,South Africa
+Test,70.0,106.0,1030.0,2053.0,47.0,11.98,50.18,20.0,135.0,16.0,20.0,0.0,0.0,0.0,0.0,0.0,Kagiso Rabada,South Africa
+ODI,106.0,45.0,401.0,507.0,31.0,14.85,79.1,18.0,30.0,12.0,2.0,0.0,0.0,0.0,0.0,0.0,Kagiso Rabada,South Africa
+T20,65.0,24.0,156.0,141.0,22.0,17.33,110.64,15.0,14.0,5.0,4.0,0.0,0.0,0.0,0.0,0.0,Kagiso Rabada,South Africa
+IPL,81.0,31.0,206.0,193.0,44.0,12.12,106.74,14.0,16.0,8.0,4.0,0.0,0.0,0.0,0.0,0.0,Kagiso Rabada,South Africa
+Test,19.0,30.0,97.0,229.0,19.0,4.85,42.36,10.0,14.0,1.0,8.0,0.0,0.0,0.0,0.0,0.0,Lungi Ngidi,South Africa
+ODI,67.0,27.0,124.0,236.0,20.0,11.27,52.55,16.0,8.0,6.0,5.0,0.0,0.0,0.0,0.0,0.0,Lungi Ngidi,South Africa
+T20,43.0,13.0,41.0,52.0,13.0,8.2,78.85,8.0,4.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,Lungi Ngidi,South Africa
+IPL,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Lungi Ngidi,South Africa
+Test,54.0,91.0,3300.0,4652.0,141.0,38.82,70.94,6.0,411.0,33.0,7.0,22.0,6.0,0.0,0.0,0.0,Quinton de Kock,South Africa
+ODI,155.0,155.0,6770.0,7005.0,178.0,45.74,96.65,7.0,771.0,118.0,4.0,30.0,21.0,0.0,0.0,0.0,Quinton de Kock,South Africa
+T20,92.0,91.0,2584.0,1868.0,100.0,31.51,138.33,9.0,264.0,103.0,7.0,16.0,1.0,0.0,0.0,0.0,Quinton de Kock,South Africa
+IPL,108.0,108.0,3161.0,2357.0,140.0,30.99,134.12,6.0,317.0,123.0,4.0,23.0,2.0,0.0,0.0,0.0,Quinton de Kock,South Africa
+Test,18.0,32.0,905.0,2221.0,98.0,30.17,40.75,2.0,101.0,4.0,3.0,6.0,0.0,0.0,0.0,0.0,Rassie van der Dussen,South Africa
+ODI,71.0,66.0,2657.0,3053.0,134.0,50.13,87.03,13.0,206.0,50.0,3.0,17.0,6.0,0.0,0.0,0.0,Rassie van der Dussen,South Africa
+T20,50.0,46.0,1257.0,971.0,94.0,33.97,129.46,9.0,73.0,60.0,2.0,9.0,0.0,0.0,0.0,0.0,Rassie van der Dussen,South Africa
+IPL,3.0,3.0,22.0,24.0,12.0,11.0,91.67,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Rassie van der Dussen,South Africa
+Test,2.0,4.0,20.0,48.0,18.0,20.0,41.67,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tabraiz Shamsi,South Africa
+ODI,55.0,15.0,39.0,69.0,11.0,9.75,56.53,11.0,4.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,Tabraiz Shamsi,South Africa
+T20,70.0,14.0,10.0,27.0,4.0,2.0,37.04,9.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,Tabraiz Shamsi,South Africa
+IPL,5.0,1.0,2.0,4.0,2.0,0.0,50.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tabraiz Shamsi,South Africa
+Test,28.0,50.0,132.0,361.0,17.0,4.0,36.57,17.0,19.0,0.0,18.0,0.0,0.0,0.0,0.0,0.0,Nuwan Pradeep,Sri Lanka
+ODI,49.0,25.0,35.0,83.0,7.0,4.38,42.17,17.0,3.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,Nuwan Pradeep,Sri Lanka
+T20,16.0,6.0,10.0,15.0,8.0,10.0,66.67,5.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Nuwan Pradeep,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Nuwan Pradeep,Sri Lanka
+Test,44.0,85.0,2088.0,5294.0,155.0,26.43,39.45,6.0,207.0,3.0,11.0,10.0,3.0,0.0,0.0,0.0,Lahiru Thirimanne,Sri Lanka
+ODI,127.0,105.0,3164.0,4389.0,139.0,34.77,72.09,14.0,244.0,25.0,7.0,21.0,4.0,0.0,0.0,0.0,Lahiru Thirimanne,Sri Lanka
+T20,26.0,20.0,291.0,267.0,44.0,16.17,108.99,2.0,27.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,Lahiru Thirimanne,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Lahiru Thirimanne,Sri Lanka
+Test,100.0,191.0,7222.0,14024.0,244.0,39.25,51.5,7.0,764.0,12.0,13.0,39.0,16.0,1.0,0.0,0.0,Dimuth Karunaratne,Sri Lanka
+ODI,50.0,46.0,1316.0,1655.0,103.0,31.33,79.52,4.0,131.0,1.0,4.0,11.0,1.0,0.0,0.0,0.0,Dimuth Karunaratne,Sri Lanka
+T20,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Dimuth Karunaratne,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Dimuth Karunaratne,Sri Lanka
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Avishka Fernando,Sri Lanka
+ODI,51.0,50.0,1589.0,1787.0,127.0,31.78,88.92,0.0,165.0,31.0,5.0,9.0,4.0,0.0,0.0,0.0,Avishka Fernando,Sri Lanka
+T20,37.0,35.0,363.0,386.0,37.0,11.0,94.05,2.0,28.0,8.0,5.0,0.0,0.0,0.0,0.0,0.0,Avishka Fernando,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Avishka Fernando,Sri Lanka
+Test,118.0,210.0,8167.0,16856.0,200.0,44.63,48.46,27.0,831.0,89.0,6.0,45.0,16.0,1.0,0.0,0.0,Angelo Mathews,Sri Lanka
+ODI,226.0,194.0,5916.0,7135.0,139.0,40.52,82.92,48.0,468.0,90.0,16.0,40.0,3.0,0.0,0.0,0.0,Angelo Mathews,Sri Lanka
+T20,90.0,73.0,1416.0,1175.0,81.0,27.76,120.52,22.0,92.0,50.0,1.0,6.0,0.0,0.0,0.0,0.0,Angelo Mathews,Sri Lanka
+IPL,49.0,42.0,724.0,575.0,65.0,23.35,125.92,11.0,44.0,29.0,3.0,1.0,0.0,0.0,0.0,0.0,Angelo Mathews,Sri Lanka
+Test,5.0,9.0,298.0,454.0,68.0,33.11,65.64,0.0,32.0,11.0,1.0,2.0,0.0,0.0,0.0,0.0,Dhananjaya de Silva,Sri Lanka
+ODI,27.0,24.0,516.0,525.0,66.0,22.43,98.29,1.0,39.0,13.0,1.0,3.0,0.0,0.0,0.0,0.0,Dhananjaya de Silva,Sri Lanka
+T20,22.0,19.0,275.0,208.0,42.0,17.19,132.22,3.0,16.0,12.0,4.0,0.0,0.0,0.0,0.0,0.0,Dhananjaya de Silva,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Dhananjaya de Silva,Sri Lanka
+Test,29.0,44.0,1432.0,1780.0,120.0,38.7,80.45,7.0,141.0,41.0,6.0,8.0,2.0,0.0,0.0,0.0,Milinda Siriwardana,Sri Lanka
+ODI,45.0,35.0,742.0,699.0,74.0,26.5,106.16,7.0,58.0,29.0,2.0,4.0,0.0,0.0,0.0,0.0,Milinda Siriwardana,Sri Lanka
+T20,41.0,39.0,503.0,365.0,59.0,15.72,137.81,7.0,27.0,30.0,6.0,3.0,0.0,0.0,0.0,0.0,Milinda Siriwardana,Sri Lanka
+IPL,25.0,21.0,303.0,225.0,40.0,18.94,134.67,5.0,18.0,18.0,3.0,0.0,0.0,0.0,0.0,0.0,Milinda Siriwardana,Sri Lanka
+Test,6.0,10.0,203.0,278.0,75.0,20.3,73.03,0.0,21.0,4.0,0.0,1.0,0.0,0.0,0.0,0.0,Thisara Perera,Sri Lanka
+ODI,166.0,133.0,2338.0,2086.0,140.0,19.98,112.09,16.0,176.0,84.0,11.0,10.0,1.0,0.0,0.0,0.0,Thisara Perera,Sri Lanka
+T20,84.0,74.0,1204.0,794.0,61.0,23.15,151.64,22.0,88.0,64.0,8.0,3.0,0.0,0.0,0.0,0.0,Thisara Perera,Sri Lanka
+IPL,37.0,30.0,422.0,307.0,40.0,19.18,137.46,8.0,23.0,26.0,1.0,0.0,0.0,0.0,0.0,0.0,Thisara Perera,Sri Lanka
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Isuru Udana,Sri Lanka
+ODI,21.0,18.0,237.0,249.0,78.0,16.93,95.19,4.0,17.0,10.0,2.0,1.0,0.0,0.0,0.0,0.0,Isuru Udana,Sri Lanka
+T20,35.0,25.0,256.0,186.0,84.0,18.29,137.64,11.0,16.0,14.0,3.0,1.0,0.0,0.0,0.0,0.0,Isuru Udana,Sri Lanka
+IPL,10.0,4.0,15.0,11.0,10.0,5.0,136.37,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,Isuru Udana,Sri Lanka
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Jeevan Mendis,Sri Lanka
+ODI,58.0,44.0,636.0,769.0,72.0,18.71,82.71,10.0,48.0,13.0,2.0,1.0,0.0,0.0,0.0,0.0,Jeevan Mendis,Sri Lanka
+T20,22.0,15.0,208.0,174.0,43.0,18.91,119.55,4.0,18.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,Jeevan Mendis,Sri Lanka
+IPL,3.0,3.0,23.0,27.0,12.0,7.67,85.19,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Jeevan Mendis,Sri Lanka
+Test,22.0,41.0,1177.0,1629.0,153.0,30.97,72.26,3.0,151.0,12.0,5.0,7.0,2.0,0.0,0.0,0.0,Kusal Perera,Sri Lanka
+ODI,116.0,111.0,3237.0,3484.0,135.0,30.25,92.92,4.0,362.0,52.0,12.0,17.0,6.0,0.0,0.0,0.0,Kusal Perera,Sri Lanka
+T20,77.0,76.0,2056.0,1533.0,101.0,28.16,134.12,3.0,199.0,65.0,4.0,15.0,1.0,0.0,0.0,0.0,Kusal Perera,Sri Lanka
+IPL,2.0,2.0,14.0,13.0,14.0,7.0,107.7,0.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Kusal Perera,Sri Lanka
+Test,71.0,133.0,4668.0,8012.0,245.0,36.76,58.27,6.0,563.0,50.0,14.0,21.0,10.0,1.0,0.0,0.0,Kusal Mendis,Sri Lanka
+ODI,143.0,140.0,4429.0,5076.0,143.0,34.33,87.26,11.0,445.0,74.0,14.0,33.0,5.0,0.0,0.0,0.0,Kusal Mendis,Sri Lanka
+T20,78.0,78.0,1920.0,1458.0,86.0,25.6,131.69,3.0,165.0,81.0,6.0,15.0,0.0,0.0,0.0,0.0,Kusal Mendis,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Kusal Mendis,Sri Lanka
+Test,107.0,155.0,2245.0,2715.0,77.0,15.48,82.69,10.0,215.0,98.0,21.0,7.0,0.0,0.0,0.0,0.0,Suranga Lakmal,Sri Lanka
+ODI,161.0,96.0,742.0,771.0,55.0,12.16,96.24,35.0,59.0,26.0,13.0,1.0,0.0,0.0,0.0,0.0,Suranga Lakmal,Sri Lanka
+T20,125.0,50.0,303.0,218.0,39.0,11.22,139.0,23.0,20.0,18.0,6.0,0.0,0.0,0.0,0.0,0.0,Suranga Lakmal,Sri Lanka
+IPL,54.0,20.0,120.0,107.0,36.0,9.23,112.15,7.0,8.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,Suranga Lakmal,Sri Lanka
+Test,30.0,37.0,275.0,619.0,64.0,11.46,44.43,13.0,36.0,6.0,9.0,1.0,0.0,0.0,0.0,0.0,Lasith Malinga,Sri Lanka
+ODI,226.0,120.0,567.0,761.0,56.0,6.83,74.51,37.0,45.0,21.0,26.0,1.0,0.0,0.0,0.0,0.0,Lasith Malinga,Sri Lanka
+T20,84.0,33.0,136.0,161.0,27.0,6.48,84.48,12.0,9.0,5.0,8.0,0.0,0.0,0.0,0.0,0.0,Lasith Malinga,Sri Lanka
+IPL,122.0,25.0,88.0,99.0,17.0,5.5,88.89,9.0,6.0,5.0,6.0,0.0,0.0,0.0,0.0,0.0,Lasith Malinga,Sri Lanka
+Test,2.0,4.0,71.0,77.0,53.0,17.75,92.21,0.0,10.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,Jeffrey Vandersay,Sri Lanka
+ODI,27.0,15.0,112.0,234.0,25.0,11.2,47.87,5.0,5.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,Jeffrey Vandersay,Sri Lanka
+T20,14.0,8.0,20.0,20.0,8.0,20.0,100.0,7.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Jeffrey Vandersay,Sri Lanka
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Jeffrey Vandersay,Sri Lanka
+Test,11.0,22.0,481.0,875.0,66.0,24.05,54.98,2.0,56.0,6.0,5.0,4.0,0.0,0.0,0.0,0.0,Sabbir Rahman,Bangladesh
+ODI,66.0,59.0,1333.0,1461.0,102.0,25.63,91.24,7.0,153.0,24.0,5.0,6.0,1.0,0.0,0.0,0.0,Sabbir Rahman,Bangladesh
+T20,48.0,47.0,977.0,819.0,80.0,23.26,119.3,5.0,92.0,29.0,3.0,4.0,0.0,0.0,0.0,0.0,Sabbir Rahman,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Sabbir Rahman,Bangladesh
+Test,0.0,134.0,5134.0,8852.0,206.0,38.89,58.0,2.0,656.0,41.0,11.0,31.0,10.0,1.0,0.0,0.0,Tamim Iqbal,Bangladesh
+ODI,243.0,240.0,8357.0,10642.0,158.0,36.65,78.53,12.0,925.0,103.0,19.0,56.0,14.0,0.0,0.0,0.0,Tamim Iqbal,Bangladesh
+T20,78.0,78.0,1758.0,1500.0,103.0,24.08,117.2,5.0,189.0,45.0,6.0,7.0,1.0,0.0,0.0,0.0,Tamim Iqbal,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Tamim Iqbal,Bangladesh
+Test,16.0,30.0,831.0,1442.0,149.0,27.7,57.63,0.0,109.0,9.0,2.0,4.0,1.0,0.0,0.0,0.0,Soumya Sarkar,Bangladesh
+ODI,76.0,71.0,2198.0,2282.0,169.0,32.32,96.32,3.0,256.0,52.0,9.0,13.0,3.0,0.0,0.0,0.0,Soumya Sarkar,Bangladesh
+T20,87.0,86.0,1462.0,1197.0,68.0,17.83,122.14,4.0,145.0,55.0,13.0,5.0,0.0,0.0,0.0,0.0,Soumya Sarkar,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Soumya Sarkar,Bangladesh
+Test,94.0,174.0,6007.0,12392.0,219.0,37.54,48.48,14.0,713.0,36.0,13.0,27.0,11.0,3.0,0.0,0.0,Mushfiqur Rahim,Bangladesh
+ODI,274.0,256.0,7795.0,9780.0,144.0,36.26,79.71,41.0,617.0,100.0,12.0,49.0,9.0,0.0,0.0,0.0,Mushfiqur Rahim,Bangladesh
+T20,102.0,93.0,1500.0,1305.0,72.0,19.23,114.95,15.0,126.0,37.0,8.0,6.0,0.0,0.0,0.0,0.0,Mushfiqur Rahim,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mushfiqur Rahim,Bangladesh
+Test,48.0,84.0,2788.0,4740.0,141.0,33.59,58.82,1.0,345.0,16.0,2.0,17.0,4.0,0.0,0.0,0.0,Litton Das,Bangladesh
+ODI,94.0,93.0,2569.0,2986.0,176.0,29.53,86.04,6.0,274.0,45.0,15.0,12.0,5.0,0.0,0.0,0.0,Litton Das,Bangladesh
+T20,95.0,93.0,2021.0,1619.0,83.0,22.46,124.84,3.0,210.0,58.0,6.0,11.0,0.0,0.0,0.0,0.0,Litton Das,Bangladesh
+IPL,1.0,1.0,4.0,4.0,4.0,4.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Litton Das,Bangladesh
+Test,10.0,18.0,333.0,752.0,67.0,18.5,44.29,0.0,32.0,3.0,4.0,2.0,0.0,0.0,0.0,0.0,Mohammad Mithun,Bangladesh
+ODI,34.0,30.0,714.0,921.0,73.0,27.46,77.53,4.0,61.0,16.0,2.0,6.0,0.0,0.0,0.0,0.0,Mohammad Mithun,Bangladesh
+T20,17.0,13.0,127.0,136.0,47.0,10.58,93.39,1.0,10.0,4.0,2.0,0.0,0.0,0.0,0.0,0.0,Mohammad Mithun,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mohammad Mithun,Bangladesh
+Test,36.0,67.0,797.0,1186.0,79.0,12.85,67.21,5.0,95.0,22.0,12.0,3.0,0.0,0.0,0.0,0.0,Mashrafe Mortaza,Bangladesh
+ODI,220.0,158.0,1787.0,2041.0,51.0,13.75,87.56,28.0,149.0,62.0,15.0,1.0,0.0,0.0,0.0,0.0,Mashrafe Mortaza,Bangladesh
+T20,54.0,39.0,377.0,278.0,36.0,13.46,135.62,11.0,28.0,23.0,6.0,0.0,0.0,0.0,0.0,0.0,Mashrafe Mortaza,Bangladesh
+IPL,1.0,1.0,2.0,2.0,2.0,0.0,100.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mashrafe Mortaza,Bangladesh
+Test,27.0,47.0,265.0,603.0,45.0,9.46,43.95,19.0,34.0,4.0,7.0,0.0,0.0,0.0,0.0,0.0,Rubel Hossain,Bangladesh
+ODI,104.0,53.0,144.0,277.0,17.0,4.97,51.99,24.0,14.0,2.0,11.0,0.0,0.0,0.0,0.0,0.0,Rubel Hossain,Bangladesh
+T20,28.0,15.0,20.0,36.0,8.0,4.0,55.56,10.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,Rubel Hossain,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Rubel Hossain,Bangladesh
+Test,15.0,22.0,66.0,162.0,16.0,4.4,40.75,7.0,3.0,5.0,8.0,0.0,0.0,0.0,0.0,0.0,Mustafizur Rahman,Bangladesh
+ODI,109.0,54.0,166.0,319.0,20.0,7.9,52.04,33.0,18.0,1.0,9.0,0.0,0.0,0.0,0.0,0.0,Mustafizur Rahman,Bangladesh
+T20,106.0,32.0,87.0,117.0,15.0,4.58,74.36,13.0,3.0,5.0,7.0,0.0,0.0,0.0,0.0,0.0,Mustafizur Rahman,Bangladesh
+IPL,57.0,9.0,13.0,23.0,8.0,13.0,56.53,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,Mustafizur Rahman,Bangladesh
+Test,51.0,93.0,1952.0,3920.0,103.0,23.52,49.8,10.0,231.0,20.0,6.0,9.0,1.0,0.0,0.0,0.0,Mehidy Hasan Miraz,Bangladesh
+ODI,105.0,76.0,1617.0,2105.0,112.0,24.5,76.82,10.0,137.0,27.0,4.0,6.0,2.0,0.0,0.0,0.0,Mehidy Hasan Miraz,Bangladesh
+T20,29.0,24.0,354.0,305.0,46.0,17.7,116.07,4.0,29.0,10.0,2.0,0.0,0.0,0.0,0.0,0.0,Mehidy Hasan Miraz,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mehidy Hasan Miraz,Bangladesh
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mohammad Saifuddin,Bangladesh
+ODI,29.0,19.0,362.0,422.0,51.0,36.2,85.79,9.0,29.0,6.0,1.0,2.0,0.0,0.0,0.0,0.0,Mohammad Saifuddin,Bangladesh
+T20,38.0,21.0,206.0,180.0,39.0,18.73,114.45,10.0,16.0,7.0,2.0,0.0,0.0,0.0,0.0,0.0,Mohammad Saifuddin,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mohammad Saifuddin,Bangladesh
+Test,13.0,22.0,36.0,157.0,8.0,2.57,22.93,8.0,4.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,Abu Jayed,Bangladesh
+ODI,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Abu Jayed,Bangladesh
+T20,3.0,2.0,3.0,7.0,2.0,1.5,42.86,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Abu Jayed,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Abu Jayed,Bangladesh
+Test,50.0,94.0,2914.0,5456.0,150.0,33.11,53.41,6.0,338.0,24.0,11.0,16.0,5.0,0.0,0.0,0.0,Mahmudullah,Bangladesh
+ODI,239.0,209.0,5689.0,7330.0,128.0,36.47,77.62,53.0,426.0,107.0,10.0,32.0,4.0,0.0,0.0,0.0,Mahmudullah,Bangladesh
+T20,141.0,130.0,2443.0,2083.0,64.0,23.49,117.29,26.0,184.0,77.0,5.0,8.0,0.0,0.0,0.0,0.0,Mahmudullah,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mahmudullah,Bangladesh
+Test,4.0,8.0,173.0,375.0,75.0,28.83,46.14,2.0,13.0,4.0,1.0,1.0,0.0,0.0,0.0,0.0,Mosaddek Hossain,Bangladesh
+ODI,43.0,35.0,634.0,762.0,52.0,25.36,83.21,10.0,58.0,13.0,1.0,3.0,0.0,0.0,0.0,0.0,Mosaddek Hossain,Bangladesh
+T20,33.0,31.0,389.0,341.0,48.0,18.52,114.08,10.0,26.0,11.0,4.0,0.0,0.0,0.0,0.0,0.0,Mosaddek Hossain,Bangladesh
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Mosaddek Hossain,Bangladesh
+Test,71.0,130.0,4609.0,7473.0,217.0,37.78,61.68,8.0,556.0,28.0,6.0,31.0,5.0,1.0,0.0,0.0,Shakib Al Hasan,Bangladesh
+ODI,247.0,234.0,7570.0,9138.0,134.0,37.11,82.85,30.0,699.0,54.0,12.0,56.0,9.0,0.0,0.0,0.0,Shakib Al Hasan,Bangladesh
+T20,129.0,126.0,2551.0,2104.0,84.0,23.19,121.25,16.0,258.0,53.0,9.0,13.0,0.0,0.0,0.0,0.0,Shakib Al Hasan,Bangladesh
+IPL,71.0,52.0,793.0,637.0,66.0,19.83,124.49,12.0,73.0,21.0,4.0,2.0,0.0,0.0,0.0,0.0,Shakib Al Hasan,Bangladesh
+Test,5.0,10.0,278.0,618.0,62.0,27.8,44.99,0.0,30.0,1.0,1.0,2.0,0.0,0.0,0.0,0.0,Aaron Finch,Australia
+ODI,146.0,142.0,5406.0,6163.0,153.0,38.89,87.72,3.0,533.0,129.0,16.0,30.0,17.0,0.0,0.0,0.0,Aaron Finch,Australia
+T20,103.0,103.0,3120.0,2189.0,172.0,34.29,142.54,12.0,309.0,125.0,8.0,19.0,2.0,0.0,0.0,0.0,Aaron Finch,Australia
+IPL,92.0,90.0,2091.0,1631.0,88.0,24.89,128.21,6.0,214.0,78.0,8.0,15.0,0.0,0.0,0.0,0.0,Aaron Finch,Australia
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Adam Zampa,Australia
+ODI,111.0,55.0,362.0,545.0,36.0,10.06,66.43,19.0,31.0,2.0,6.0,0.0,0.0,0.0,0.0,0.0,Adam Zampa,Australia
+T20,95.0,22.0,68.0,76.0,13.0,5.67,89.48,10.0,7.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,Adam Zampa,Australia
+IPL,21.0,5.0,15.0,24.0,7.0,3.0,62.5,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,Adam Zampa,Australia
+Test,39.0,57.0,1757.0,2824.0,156.0,35.14,62.22,7.0,186.0,12.0,3.0,9.0,2.0,0.0,0.0,0.0,Alex Carey,Australia
+ODI,80.0,72.0,2149.0,2364.0,106.0,35.82,90.91,12.0,203.0,24.0,4.0,12.0,1.0,0.0,0.0,0.0,Alex Carey,Australia
+T20,38.0,26.0,233.0,215.0,37.0,11.1,108.38,5.0,19.0,7.0,2.0,0.0,0.0,0.0,0.0,0.0,Alex Carey,Australia
+IPL,3.0,3.0,32.0,29.0,14.0,16.0,110.35,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,Alex Carey,Australia
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Andrew Tye,Australia
+ODI,7.0,7.0,57.0,48.0,19.0,14.25,118.75,3.0,5.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,Andrew Tye,Australia
+T20,32.0,15.0,83.0,76.0,20.0,10.38,109.22,7.0,5.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,Andrew Tye,Australia
+IPL,30.0,13.0,91.0,76.0,25.0,10.11,119.74,4.0,6.0,5.0,2.0,0.0,0.0,0.0,0.0,0.0,Andrew Tye,Australia
+Test,5.0,7.0,195.0,351.0,98.0,32.5,55.56,1.0,24.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,Ashton Agar,Australia
+ODI,22.0,18.0,322.0,388.0,48.0,24.77,82.99,5.0,28.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,Ashton Agar,Australia
+T20,49.0,29.0,279.0,278.0,29.0,11.63,100.36,5.0,19.0,9.0,4.0,0.0,0.0,0.0,0.0,0.0,Ashton Agar,Australia
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Ashton Agar,Australia
+Test,28.0,43.0,1377.0,2835.0,174.0,36.24,48.58,5.0,152.0,13.0,3.0,6.0,2.0,0.0,0.0,0.0,Cameron Green,Australia
+ODI,28.0,24.0,626.0,756.0,89.0,36.82,82.81,7.0,54.0,12.0,1.0,2.0,0.0,0.0,0.0,0.0,Cameron Green,Australia
+T20,13.0,12.0,263.0,172.0,62.0,26.3,152.91,2.0,21.0,16.0,0.0,3.0,0.0,0.0,0.0,0.0,Cameron Green,Australia
+IPL,29.0,28.0,707.0,460.0,100.0,41.59,153.7,11.0,62.0,32.0,0.0,2.0,1.0,0.0,0.0,0.0,Cameron Green,Australia
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Daniel Sams,Australia
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+IPL,7.0,5.0,52.0,47.0,24.0,13.0,110.64,1.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,shoaib-malik,Pakistan
+Test,6.0,11.0,300.0,479.0,56.0,33.33,62.64,2.0,38.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,shadab-khan,Pakistan
+ODI,70.0,44.0,855.0,997.0,86.0,25.91,85.76,11.0,51.0,19.0,3.0,4.0,0.0,0.0,0.0,0.0,shadab-khan,Pakistan
+T20,109.0,56.0,737.0,530.0,52.0,17.55,139.06,14.0,51.0,36.0,6.0,1.0,0.0,0.0,0.0,0.0,shadab-khan,Pakistan
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,shadab-khan,Pakistan
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,imad-wasim,Pakistan
+ODI,55.0,40.0,986.0,894.0,63.0,42.87,110.3,17.0,91.0,19.0,1.0,5.0,0.0,0.0,0.0,0.0,imad-wasim,Pakistan
+T20,75.0,50.0,554.0,426.0,64.0,15.83,130.05,15.0,55.0,12.0,6.0,1.0,0.0,0.0,0.0,0.0,imad-wasim,Pakistan
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,imad-wasim,Pakistan
+Test,54.0,95.0,3031.0,4320.0,118.0,36.96,70.17,13.0,309.0,9.0,4.0,21.0,4.0,0.0,0.0,0.0,sarfaraz-ahmed,Pakistan
+ODI,117.0,91.0,2315.0,2635.0,105.0,33.55,87.86,22.0,174.0,12.0,1.0,11.0,2.0,0.0,0.0,0.0,sarfaraz-ahmed,Pakistan
+T20,61.0,42.0,818.0,653.0,89.0,27.27,125.27,12.0,79.0,15.0,2.0,3.0,0.0,0.0,0.0,0.0,sarfaraz-ahmed,Pakistan
+IPL,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,sarfaraz-ahmed,Pakistan
+Test,56.0,102.0,3538.0,7886.0,218.0,36.1,44.87,4.0,405.0,41.0,5.0,17.0,8.0,1.0,0.0,0.0,Darren Bravo,West Indies
+ODI,122.0,117.0,3109.0,4434.0,124.0,29.61,70.12,12.0,252.0,75.0,9.0,18.0,4.0,0.0,0.0,0.0,Darren Bravo,West Indies
+T20,26.0,22.0,405.0,379.0,43.0,21.32,106.87,3.0,32.0,14.0,3.0,0.0,0.0,0.0,0.0,0.0,Darren Bravo,West Indies
+IPL,1.0,1.0,6.0,5.0,6.0,0.0,120.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Darren Bravo,West Indies
+Test,56.0,102.0,3538.0,7886.0,218.0,36.1,44.87,4.0,405.0,41.0,5.0,17.0,8.0,1.0,0.0,0.0,Chris Gayle,West Indies
+ODI,122.0,117.0,3109.0,4434.0,124.0,29.61,70.12,12.0,252.0,75.0,9.0,18.0,4.0,0.0,0.0,0.0,Chris Gayle,West Indies
+T20,26.0,22.0,405.0,379.0,43.0,21.32,106.87,3.0,32.0,14.0,3.0,0.0,0.0,0.0,0.0,0.0,Chris Gayle,West Indies
+IPL,1.0,1.0,6.0,5.0,6.0,0.0,120.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Chris Gayle,West Indies
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Evin Lewis,West Indies
+ODI,63.0,60.0,2131.0,2472.0,176.0,38.05,86.21,4.0,206.0,69.0,3.0,11.0,5.0,0.0,0.0,0.0,Evin Lewis,West Indies
+T20,61.0,60.0,1643.0,1081.0,125.0,28.82,151.99,3.0,125.0,124.0,5.0,12.0,2.0,0.0,0.0,0.0,Evin Lewis,West Indies
+IPL,27.0,26.0,654.0,477.0,65.0,27.25,137.11,2.0,62.0,36.0,2.0,4.0,0.0,0.0,0.0,0.0,Evin Lewis,West Indies
+Test,16.0,30.0,838.0,1138.0,93.0,27.93,73.64,0.0,85.0,27.0,0.0,5.0,0.0,0.0,0.0,0.0,Shimron Hetmyer,West Indies
+ODI,56.0,51.0,1539.0,1460.0,139.0,32.06,105.42,3.0,117.0,56.0,3.0,4.0,5.0,0.0,0.0,0.0,Shimron Hetmyer,West Indies
+T20,62.0,52.0,942.0,795.0,81.0,20.04,118.5,5.0,63.0,47.0,4.0,5.0,0.0,0.0,0.0,0.0,Shimron Hetmyer,West Indies
+IPL,73.0,67.0,1285.0,835.0,75.0,31.34,153.9,26.0,77.0,86.0,2.0,4.0,0.0,0.0,0.0,0.0,Shimron Hetmyer,West Indies
+Test,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Fabian Allen,West Indies
+ODI,20.0,16.0,200.0,203.0,51.0,15.38,98.53,3.0,18.0,8.0,2.0,1.0,0.0,0.0,0.0,0.0,Fabian Allen,West Indies
+T20,39.0,27.0,272.0,199.0,34.0,15.11,136.69,9.0,16.0,21.0,5.0,0.0,0.0,0.0,0.0,0.0,Fabian Allen,West Indies
+IPL,5.0,4.0,14.0,19.0,8.0,7.0,73.69,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,Fabian Allen,West Indies
+Test,69.0,123.0,3073.0,5595.0,202.0,29.83,54.93,20.0,359.0,55.0,11.0,14.0,3.0,1.0,0.0,0.0,Jason Holder,West Indies
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+T20,41.0,27.0,310.0,274.0,37.0,14.76,113.14,6.0,13.0,22.0,3.0,0.0,0.0,0.0,0.0,0.0,Carlos Brathwaite,West Indies
+IPL,16.0,14.0,181.0,111.0,43.0,13.92,163.07,1.0,10.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,Carlos Brathwaite,West Indies

Bowling_10_Teams_Final.csv

@@ -0,0 +1,629 @@
+Format,Matches,Innings,Balls,Runs,Maidens,Wickets,Avg,Eco,SR,BBI,BBM,4w,5w,10w,player_name,Country
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Aftab Alam,Afghanistan
+ODI,27,27,1257,1033,14,41,25.2,4.93,30.66,25-Apr,25-Apr,1,0,0,Aftab Alam,Afghanistan
+T20,12,12,245,324,0,11,29.45,7.93,22.27,23-Feb,23-Feb,0,0,0,Aftab Alam,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Aftab Alam,Afghanistan
+Test,6,2,18,17,0,0,0.0,5.67,0.0,0/1,0/1,0,0,0,Asghar Afghan,Afghanistan
+ODI,114,7,139,91,1,3,30.33,3.93,46.33,1-Jan,1-Jan,0,0,0,Asghar Afghan,Afghanistan
+T20,75,1,4,4,0,1,4.0,0.0,4.0,4-Jan,4-Jan,0,0,0,Asghar Afghan,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Asghar Afghan,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dawlat Zadran,Afghanistan
+ODI,82,80,3769,3423,42,115,29.77,5.45,32.77,22-Apr,22-Apr,3,0,0,Dawlat Zadran,Afghanistan
+T20,33,34,741,980,2,40,24.5,7.94,18.52,Apr-44,Apr-44,1,0,0,Dawlat Zadran,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dawlat Zadran,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Gulbadin Naib,Afghanistan
+ODI,89,80,2883,2675,12,74,36.15,5.57,38.96,Jun-43,Jun-43,3,1,0,Gulbadin Naib,Afghanistan
+T20,74,44,649,860,1,33,26.06,7.95,19.67,20-Apr,20-Apr,1,0,0,Gulbadin Naib,Afghanistan
+IPL,2,1,6,12,0,0,0.0,12.0,0.0,0/12,0/12,0,0,0,Gulbadin Naib,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hamid Hassan,Afghanistan
+ODI,38,37,1734,1331,25,59,22.56,4.61,29.39,May-45,May-45,2,1,0,Hamid Hassan,Afghanistan
+T20,25,25,544,580,2,35,16.57,6.4,15.54,22-Apr,22-Apr,1,0,0,Hamid Hassan,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hamid Hassan,Afghanistan
+Test,10,5,84,59,0,0,0.0,4.21,0.0,0/4,0/4,0,0,0,Hashmatullah Shahidi,Afghanistan
+ODI,90,2,18,25,0,0,0.0,8.33,0.0,0/8,0/8,0,0,0,Hashmatullah Shahidi,Afghanistan
+T20,6,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hashmatullah Shahidi,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hashmatullah Shahidi,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hazratullah Zazai,Afghanistan
+ODI,16,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hazratullah Zazai,Afghanistan
+T20,45,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hazratullah Zazai,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hazratullah Zazai,Afghanistan
+Test,7,1,12,13,0,1,13.0,6.5,12.0,13-Jan,13-Jan,0,0,0,Ibrahim Zadran,Afghanistan
+ODI,36,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ibrahim Zadran,Afghanistan
+T20,44,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ibrahim Zadran,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ibrahim Zadran,Afghanistan
+Test,3,5,546,254,17,8,31.75,2.79,68.25,Mar-36,Apr-95,0,0,0,Mohammad Nabi,Afghanistan
+ODI,173,164,7960,5706,52,176,32.42,4.3,45.23,17-May,17-May,4,1,0,Mohammad Nabi,Afghanistan
+T20,131,122,2242,2730,5,97,28.14,7.31,23.11,10-Apr,10-Apr,3,0,0,Mohammad Nabi,Afghanistan
+IPL,24,23,417,517,0,15,34.47,7.44,27.8,11-Apr,11-Apr,1,0,0,Mohammad Nabi,Afghanistan
+Test,2,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Shahzad,Afghanistan
+ODI,84,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Shahzad,Afghanistan
+T20,72,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Shahzad,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Shahzad,Afghanistan
+Test,1,1,90,75,1,1,75.0,5.0,90.0,Jan-75,Jan-75,0,0,0,Muheeb Ur Rahman,Afghanistan
+ODI,75,74,3968,2863,39,101,28.35,4.33,39.29,May-50,May-50,3,1,0,Muheeb Ur Rahman,Afghanistan
+T20,49,49,1080,1141,1,63,18.11,6.34,17.14,20-May,20-May,1,1,0,Muheeb Ur Rahman,Afghanistan
+IPL,19,19,434,592,0,19,31.16,8.18,22.84,27-Mar,27-Mar,0,0,0,Muheeb Ur Rahman,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Najibullah Zadran,Afghanistan
+ODI,92,2,30,30,0,0,0.0,6.0,0.0,0/9,0/9,0,0,0,Najibullah Zadran,Afghanistan
+T20,107,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Najibullah Zadran,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Najibullah Zadran,Afghanistan
+Test,2,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Noor Ali Zadran,Afghanistan
+ODI,51,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Noor Ali Zadran,Afghanistan
+T20,22,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Noor Ali Zadran,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Noor Ali Zadran,Afghanistan
+Test,11,4,84,53,1,1,53.0,3.79,84.0,30-Jan,Jan-34,0,0,0,Rahmat Shah,Afghanistan
+ODI,123,29,543,532,2,15,35.47,5.88,36.2,May-32,May-32,0,1,0,Rahmat Shah,Afghanistan
+T20,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rahmat Shah,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rahmat Shah,Afghanistan
+Test,6,11,1864,920,53,45,20.44,2.96,41.42,Jul-66,11/104,2,5,3,Rashid Khan,Afghanistan
+ODI,114,106,5741,4060,35,199,20.4,4.24,28.85,18-Jul,18-Jul,6,5,0,Rashid Khan,Afghanistan
+T20,96,96,2192,2222,1,161,13.8,6.08,13.61,3-May,3-May,8,2,0,Rashid Khan,Afghanistan
+IPL,122,122,2883,3300,4,150,22.0,6.87,19.22,24-Apr,24-Apr,2,0,0,Rashid Khan,Afghanistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Samiullah Shinwari,Afghanistan
+ODI,84,65,2111,1729,10,45,38.42,4.91,46.91,Apr-31,Apr-31,1,0,0,Samiullah Shinwari,Afghanistan
+T20,64,38,634,688,0,28,24.57,6.51,22.64,13-May,13-May,1,1,0,Samiullah Shinwari,Afghanistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Samiullah Shinwari,Afghanistan
+Test,16,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Eoin Morgan,England
+ODI,248,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Eoin Morgan,England
+T20,115,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Eoin Morgan,England
+IPL,83,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Eoin Morgan,England
+Test,152,156,5851,3221,158,71,45.37,3.3,82.41,5/8,5/33,2,1,0,Joe Root,England
+ODI,177,77,1755,1731,2,28,61.82,5.92,62.68,3/52,3/52,0,0,0,Joe Root,England
+T20,32,9,84,139,0,6,23.17,9.93,14.0,2/9,2/9,0,0,0,Joe Root,England
+IPL,3,1,12,14,0,0,0.0,7.0,0.0,0/14,0/14,0,0,0,Joe Root,England
+Test,5,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jason Roy,England
+ODI,116,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jason Roy,England
+T20,64,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jason Roy,England
+IPL,21,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jason Roy,England
+Test,22,8,222,131,4,2,65.5,3.54,111.0,2/33,2/33,0,0,0,Dawid Malan,England
+ODI,30,2,15,17,0,1,17.0,6.8,15.0,1/5,1/5,0,0,0,Dawid Malan,England
+T20,62,1,12,27,0,1,27.0,13.5,12.0,1/27,1/27,0,0,0,Dawid Malan,England
+IPL,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dawid Malan,England
+Test,68,119,12610,7612,292,204,37.31,3.62,61.81,6/53,10/112,13,5,1,Moeen Ali,England
+ODI,138,128,5988,5311,13,111,47.85,5.32,53.95,4/46,4/46,2,0,0,Moeen Ali,England
+T20,92,71,999,1384,1,51,27.14,8.31,19.59,3/24,3/24,0,0,0,Moeen Ali,England
+IPL,67,52,758,893,0,35,25.51,7.07,21.66,4/26,4/26,1,0,0,Moeen Ali,England
+Test,110,160,12252,6798,359,210,32.37,3.33,58.34,6/22,8/161,8,4,0,Ben Stokes,England
+ODI,114,88,3110,3137,8,74,42.39,6.05,42.03,5/61,5/61,1,1,0,Ben Stokes,England
+T20,43,36,612,856,1,26,32.92,8.39,23.54,3/26,3/26,0,0,0,Ben Stokes,England
+IPL,45,38,689,992,2,28,35.43,8.64,24.61,3/15,3/15,0,0,0,Ben Stokes,England
+Test,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Liam Livingstone,England
+ODI,39,31,968,982,2,25,39.28,6.09,38.72,3/16,3/16,0,0,0,Liam Livingstone,England
+T20,60,41,576,838,1,33,25.39,8.73,17.45,3/17,3/17,0,0,0,Liam Livingstone,England
+IPL,40,23,270,407,0,11,37.0,9.04,24.55,3/27,3/27,0,0,0,Liam Livingstone,England
+Test,57,109,10133,5112,380,181,28.24,3.03,55.98,6/17,11/102,5,5,1,Chris Woakes,England
+ODI,122,118,5737,5193,53,173,30.02,5.43,33.16,6/45,6/45,11,3,0,Chris Woakes,England
+T20,33,33,611,822,1,31,26.52,8.07,19.71,3/4,3/4,0,0,0,Chris Woakes,England
+IPL,21,21,440,658,0,30,21.93,8.97,14.67,3/6,3/6,0,0,0,Chris Woakes,England
+Test,2,3,396,200,14,2,100.0,3.03,198.0,1/65,1/82,0,0,0,Tom Curran,England
+ODI,28,28,1308,1290,8,34,37.94,5.92,38.47,5/35,5/35,2,1,0,Tom Curran,England
+T20,30,29,588,907,1,29,31.28,9.26,20.28,4/36,4/36,1,0,0,Tom Curran,England
+IPL,13,13,238,430,0,13,33.08,10.84,18.31,3/29,3/29,0,0,0,Tom Curran,England
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+ODI,3,3,114,97,1,4,24.25,5.11,28.5,3/44,3/44,0,0,0,Lewis Gregory,England
+T20,9,5,78,117,0,2,58.5,9.0,39.0,1/10,1/10,0,0,0,Lewis Gregory,England
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Lewis Gregory,England
+Test,24,42,3091,1669,96,47,35.51,3.24,65.77,4/58,5/92,2,0,0,Sam Curran,England
+ODI,35,35,1325,1376,10,33,41.7,6.23,40.15,5/48,5/48,1,1,0,Sam Curran,England
+T20,58,57,1043,1462,2,54,27.07,8.41,19.31,5/10,5/10,0,1,0,Sam Curran,England
+IPL,60,59,1187,1913,0,58,32.98,9.67,20.47,4/11,4/11,1,0,0,Sam Curran,England
+Test,100,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jonny Bairstow,England
+ODI,107,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jonny Bairstow,England
+T20,80,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jonny Bairstow,England
+IPL,50,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jonny Bairstow,England
+Test,57,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jos Buttler,England
+ODI,187,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jos Buttler,England
+T20,134,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jos Buttler,England
+IPL,108,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jos Buttler,England
+Test,3,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sam Billings,England
+ODI,28,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sam Billings,England
+T20,37,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sam Billings,England
+IPL,30,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sam Billings,England
+Test,19,34,3816,2390,50,60,39.83,3.76,63.6,5/49,7/178,5,2,0,Adil Rashid,England
+ODI,149,143,7517,7058,14,215,32.83,5.63,34.96,5/27,5/27,9,2,0,Adil Rashid,England
+T20,124,119,2600,3190,5,131,24.35,7.36,19.85,4/2,4/2,3,0,0,Adil Rashid,England
+IPL,3,3,60,91,0,2,45.5,9.1,30.0,2/23,2/23,0,0,0,Adil Rashid,England
+Test,13,24,2609,1304,95,42,31.05,3.0,62.12,6/45,8/85,0,3,0,Jofra Archer,England
+ODI,31,31,1631,1421,18,54,26.31,5.23,30.2,6/40,6/40,0,1,0,Jofra Archer,England
+T20,34,34,754,1002,2,41,24.44,7.97,18.39,4/33,4/33,1,0,0,Jofra Archer,England
+IPL,41,41,969,1247,2,48,25.98,7.72,20.19,3/15,3/15,0,0,0,Jofra Archer,England
+Test,5,9,610,400,17,17,23.53,3.93,35.88,3/29,4/68,0,0,0,Olly Stone,England
+ODI,10,9,394,399,2,9,44.33,6.08,43.78,4/85,4/85,1,0,0,Olly Stone,England
+T20,1,1,24,36,0,0,0.0,9.0,0.0,0/36,0/36,0,0,0,Olly Stone,England
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Olly Stone,England
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Reece Topley,England
+ODI,30,30,1392,1257,17,47,26.74,5.42,29.62,6/24,6/24,2,1,0,Reece Topley,England
+T20,35,35,706,978,0,33,29.64,8.31,21.39,3/22,3/22,0,0,0,Reece Topley,England
+IPL,5,5,102,182,0,5,36.4,10.71,20.4,2/27,2/27,0,0,0,Reece Topley,England
+Test,8,16,1530,752,74,21,35.81,2.95,72.86,4/18,7/50,1,0,0,Chris Jordan,England
+ODI,35,35,1660,1660,5,46,36.09,6.0,36.09,5/29,5/29,0,1,0,Chris Jordan,England
+T20,95,94,1953,2846,2,108,26.35,8.74,18.08,4/6,4/6,4,0,0,Chris Jordan,England
+IPL,34,34,668,1070,1,30,35.67,9.61,22.27,4/11,4/11,1,0,0,Chris Jordan,England
+Test,123,11,175,84,2,0,0.0,2.88,0.0,0/0,0/0,0,0,0,Virat Kohli,India
+ODI,302,50,662,680,1,5,136.0,6.16,132.4,1/13,1/13,0,0,0,Virat Kohli,India
+T20,125,13,152,204,0,4,51.0,8.05,38.0,1/13,1/13,0,0,0,Virat Kohli,India
+IPL,253,26,251,368,0,4,92.0,8.8,62.75,2/25,2/25,0,0,0,Virat Kohli,India
+Test,67,16,383,224,5,2,112.0,3.51,191.5,1/26,1/35,0,0,0,Rohit Sharma,India
+ODI,273,40,610,533,2,9,59.22,5.24,67.78,2/27,2/27,0,0,0,Rohit Sharma,India
+T20,159,9,68,113,0,1,113.0,9.97,68.0,1/22,1/22,0,0,0,Rohit Sharma,India
+IPL,258,32,339,453,0,15,30.2,8.02,22.6,4/6,4/6,1,0,0,Rohit Sharma,India
+Test,34,5,54,18,2,0,0.0,2.0,0.0,0/0,0/0,0,0,0,Shikhar Dhawan,India
+ODI,167,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Shikhar Dhawan,India
+T20,68,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Shikhar Dhawan,India
+IPL,222,6,48,66,0,4,16.5,8.25,12.0,1/7,1/7,0,0,0,Shikhar Dhawan,India
+Test,32,1,7,1,0,0,0.0,0.86,0.0,0/1,0/1,0,0,0,Shubman Gill,India
+ODI,55,2,18,25,0,0,0.0,8.33,0.0,0/11,0/11,0,0,0,Shubman Gill,India
+T20,21,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Shubman Gill,India
+IPL,104,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Shubman Gill,India
+Test,14,1,6,2,0,0,0.0,2.0,0.0,0/2,0/2,0,0,0,Shreyas Iyer,India
+ODI,70,5,37,39,0,0,0.0,6.32,0.0,0/1,0/1,0,0,0,Shreyas Iyer,India
+T20,51,1,2,2,0,0,0.0,0.0,0.0,0/2,0/2,0,0,0,Shreyas Iyer,India
+IPL,116,1,6,7,0,0,0.0,7.0,0.0,0/7,0/7,0,0,0,Shreyas Iyer,India
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Manish Pandey,India
+ODI,29,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Manish Pandey,India
+T20,39,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Manish Pandey,India
+IPL,171,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Manish Pandey,India
+Test,21,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mayank Agarwal,India
+ODI,5,1,6,10,0,0,0.0,10.0,0.0,0/10,0/10,0,0,0,Mayank Agarwal,India
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mayank Agarwal,India
+IPL,127,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mayank Agarwal,India
+Test,5,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Prithvi Shaw,India
+ODI,6,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Prithvi Shaw,India
+T20,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Prithvi Shaw,India
+IPL,79,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Prithvi Shaw,India
+Test,103,2,12,3,0,0,0.0,1.5,0.0,0/1,0/1,0,0,0,Cheteshwar Pujara,India
+ODI,5,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Cheteshwar Pujara,India
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Cheteshwar Pujara,India
+IPL,30,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Cheteshwar Pujara,India
+Test,85,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ajinkya Rahane,India
+ODI,90,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ajinkya Rahane,India
+T20,20,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ajinkya Rahane,India
+IPL,186,1,6,5,0,1,5.0,5.0,6.0,1/5,1/5,0,0,0,Ajinkya Rahane,India
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ruturaj Gaikwad,India
+ODI,6,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ruturaj Gaikwad,India
+T20,23,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ruturaj Gaikwad,India
+IPL,67,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ruturaj Gaikwad,India
+Test,11,19,937,528,19,17,31.06,3.38,55.12,5/28,6/50,0,1,0,Hardik Pandya,India
+ODI,94,88,3460,3231,16,91,35.51,5.6,38.02,4/24,4/24,1,0,0,Hardik Pandya,India
+T20,114,102,1817,2485,4,94,26.44,8.21,19.33,4/16,4/16,3,0,0,Hardik Pandya,India
+IPL,137,93,1418,2150,0,64,33.59,9.1,22.16,3/17,3/17,0,0,0,Hardik Pandya,India
+Test,16,10,345,180,10,5,36.0,3.13,69.0,3/37,3/38,0,0,0,Hanuma Vihari,India
+ODI,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hanuma Vihari,India
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Hanuma Vihari,India
+IPL,24,6,42,47,0,1,47.0,6.71,42.0,1/5,1/5,0,0,0,Hanuma Vihari,India
+Test,80,150,18473,7798,729,323,24.14,2.53,57.19,7/42,10/110,13,15,3,Ravindra Jadeja,India
+ODI,204,196,10116,8180,59,231,35.41,4.85,43.79,5/33,5/33,7,2,0,Ravindra Jadeja,India
+T20,74,71,1356,1612,4,54,29.85,7.13,25.11,3/15,3/15,0,0,0,Ravindra Jadeja,India
+IPL,241,212,3847,4885,2,160,30.53,7.62,24.04,5/16,5/16,3,1,0,Ravindra Jadeja,India
+Test,11,19,1449,880,36,31,28.39,3.64,46.74,7/61,8/108,1,1,0,Shardul Thakur,India
+ODI,47,46,1940,2014,10,65,30.98,6.23,29.85,4/37,4/37,3,0,0,Shardul Thakur,India
+T20,25,24,506,772,0,33,23.39,9.15,15.33,4/27,4/27,1,0,0,Shardul Thakur,India
+IPL,96,93,1878,2888,3,96,30.08,9.23,19.56,4/36,4/36,1,0,0,Shardul Thakur,India
+Test,106,200,27246,12891,907,537,24.01,2.84,50.74,7/59,13/140,25,37,8,Ravichandran Ashwin,India
+ODI,116,114,6303,5180,37,156,33.21,4.93,40.4,4/25,4/25,1,0,0,Ravichandran Ashwin,India
+T20,65,65,1452,1672,3,72,23.22,6.91,20.17,4/8,4/8,2,0,0,Ravichandran Ashwin,India
+IPL,212,209,4548,5400,4,181,29.83,7.12,25.13,4/34,4/34,1,0,0,Ravichandran Ashwin,India
+Test,58,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,KL Rahul,India
+ODI,85,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,KL Rahul,India
+T20,72,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,KL Rahul,India
+IPL,132,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,KL Rahul,India
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sanju Samson,India
+ODI,16,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sanju Samson,India
+T20,42,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sanju Samson,India
+IPL,168,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sanju Samson,India
+Test,40,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Wriddhiman Saha,India
+ODI,9,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Wriddhiman Saha,India
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Wriddhiman Saha,India
+IPL,170,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Wriddhiman Saha,India
+Test,43,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rishabh Pant,India
+ODI,31,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rishabh Pant,India
+T20,76,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rishabh Pant,India
+IPL,112,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rishabh Pant,India
+Test,64,122,11515,6346,364,229,27.71,3.31,50.28,6/56,9/118,12,6,0,Mohammed Shami,India
+ODI,108,107,5326,4955,52,206,24.05,5.58,25.85,7/57,7/57,10,6,0,Mohammed Shami,India
+T20,25,25,510,761,1,27,28.19,8.95,18.89,3/15,3/15,0,0,0,Mohammed Shami,India
+IPL,111,111,2444,3444,3,128,26.91,8.45,19.09,4/11,4/11,2,0,0,Mohammed Shami,India
+Test,45,86,8630,3977,344,205,19.4,2.77,42.1,6/27,9/86,7,13,0,Jasprit Bumrah,India
+ODI,89,88,4580,3509,57,149,23.55,4.6,30.74,6/19,6/19,6,2,0,Jasprit Bumrah,India
+T20,70,69,1509,1579,12,89,17.74,6.28,16.96,3/7,3/7,0,0,0,Jasprit Bumrah,India
+IPL,133,133,3053,3716,7,165,22.52,7.3,18.5,5/10,5/10,2,2,0,Jasprit Bumrah,India
+Test,13,24,2093,1241,46,56,22.16,3.56,37.38,5/40,8/113,3,4,0,Kuldeep Yadav,India
+ODI,113,110,5754,4786,30,181,26.44,4.99,31.79,6/25,6/25,7,2,0,Kuldeep Yadav,India
+T20,40,39,860,971,2,69,14.07,6.77,12.46,5/17,5/17,1,2,0,Kuldeep Yadav,India
+IPL,85,83,1770,2408,1,89,27.06,8.16,19.89,4/14,4/14,4,0,0,Kuldeep Yadav,India
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Yuzvendra Chahal,India
+ODI,72,69,3739,3283,14,121,27.13,5.27,30.9,6/42,6/42,5,2,0,Yuzvendra Chahal,India
+T20,80,79,1764,2409,2,96,25.09,8.19,18.38,6/25,6/25,2,1,0,Yuzvendra Chahal,India
+IPL,161,160,3539,4636,4,205,22.61,7.86,17.26,5/40,5/40,6,1,0,Yuzvendra Chahal,India
+Test,2,4,251,172,5,4,43.0,4.11,62.75,2/54,4/119,0,0,0,Navdeep Saini,India
+ODI,8,8,420,481,0,6,80.17,6.87,70.0,2/58,2/58,0,0,0,Navdeep Saini,India
+T20,11,9,197,235,1,13,18.08,7.16,15.15,3/17,3/17,0,0,0,Navdeep Saini,India
+IPL,32,32,658,974,1,23,42.35,8.88,28.61,3/40,3/40,0,0,0,Navdeep Saini,India
+Test,57,112,8979,5263,245,170,30.96,3.52,52.82,6/88,10/133,6,3,1,Umesh Yadav,India
+ODI,75,73,3558,3565,23,106,33.63,6.01,33.57,4/31,4/31,4,0,0,Umesh Yadav,India
+T20,9,9,180,280,0,12,23.33,9.33,15.0,2/19,2/19,0,0,0,Umesh Yadav,India
+IPL,148,147,3050,4317,5,144,29.98,8.49,21.18,4/23,4/23,3,0,0,Umesh Yadav,India
+Test,36,67,5306,3074,164,100,30.74,3.48,53.06,6/15,8/126,6,3,0,Mohammed Siraj,India
+ODI,44,43,1975,1708,32,71,24.06,5.19,27.82,6/21,6/21,2,1,0,Mohammed Siraj,India
+T20,16,16,348,452,2,14,32.29,7.79,24.86,4/17,4/17,1,0,0,Mohammed Siraj,India
+IPL,94,94,1982,2876,4,93,30.92,8.71,21.31,4/21,4/21,2,0,0,Mohammed Siraj,India
+Test,47,18,428,298,9,8,37.25,4.18,53.5,3/11,3/11,0,0,0,Martin Guptil,NewZeland
+ODI,198,12,109,98,0,4,24.5,5.39,27.25,2/6,2/6,0,0,0,Martin Guptil,NewZeland
+T20,122,1,6,11,0,0,0.0,11.0,0.0,0/11,0/11,0,0,0,Martin Guptil,NewZeland
+IPL,13,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Martin Guptil,NewZeland
+Test,112,8,99,48,3,3,16.0,2.91,33.0,2/4,2/4,0,0,0,Ross Taylor,NewZeland
+ODI,236,6,42,35,0,0,0.0,5.0,0.0,0/0,0/0,0,0,0,Ross Taylor,NewZeland
+T20,102,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ross Taylor,NewZeland
+IPL,55,2,12,24,0,0,0.0,12.0,0.0,0/11,0/11,0,0,0,Ross Taylor,NewZeland
+Test,105,67,2151,1207,48,30,40.23,3.37,71.7,4/44,4/44,1,0,0,Kane Williamson,NewZeland
+ODI,173,65,1467,1310,2,37,35.41,5.36,39.65,4/22,4/22,1,0,0,Kane Williamson,NewZeland
+T20,93,12,118,164,0,6,27.33,8.34,19.67,2/16,2/16,0,0,0,Kane Williamson,NewZeland
+IPL,79,2,18,31,0,0,0.0,10.33,0.0,0/7,0/7,0,0,0,Kane Williamson,NewZeland
+Test,1,1,108,40,4,2,20.0,2.22,54.0,2/40,2/40,0,0,0,Colin Munro,NewZeland
+ODI,57,25,552,481,1,7,68.71,5.23,78.86,2/10,2/10,0,0,0,Colin Munro,NewZeland
+T20,65,12,118,186,0,4,46.5,9.46,29.5,1/12,1/12,0,0,0,Colin Munro,NewZeland
+IPL,13,2,12,15,0,0,0.0,7.5,0.0,0/7,0/7,0,0,0,Colin Munro,NewZeland
+Test,56,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Henry Nicholls,NewZeland
+ODI,78,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Henry Nicholls,NewZeland
+T20,10,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Henry Nicholls,NewZeland
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Henry Nicholls,NewZeland
+Test,12,21,1076,675,18,14,48.21,3.76,76.86,3/42,3/42,0,0,0,James Neesham,NewZeland
+ODI,76,72,2448,2556,6,71,36.0,6.26,34.48,5/27,5/27,2,2,0,James Neesham,NewZeland
+T20,83,57,771,1149,0,47,24.45,8.94,16.4,5/22,5/22,0,1,0,James Neesham,NewZeland
+IPL,14,13,216,334,0,8,41.75,9.28,27.0,3/12,3/12,0,0,0,James Neesham,NewZeland
+Test,29,53,4054,1615,163,49,32.96,2.39,82.73,6/41,7/64,1,1,0,Colin de Grandhomme,NewZeland
+ODI,45,45,1548,1230,10,30,41.0,4.77,51.6,3/26,3/26,0,0,0,Colin de Grandhomme,NewZeland
+T20,41,21,321,461,0,12,38.42,8.62,26.75,2/22,2/22,0,0,0,Colin de Grandhomme,NewZeland
+IPL,25,19,216,319,0,6,53.17,8.86,36.0,3/4,3/4,0,0,0,Colin de Grandhomme,NewZeland
+Test,30,51,5346,2526,178,74,34.14,2.84,72.24,7/53,13/157,1,2,1,Mitchell Santner,NewZeland
+ODI,118,112,5607,4505,24,126,35.75,4.82,44.5,5/50,5/50,0,2,0,Mitchell Santner,NewZeland
+T20,109,107,2268,2661,2,120,22.18,7.04,18.9,4/11,4/11,3,0,0,Mitchell Santner,NewZeland
+IPL,19,19,379,446,0,15,29.73,7.06,25.27,2/13,2/13,0,0,0,Mitchell Santner,NewZeland
+Test,88,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Latham,NewZeland
+ODI,157,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Latham,NewZeland
+T20,26,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Latham,NewZeland
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Latham,NewZeland
+Test,40,1,18,13,0,0,0.0,4.33,0.0,0/13,0/13,0,0,0,Tom Blundell,NewZeland
+ODI,12,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Blundell,NewZeland
+T20,9,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Blundell,NewZeland
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tom Blundell,NewZeland
+Test,78,149,17417,8717,655,317,27.5,3.0,54.94,6/30,10/80,18,10,1,Trent Boult,NewZeland
+ODI,114,113,6180,5146,76,211,24.39,5.0,29.29,7/34,7/34,10,6,0,Trent Boult,NewZeland
+T20,61,61,1389,1779,4,83,21.43,7.68,16.73,4/13,4/13,2,0,0,Trent Boult,NewZeland
+IPL,104,104,2355,3257,11,121,26.92,8.3,19.46,4/18,4/18,1,0,0,Trent Boult,NewZeland
+Test,30,59,6750,3581,231,120,29.84,3.18,56.25,7/23,9/55,6,4,0,Matt Henry,NewZeland
+ODI,91,89,4734,4094,57,165,24.81,5.19,28.69,5/30,5/30,12,3,0,Matt Henry,NewZeland
+T20,21,20,462,639,1,27,23.67,8.3,17.11,3/32,3/32,0,0,0,Matt Henry,NewZeland
+IPL,6,6,102,181,0,2,90.5,10.65,51.0,1/28,1/28,0,0,0,Matt Henry,NewZeland
+Test,107,203,23490,11832,888,391,30.26,3.02,60.08,7/64,10/108,19,15,1,Tim Southee,NewZeland
+ODI,161,159,8075,7447,80,221,33.7,5.53,36.54,7/33,7/33,5,3,0,Tim Southee,NewZeland
+T20,125,123,2753,3671,7,164,22.38,8.0,16.79,5/18,5/18,2,2,0,Tim Southee,NewZeland
+IPL,54,54,1206,1742,2,47,37.06,8.67,25.66,3/20,3/20,0,0,0,Tim Southee,NewZeland
+Test,21,38,4043,2500,91,58,43.1,3.71,69.71,6/86,8/173,2,1,0,Ish Sodhi,NewZeland
+ODI,55,51,2587,2384,12,64,37.25,5.53,40.42,6/39,6/39,1,1,0,Ish Sodhi,NewZeland
+T20,124,119,2501,3333,0,144,23.15,8.0,17.37,4/28,4/28,3,0,0,Ish Sodhi,NewZeland
+IPL,8,8,181,202,1,9,22.44,6.7,20.11,3/26,3/26,0,0,0,Ish Sodhi,NewZeland
+Test,1,1,66,47,1,0,0.0,4.27,0.0,0/47,0/47,0,0,0,Lockie Ferguson,NewZeland
+ODI,65,64,3300,3124,13,99,31.56,5.68,33.33,5/45,5/45,2,1,0,Lockie Ferguson,NewZeland
+T20,43,43,919,1087,5,64,16.98,7.1,14.36,5/21,5/21,2,1,0,Lockie Ferguson,NewZeland
+IPL,45,45,955,1426,1,46,31.0,8.96,20.76,4/28,4/28,1,0,0,Lockie Ferguson,NewZeland
+Test,45,21,483,254,9,3,84.67,3.16,161.0,2/27,2/27,0,0,0,Aiden Markram,South Africa
+ODI,77,37,1085,1017,2,20,50.85,5.62,54.25,2/18,2/18,0,0,0,Aiden Markram,South Africa
+T20,57,30,342,487,2,13,37.46,8.54,26.31,3/21,3/21,0,0,0,Aiden Markram,South Africa
+IPL,45,14,121,172,0,2,86.0,8.53,60.5,1/8,1/8,0,0,0,Aiden Markram,South Africa
+Test,4,8,250,147,9,11,13.36,3.53,22.73,3/13,5/25,0,0,0,Andile Phehlukwayo,South Africa
+ODI,85,79,3175,3040,17,97,31.34,5.74,32.73,4/22,4/22,3,0,0,Andile Phehlukwayo,South Africa
+T20,42,39,748,1112,0,50,22.24,8.92,14.96,4/24,4/24,1,0,0,Andile Phehlukwayo,South Africa
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Andile Phehlukwayo,South Africa
+Test,1,2,231,175,5,6,29.17,4.55,38.5,5/64,6/175,0,1,0,Beuran Hendricks,South Africa
+ODI,10,8,386,346,2,10,34.6,5.38,38.6,3/59,3/59,0,0,0,Beuran Hendricks,South Africa
+T20,19,19,409,627,0,25,25.08,9.2,16.36,4/14,4/14,1,0,0,Beuran Hendricks,South Africa
+IPL,7,7,150,235,0,9,26.11,9.4,16.67,3/36,3/36,0,0,0,Beuran Hendricks,South Africa
+Test,4,8,623,459,15,12,38.25,4.42,51.92,3/38,5/45,0,0,0,Chris Morris,South Africa
+ODI,42,40,1894,1756,10,48,36.58,5.56,39.46,4/31,4/31,2,0,0,Chris Morris,South Africa
+T20,23,23,498,697,3,34,20.5,8.4,14.65,4/27,4/27,1,0,0,Chris Morris,South Africa
+IPL,81,81,1720,2295,1,95,24.16,8.01,18.11,4/23,4/23,4,0,0,Chris Morris,South Africa
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,David Miller,South Africa
+ODI,178,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,David Miller,South Africa
+T20,130,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,David Miller,South Africa
+IPL,131,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,David Miller,South Africa
+Test,3,6,480,252,22,7,36.0,3.15,68.57,2/26,3/82,0,0,0,Dwaine Pretorius,South Africa
+ODI,27,26,1144,947,9,35,27.06,4.97,32.69,4/36,4/36,1,0,0,Dwaine Pretorius,South Africa
+T20,30,27,504,696,0,35,19.89,8.29,14.4,5/17,5/17,0,1,0,Dwaine Pretorius,South Africa
+IPL,7,7,150,238,0,6,39.67,9.52,25.0,2/30,2/30,0,0,0,Dwaine Pretorius,South Africa
+Test,69,5,78,69,0,0,0.0,5.31,0.0,0/1,0/1,0,0,0,Faf du Plessis ,South Africa
+ODI,143,11,192,189,0,2,94.5,5.91,96.0,1/8,1/8,0,0,0,Faf du Plessis ,South Africa
+T20,50,2,8,3,0,0,0.0,2.25,0.0,0/0,0/0,0,0,0,Faf du Plessis ,South Africa
+IPL,146,1,6,16,0,0,0.0,16.0,0.0,0/16,0/16,0,0,0,Faf du Plessis ,South Africa
+Test,20,37,3925,2294,86,57,40.25,3.51,68.86,5/32,8/130,1,2,0,Imran Tahir,South Africa
+ODI,107,104,5541,4297,38,173,24.84,4.65,32.03,7/45,7/45,7,3,0,Imran Tahir,South Africa
+T20,38,38,845,948,0,63,15.05,6.73,13.41,5/23,5/23,2,2,0,Imran Tahir,South Africa
+IPL,59,59,1316,1703,1,82,20.77,7.76,16.05,4/12,4/12,3,0,0,Imran Tahir,South Africa
+Test,46,57,2703,1601,48,42,38.12,3.55,64.36,4/47,4/51,2,0,0,Jean-Paul Duminy,South Africa
+ODI,199,135,3513,3143,9,69,45.55,5.37,50.91,4/16,4/16,1,0,0,Jean-Paul Duminy,South Africa
+T20,81,41,463,599,0,21,28.52,7.76,22.05,3/18,3/18,0,0,0,Jean-Paul Duminy,South Africa
+IPL,83,49,678,834,0,23,36.26,7.38,29.48,4/17,4/17,1,0,0,Jean-Paul Duminy,South Africa
+Test,70,128,12898,7196,427,327,22.01,3.35,39.44,7/112,13/144,14,16,4,Kagiso Rabada,South Africa
+ODI,106,104,5444,4613,63,168,27.46,5.08,32.4,6/16,6/16,6,2,0,Kagiso Rabada,South Africa
+T20,65,65,1393,1928,3,71,27.15,8.3,19.62,3/18,3/18,0,0,0,Kagiso Rabada,South Africa
+IPL,81,81,1842,2611,2,118,22.13,8.5,15.61,4/21,4/21,6,0,0,Kagiso Rabada,South Africa
+Test,19,33,2452,1273,99,55,23.15,3.12,44.58,6/39,8/102,1,3,0,Lungi Ngidi,South Africa
+ODI,67,66,3117,3018,29,103,29.3,5.81,30.26,6/58,6/58,4,1,0,Lungi Ngidi,South Africa
+T20,43,43,857,1320,0,63,20.95,9.24,13.6,5/39,5/39,2,1,0,Lungi Ngidi,South Africa
+IPL,14,14,324,448,2,25,17.92,8.3,12.96,4/10,4/10,1,0,0,Lungi Ngidi,South Africa
+Test,54,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Quinton de Kock,South Africa
+ODI,155,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Quinton de Kock,South Africa
+T20,92,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Quinton de Kock,South Africa
+IPL,108,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Quinton de Kock,South Africa
+Test,18,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rassie van der Dussen,South Africa
+ODI,71,1,6,3,0,1,3.0,3.0,6.0,1/3,1/3,0,0,0,Rassie van der Dussen,South Africa
+T20,50,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rassie van der Dussen,South Africa
+IPL,3,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rassie van der Dussen,South Africa
+Test,2,4,483,278,10,6,46.33,3.45,80.5,3/91,4/128,0,0,0,Tabraiz Shamsi,South Africa
+ODI,55,52,2697,2510,8,73,34.38,5.58,36.95,5/49,5/49,3,1,0,Tabraiz Shamsi,South Africa
+T20,70,70,1509,1859,1,89,20.89,7.39,16.96,5/24,5/24,3,1,0,Tabraiz Shamsi,South Africa
+IPL,5,5,120,181,0,3,60.33,9.05,40.0,1/21,1/21,0,0,0,Tabraiz Shamsi,South Africa
+Test,28,53,5077,3003,130,70,42.9,3.55,72.53,6/132,7/180,6,1,0,Nuwan Pradeep,Sri Lanka
+ODI,49,47,2345,2339,20,63,37.13,5.98,37.22,4/31,4/31,2,0,0,Nuwan Pradeep,Sri Lanka
+T20,16,16,278,436,0,15,29.07,9.41,18.53,4/25,4/25,1,0,0,Nuwan Pradeep,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Nuwan Pradeep,Sri Lanka
+Test,44,5,84,51,1,0,0.0,3.64,0.0,0/5,0/5,0,0,0,Lahiru Thirimanne,Sri Lanka
+ODI,127,4,104,94,0,3,31.33,5.42,34.67,2/36,2/36,0,0,0,Lahiru Thirimanne,Sri Lanka
+T20,26,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Lahiru Thirimanne,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Lahiru Thirimanne,Sri Lanka
+Test,100,15,312,202,5,2,101.0,3.88,156.0,1/12,1/12,0,0,0,Dimuth Karunaratne,Sri Lanka
+ODI,50,2,16,18,0,0,0.0,6.75,0.0,0/7,0/7,0,0,0,Dimuth Karunaratne,Sri Lanka
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dimuth Karunaratne,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dimuth Karunaratne,Sri Lanka
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Avishka Fernando,Sri Lanka
+ODI,51,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Avishka Fernando,Sri Lanka
+T20,37,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Avishka Fernando,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Avishka Fernando,Sri Lanka
+Test,118,86,3978,1798,161,33,54.48,2.71,120.55,4/44,4/60,1,0,0,Angelo Mathews,Sri Lanka
+ODI,226,163,5324,4110,56,126,32.62,4.63,42.25,6/20,6/20,2,1,0,Angelo Mathews,Sri Lanka
+T20,90,72,1169,1389,4,45,30.87,7.13,25.98,3/16,3/16,0,0,0,Angelo Mathews,Sri Lanka
+IPL,49,44,791,1079,0,27,39.96,8.18,29.3,4/19,4/19,1,0,0,Angelo Mathews,Sri Lanka
+Test,5,9,413,257,6,11,23.36,3.73,37.55,3/25,5/51,0,0,0,Dhananjaya de Silva,Sri Lanka
+ODI,27,21,601,547,2,9,60.78,5.46,66.78,2/27,2/27,0,0,0,Dhananjaya de Silva,Sri Lanka
+T20,22,13,138,206,0,8,25.75,8.96,17.25,2/17,2/17,0,0,0,Dhananjaya de Silva,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Dhananjaya de Silva,Sri Lanka
+Test,29,53,4054,1615,163,49,32.96,2.39,82.73,6/41,7/64,1,1,0,Milinda Siriwardana,Sri Lanka
+ODI,45,45,1548,1230,10,30,41.0,4.77,51.6,3/26,3/26,0,0,0,Milinda Siriwardana,Sri Lanka
+T20,41,21,321,461,0,12,38.42,8.62,26.75,2/22,2/22,0,0,0,Milinda Siriwardana,Sri Lanka
+IPL,25,19,216,319,0,6,53.17,8.86,36.0,3/4,3/4,0,0,0,Milinda Siriwardana,Sri Lanka
+Test,6,8,954,653,20,11,59.36,4.11,86.73,4/63,4/151,1,0,0,Thisara Perera,Sri Lanka
+ODI,166,157,5900,5740,28,175,32.8,5.84,33.71,6/44,6/44,5,4,0,Thisara Perera,Sri Lanka
+T20,84,67,1102,1717,1,51,33.67,9.35,21.61,3/24,3/24,0,0,0,Thisara Perera,Sri Lanka
+IPL,37,36,698,1016,0,31,32.77,8.73,22.52,3/20,3/20,0,0,0,Thisara Perera,Sri Lanka
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Isuru Udana,Sri Lanka
+ODI,21,21,909,950,2,18,52.78,6.27,50.5,3/82,3/82,0,0,0,Isuru Udana,Sri Lanka
+T20,35,32,631,915,1,27,33.89,8.7,23.37,3/11,3/11,0,0,0,Isuru Udana,Sri Lanka
+IPL,10,10,174,282,0,8,35.25,9.72,21.75,2/41,2/41,0,0,0,Isuru Udana,Sri Lanka
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jeevan Mendis,Sri Lanka
+ODI,58,49,1404,1204,2,28,43.0,5.15,50.14,3/15,3/15,0,0,0,Jeevan Mendis,Sri Lanka
+T20,22,14,210,249,0,12,20.75,7.11,17.5,3/24,3/24,0,0,0,Jeevan Mendis,Sri Lanka
+IPL,3,2,30,36,0,1,36.0,7.2,30.0,1/16,1/16,0,0,0,Jeevan Mendis,Sri Lanka
+Test,22,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Perera,Sri Lanka
+ODI,116,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Perera,Sri Lanka
+T20,77,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Perera,Sri Lanka
+IPL,2,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Perera,Sri Lanka
+Test,71,9,132,118,1,1,118.0,5.36,132.0,1/10,1/18,0,0,0,Kusal Mendis,Sri Lanka
+ODI,143,2,20,28,0,0,0.0,8.4,0.0,0/13,0/13,0,0,0,Kusal Mendis,Sri Lanka
+T20,78,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Mendis,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Kusal Mendis,Sri Lanka
+Test,107,203,23490,11832,888,391,30.26,3.02,60.08,7/64,10/108,19,15,1,Suranga Lakmal,Sri Lanka
+ODI,161,159,8075,7447,80,221,33.7,5.53,36.54,7/33,7/33,5,3,0,Suranga Lakmal,Sri Lanka
+T20,125,123,2753,3671,7,164,22.38,8.0,16.79,5/18,5/18,2,2,0,Suranga Lakmal,Sri Lanka
+IPL,54,54,1206,1742,2,47,37.06,8.67,25.66,3/20,3/20,0,0,0,Suranga Lakmal,Sri Lanka
+Test,30,59,5209,3349,112,101,33.16,3.86,51.57,5/50,9/210,7,3,0,Lasith Malinga,Sri Lanka
+ODI,226,220,10936,9759,103,338,28.87,5.35,32.36,6/38,6/38,11,8,0,Lasith Malinga,Sri Lanka
+T20,84,83,1799,2225,1,107,20.79,7.42,16.81,5/6,5/6,1,2,0,Lasith Malinga,Sri Lanka
+IPL,122,122,2827,3365,8,170,19.79,7.14,16.63,5/13,5/13,6,1,0,Lasith Malinga,Sri Lanka
+Test,2,2,288,250,0,5,50.0,5.21,57.6,3/182,3/182,0,0,0,Jeffrey Vandersay,Sri Lanka
+ODI,27,26,1185,1065,6,40,26.63,5.39,29.63,6/33,6/33,1,1,0,Jeffrey Vandersay,Sri Lanka
+T20,14,14,296,395,1,7,56.43,8.01,42.29,2/26,2/26,0,0,0,Jeffrey Vandersay,Sri Lanka
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Jeffrey Vandersay,Sri Lanka
+Test,51,89,12069,6381,299,190,33.58,3.17,63.52,Jul-58,12/117,9,10,2,Mehidy Hasan Miraz,Bangladesh
+ODI,105,102,5037,4061,35,110,36.92,4.84,45.79,Apr-25,Apr-25,5,0,0,Mehidy Hasan Miraz,Bangladesh
+T20,29,26,378,539,0,14,38.5,8.56,27.0,04-Dec,04-Dec,1,0,0,Mehidy Hasan Miraz,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mehidy Hasan Miraz,Bangladesh
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Saifuddin,Bangladesh
+ODI,29,28,1283,1279,7,41,31.2,5.98,31.29,Apr-41,Apr-41,1,0,0,Mohammad Saifuddin,Bangladesh
+T20,38,38,797,1158,0,42,27.57,8.72,18.98,Apr-33,Apr-33,1,0,0,Mohammad Saifuddin,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Saifuddin,Bangladesh
+Test,4,6,162,87,2,0,0.0,3.22,0.0,0/1,0/4,0,0,0,Mosaddek Hossain,Bangladesh
+ODI,43,41,1130,969,2,17,57.0,5.15,66.47,Mar-13,Mar-13,0,0,0,Mosaddek Hossain,Bangladesh
+T20,33,26,331,398,1,18,22.11,7.21,18.39,May-20,May-20,0,1,0,Mosaddek Hossain,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mosaddek Hossain,Bangladesh
+Test,71,121,15675,7803,487,246,31.72,2.99,63.72,Jul-36,10/124,11,19,2,Shakib Al Hasan,Bangladesh
+ODI,247,241,12575,9360,102,317,29.53,4.47,39.67,May-29,May-29,10,4,0,Shakib Al Hasan,Bangladesh
+T20,129,126,2745,3116,3,149,20.91,6.81,18.42,May-20,May-20,6,2,0,Shakib Al Hasan,Bangladesh
+IPL,71,70,1484,1839,1,63,29.19,7.44,23.56,Mar-17,Mar-17,0,0,0,Shakib Al Hasan,Bangladesh
+Test,50,66,3423,1958,56,43,45.53,3.43,79.6,May-51,8/110,0,1,0,Mahmudullah,Bangladesh
+ODI,239,153,4380,3810,14,82,46.46,5.22,53.41,03-Apr,03-Apr,0,0,0,Mahmudullah,Bangladesh
+T20,141,80,950,1135,2,41,27.68,7.17,23.17,03-Oct,03-Oct,0,0,0,Mahmudullah,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mahmudullah,Bangladesh
+Test,11,7,144,98,1,0,0.0,4.08,0.0,0/9,0/9,0,0,0,Sabbir Rahman,Bangladesh
+ODI,66,21,306,345,0,3,115.0,6.76,102.0,01-Dec,01-Dec,0,0,0,Sabbir Rahman,Bangladesh
+T20,48,9,73,79,0,6,13.17,6.49,12.17,03-Nov,03-Nov,0,0,0,Sabbir Rahman,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sabbir Rahman,Bangladesh
+Test,13,18,1964,1118,64,30,37.27,3.42,65.47,Apr-71,6/130,3,0,0,Abu Jayed,Bangladesh
+ODI,2,2,108,114,0,5,22.8,6.33,21.6,May-58,May-58,0,1,0,Abu Jayed,Bangladesh
+T20,3,3,66,106,0,4,26.5,9.64,16.5,Feb-27,Feb-27,0,0,0,Abu Jayed,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Abu Jayed,Bangladesh
+Test,15,25,2145,1139,76,31,36.74,3.19,69.19,Apr-37,May-66,2,0,0,Mustafizur Rahman,Bangladesh
+ODI,109,108,5279,4556,35,174,26.18,5.18,30.34,Jun-43,Jun-43,6,5,0,Mustafizur Rahman,Bangladesh
+T20,106,105,2278,2854,8,132,21.62,7.52,17.26,06-Oct,06-Oct,3,2,0,Mustafizur Rahman,Bangladesh
+IPL,57,57,1298,1762,2,61,28.89,8.14,21.28,Apr-29,Apr-29,1,0,0,Mustafizur Rahman,Bangladesh
+Test,27,44,4223,2764,73,36,76.78,3.93,117.31,5/166,5/210,0,1,0,Rubel Hossain,Bangladesh
+ODI,104,102,4678,4427,29,129,34.32,5.68,36.26,Jun-26,Jun-26,7,1,0,Rubel Hossain,Bangladesh
+T20,28,27,579,912,0,28,32.57,9.45,20.68,Mar-31,Mar-31,0,0,0,Rubel Hossain,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Rubel Hossain,Bangladesh
+Test,36,51,5990,3239,202,78,41.53,3.24,76.79,Apr-60,May-88,4,0,0,Mashrafe Mortaza,Bangladesh
+ODI,220,220,10928,8897,123,270,32.95,4.88,40.47,Jun-26,Jun-26,7,1,0,Mashrafe Mortaza,Bangladesh
+T20,54,53,1139,1528,1,42,36.38,8.05,27.12,Apr-19,Apr-19,1,0,0,Mashrafe Mortaza,Bangladesh
+IPL,1,1,24,58,0,0,0.0,14.5,0.0,0/58,0/58,0,0,0,Mashrafe Mortaza,Bangladesh
+Test,70,5,30,20,0,0,0.0,4.0,0.0,0/1,0/1,0,0,0,Tamim Iqbal,Bangladesh
+ODI,243,2,6,13,0,0,0.0,13.0,0.0,0/6,0/6,0,0,0,Tamim Iqbal,Bangladesh
+T20,78,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tamim Iqbal,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tamim Iqbal,Bangladesh
+Test,10,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Mithun,Bangladesh
+ODI,34,1,12,12,0,0,0.0,6.0,0.0,0/12,0/12,0,0,0,Mohammad Mithun,Bangladesh
+T20,17,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Mithun,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mohammad Mithun,Bangladesh
+Test,48,1,12,13,0,0,0.0,6.5,0.0,0/13,0/13,0,0,0,Litton Das,Bangladesh
+ODI,94,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Litton Das,Bangladesh
+T20,95,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Litton Das,Bangladesh
+IPL,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Litton Das,Bangladesh
+Test,94,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mushfiqur Rahim,Bangladesh
+ODI,274,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mushfiqur Rahim,Bangladesh
+T20,102,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mushfiqur Rahim,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mushfiqur Rahim,Bangladesh
+Test,16,12,508,336,3,4,84.0,3.97,127.0,Feb-68,Feb-68,0,0,0,Soumya Sarkar,Bangladesh
+ODI,76,27,558,567,1,16,35.44,6.1,34.88,Mar-18,Mar-18,0,0,0,Soumya Sarkar,Bangladesh
+T20,87,28,288,451,0,12,37.58,9.4,24.0,Feb-19,Feb-19,0,0,0,Soumya Sarkar,Bangladesh
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Soumya Sarkar,Bangladesh
+Test,5,1,12,8,0,0,0.0,4.0,0.0,0/8,0/8,0,0,0,Aaron Finch,Australia
+ODI,146,21,284,259,0,4,64.75,5.47,71.0,1/2,1/2,0,0,0,Aaron Finch,Australia
+T20,103,2,12,27,0,0,0.0,13.5,0.0,0/9,0/9,0,0,0,Aaron Finch,Australia
+IPL,92,5,43,67,0,1,67.0,9.35,43.0,1/11,1/11,0,0,0,Aaron Finch,Australia
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Adam Zampa,Australia
+ODI,111,111,5777,5343,15,187,28.57,5.55,30.89,5/35,5/35,11,1,0,Adam Zampa,Australia
+T20,95,94,2057,2458,1,117,21.01,7.17,17.58,5/19,5/19,2,1,0,Adam Zampa,Australia
+IPL,21,21,443,606,0,30,20.2,8.21,14.77,6/19,6/19,0,1,0,Adam Zampa,Australia
+Test,39,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Alex Carey,Australia
+ODI,80,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Alex Carey,Australia
+T20,38,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Alex Carey,Australia
+IPL,3,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Alex Carey,Australia
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Andrew Tye,Australia
+ODI,7,7,387,392,1,12,32.67,6.08,32.25,5/46,5/46,0,1,0,Andrew Tye,Australia
+T20,32,31,683,997,1,47,21.21,8.76,14.53,4/23,4/23,1,0,0,Andrew Tye,Australia
+IPL,30,30,684,979,0,42,23.31,8.59,16.29,5/17,5/17,3,1,0,Andrew Tye,Australia
+Test,5,10,1006,468,36,9,52.0,2.79,111.78,3/46,5/101,0,0,0,Ashton Agar,Australia
+ODI,22,22,1098,958,4,21,45.62,5.23,52.29,2/31,2/31,0,0,0,Ashton Agar,Australia
+T20,49,49,1042,1129,2,49,23.04,6.5,21.27,6/30,6/30,0,2,0,Ashton Agar,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ashton Agar,Australia
+Test,28,44,2190,1236,63,35,35.31,3.39,62.57,5/27,5/27,0,1,0,Cameron Green,Australia
+ODI,28,25,814,784,0,20,39.2,5.78,40.7,5/33,5/33,0,1,0,Cameron Green,Australia
+T20,13,12,188,279,0,12,23.25,8.9,15.67,3/35,3/35,0,0,0,Cameron Green,Australia
+IPL,29,29,439,664,0,16,41.5,9.08,27.44,2/12,2/12,0,0,0,Cameron Green,Australia
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Daniel Sams,Australia
+ODI,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Daniel Sams,Australia
+T20,10,10,180,305,0,7,43.57,10.17,25.71,2/33,2/33,0,0,0,Daniel Sams,Australia
+IPL,16,16,360,523,0,14,37.36,8.72,25.71,4/30,4/30,1,0,0,Daniel Sams,Australia
+Test,112,19,342,269,1,4,67.25,4.72,85.5,2/45,2/45,0,0,0,David Warner,Australia
+ODI,161,1,6,8,0,0,0.0,8.0,0.0,0/8,0/8,0,0,0,David Warner,Australia
+T20,110,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,David Warner,Australia
+IPL,184,1,1,2,0,0,0.0,0.0,0.0,0/2,0/2,0,0,0,David Warner,Australia
+Test,7,9,462,341,4,8,42.63,4.43,57.75,4/127,4/127,1,0,0,Glenn Maxwell,Australia
+ODI,149,119,4002,3644,14,77,47.32,5.46,51.97,4/40,4/40,4,0,0,Glenn Maxwell,Australia
+T20,116,76,985,1321,0,43,30.72,8.05,22.91,3/10,3/10,0,0,0,Glenn Maxwell,Australia
+IPL,135,80,956,1329,1,38,34.97,8.34,25.16,2/15,2/15,0,0,0,Glenn Maxwell,Australia
+Test,21,38,3963,2133,142,81,26.33,3.23,48.93,5/27,8/105,4,4,0,James Pattinson,Australia
+ODI,15,15,727,681,6,16,42.56,5.62,45.44,4/51,4/51,1,0,0,James Pattinson,Australia
+T20,4,4,78,104,0,3,34.67,8.0,26.0,2/17,2/17,0,0,0,James Pattinson,Australia
+IPL,10,10,213,320,0,11,29.09,9.01,19.36,2/19,2/19,0,0,0,James Pattinson,Australia
+Test,23,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Joe Burns,Australia
+ODI,6,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Joe Burns,Australia
+T20,5,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Joe Burns,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Joe Burns,Australia
+Test,72,135,14817,6857,634,279,24.58,2.78,53.11,6/67,9/79,11,12,0,Josh Hazlewood,Australia
+ODI,91,90,4737,3763,59,138,27.27,4.77,34.33,6/52,6/52,1,3,0,Josh Hazlewood,Australia
+T20,52,52,1186,1481,7,67,22.1,7.49,17.7,4/12,4/12,4,0,0,Josh Hazlewood,Australia
+IPL,28,28,627,832,1,37,22.49,7.96,16.95,4/25,4/25,1,0,0,Josh Hazlewood,Australia
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Marcus Stoinis,Australia
+ODI,71,64,2071,2070,5,48,43.13,6.0,43.15,3/16,3/16,0,0,0,Marcus Stoinis,Australia
+T20,74,48,750,1091,0,45,24.24,8.73,16.67,4/23,4/23,1,0,0,Marcus Stoinis,Australia
+IPL,97,63,815,1305,0,43,30.35,9.61,18.95,4/15,4/15,1,0,0,Marcus Stoinis,Australia
+Test,57,46,1268,795,20,13,61.15,3.76,97.54,3/45,5/119,0,0,0,Marnus Labuschagne,Australia
+ODI,63,14,281,325,1,8,40.63,6.94,35.13,3/39,3/39,0,0,0,Marnus Labuschagne,Australia
+T20,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Marnus Labuschagne,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Marnus Labuschagne,Australia
+Test,36,4,30,28,1,0,0.0,5.6,0.0,0/0,0/0,0,0,0,Matthew Wade,Australia
+ODI,97,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Matthew Wade,Australia
+T20,92,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Matthew Wade,Australia
+IPL,15,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Matthew Wade,Australia
+Test,2,4,281,117,11,7,16.71,2.5,40.14,3/22,5/56,0,0,0,Michael Neser,Australia
+ODI,4,4,220,239,2,3,79.67,6.52,73.33,2/46,2/46,0,0,0,Michael Neser,Australia
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Michael Neser,Australia
+IPL,1,1,24,62,0,0,0.0,15.5,0.0,0/62,0/62,0,0,0,Michael Neser,Australia
+Test,96,184,18535,10534,591,382,27.58,3.41,48.52,6/48,11/94,20,15,2,Mitchell Starc,Australia
+ODI,127,127,6512,5712,55,244,23.41,5.26,26.69,6/28,6/28,12,9,0,Mitchell Starc,Australia
+T20,65,65,1458,1881,2,79,23.81,7.74,18.46,4/20,4/20,1,0,0,Mitchell Starc,Australia
+IPL,41,40,855,1179,1,54,21.83,8.27,15.83,4/15,4/15,2,0,0,Mitchell Starc,Australia
+Test,4,7,892,458,14,10,45.8,3.08,89.2,3/55,5/89,0,0,0,Mitchell Swepson,Australia
+ODI,3,3,158,161,0,3,53.67,6.11,52.67,2/53,2/53,0,0,0,Mitchell Swepson,Australia
+T20,8,8,150,204,0,11,18.55,8.16,13.64,3/12,3/12,0,0,0,Mitchell Swepson,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Mitchell Swepson,Australia
+Test,4,4,330,164,12,2,82.0,2.98,165.0,1/48,1/48,0,0,0,Moises Henriques,Australia
+ODI,16,12,402,347,1,8,43.38,5.18,50.25,3/32,3/32,0,0,0,Moises Henriques,Australia
+T20,24,10,138,194,0,7,27.71,8.43,19.71,3/22,3/22,0,0,0,Moises Henriques,Australia
+IPL,62,60,950,1289,0,42,30.69,8.14,22.62,3/12,3/12,0,0,0,Moises Henriques,Australia
+Test,136,253,34103,16699,1078,553,30.2,2.94,61.67,8/50,13/154,26,24,5,Nathan Lyon,Australia
+ODI,29,29,1626,1334,11,29,46.0,4.92,56.07,4/44,4/44,1,0,0,Nathan Lyon,Australia
+T20,2,2,30,48,0,1,48.0,9.6,30.0,1/33,1/33,0,0,0,Nathan Lyon,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Nathan Lyon,Australia
+Test,67,125,13616,6597,496,294,22.44,2.91,46.31,6/23,10/62,17,13,2,Pat Cummins,Australia
+ODI,90,90,4683,4116,46,143,28.78,5.27,32.75,5/70,5/70,6,1,0,Pat Cummins,Australia
+T20,57,57,1254,1556,4,66,23.58,7.44,19.0,3/15,3/15,0,0,0,Pat Cummins,Australia
+IPL,59,59,1343,1983,2,63,31.48,8.86,21.32,4/34,4/34,1,0,0,Pat Cummins,Australia
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Sean Abbott,Australia
+ODI,28,28,1307,1244,9,33,37.7,5.71,39.61,3/23,3/23,0,0,0,Sean Abbott,Australia
+T20,20,20,367,545,1,26,20.96,8.91,14.12,4/31,4/31,1,0,0,Sean Abbott,Australia
+IPL,3,3,54,104,0,1,104.0,11.56,54.0,1/47,1/47,0,0,0,Sean Abbott,Australia
+Test,116,62,1470,1008,28,19,53.05,4.11,77.37,3/18,4/83,0,0,0,Steven Smith,Australia
+ODI,170,40,1076,971,1,28,34.68,5.41,38.43,3/16,3/16,0,0,0,Steven Smith,Australia
+T20,67,17,291,378,1,17,22.24,7.79,17.12,3/20,3/20,0,0,0,Steven Smith,Australia
+IPL,103,1,2,5,0,0,0.0,0.0,0.0,0/5,0/5,0,0,0,Steven Smith,Australia
+Test,35,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tim Paine,Australia
+ODI,35,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tim Paine,Australia
+T20,12,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tim Paine,Australia
+IPL,2,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Tim Paine,Australia
+Test,56,37,855,515,11,15,34.33,3.61,57.0,4/10,4/10,1,0,0,Travis Head,Australia
+ODI,73,40,1125,1067,0,24,44.46,5.69,46.88,4/28,4/28,1,0,0,Travis Head,Australia
+T20,38,4,36,56,0,1,56.0,9.33,36.0,1/16,1/16,0,0,0,Travis Head,Australia
+IPL,26,6,58,113,0,2,56.5,11.69,29.0,2/30,2/30,0,0,0,Travis Head,Australia
+Test,1,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Will Pucovski,Australia
+ODI,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Will Pucovski,Australia
+T20,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Will Pucovski,Australia
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Will Pucovski,Australia
+Test,27,49,5018,2864,118,83,34.51,3.42,60.46,May-63,7/134,3,2,0,wahab-riaz,Pakistan
+ODI,91,90,4327,4117,20,120,34.31,5.71,36.06,May-46,May-46,5,1,0,wahab-riaz,Pakistan
+T20,36,35,710,971,2,34,28.56,8.21,20.88,Mar-18,Mar-18,0,0,0,wahab-riaz,Pakistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,wahab-riaz,Pakistan
+Test,31,53,6162,3235,206,116,27.89,3.15,53.12,Jun-51,Oct-94,12,4,1,shaheen-afridi,Pakistan
+ODI,64,63,3288,3095,28,127,24.37,5.65,25.89,Jun-35,Jun-35,7,3,0,shaheen-afridi,Pakistan
+T20,79,79,1714,2257,3,102,22.13,7.9,16.8,Apr-22,Apr-22,2,0,0,shaheen-afridi,Pakistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,shaheen-afridi,Pakistan
+Test,24,46,4295,2185,164,80,27.31,3.05,53.69,May-27,10/114,2,6,1,hasan-ali,Pakistan
+ODI,66,64,3188,3084,16,100,30.84,5.8,31.88,May-34,May-34,2,4,0,hasan-ali,Pakistan
+T20,51,50,1033,1456,5,60,24.27,8.46,17.22,Apr-18,Apr-18,1,0,0,hasan-ali,Pakistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,hasan-ali,Pakistan
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,mohammad-hasnain,Pakistan
+ODI,15,15,718,755,6,17,44.41,6.31,42.24,May-26,May-26,0,1,0,mohammad-hasnain,Pakistan
+T20,28,27,618,877,0,25,35.08,8.51,24.72,Mar-37,Mar-37,0,0,0,mohammad-hasnain,Pakistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,mohammad-hasnain,Pakistan
+Test,36,67,7619,3627,291,119,30.48,2.86,64.03,Jun-44,Jul-64,6,4,0,mohammad-amir,Pakistan
+ODI,61,60,3013,2400,34,81,29.63,4.78,37.2,May-30,May-30,1,1,0,mohammad-amir,Pakistan
+T20,62,61,1321,1558,6,71,21.94,7.08,18.61,Apr-13,Apr-13,1,0,0,mohammad-amir,Pakistan
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,mohammad-amir,Pakistan
+Test,2,2,276,196,4,2,98.0,4.26,138.0,1/72,1/72,0,0,0,Sheldon Cottrell,West Indies
+ODI,38,36,1722,1685,11,52,32.4,5.87,33.12,5/46,5/46,2,1,0,Sheldon Cottrell,West Indies
+T20,45,44,918,1244,4,52,23.92,8.13,17.65,4/28,4/28,1,0,0,Sheldon Cottrell,West Indies
+IPL,6,6,120,176,1,6,29.33,8.8,20.0,2/17,2/17,0,0,0,Sheldon Cottrell,West Indies
+Test,59,104,9379,5348,267,166,32.22,3.42,56.5,8/62,13/121,5,6,1,Shannon Gabriel,West Indies
+ODI,25,25,1148,1134,6,33,34.36,5.93,34.79,3/17,3/17,0,0,0,Shannon Gabriel,West Indies
+T20,2,2,42,56,0,3,18.67,8.0,14.0,3/44,3/44,0,0,0,Shannon Gabriel,West Indies
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Shannon Gabriel,West Indies
+Test,85,154,14944,7729,539,284,27.21,3.1,52.62,6/48,10/146,14,11,1,Kemar Roach,West Indies
+ODI,95,93,4579,3887,53,125,31.1,5.09,36.63,6/27,6/27,3,3,0,Kemar Roach,West Indies
+T20,11,11,234,284,1,10,28.4,7.28,23.4,2/25,2/25,0,0,0,Kemar Roach,West Indies
+IPL,2,2,48,80,0,0,0.0,10.0,0.0,0/32,0/32,0,0,0,Kemar Roach,West Indies
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ashley Nurse,West Indies
+ODI,54,49,2384,2125,6,49,43.37,5.35,48.65,4/51,4/51,2,0,0,Ashley Nurse,West Indies
+T20,13,13,240,317,0,8,39.63,7.93,30.0,2/6,2/6,0,0,0,Ashley Nurse,West Indies
+IPL,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Ashley Nurse,West Indies
+Test,0,0,0,0,0,0,0.0,0.0,0.0,-/-,-/-,0,0,0,Oshane Thomas,West Indies
+ODI,25,24,920,1034,1,31,33.35,6.74,29.68,5/21,5/21,1,1,0,Oshane Thomas,West Indies
+T20,21,20,408,638,1,21,30.38,9.38,19.43,5/28,5/28,0,1,0,Oshane Thomas,West Indies
+IPL,4,4,60,79,0,5,15.8,7.9,12.0,2/6,2/6,0,0,0,Oshane Thomas,West Indies

app.py

@@ -0,0 +1,611 @@
+import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+
+st.set_page_config(page_icon='🏏', layout='wide', page_title='Cricket Analysis')
+
+st.title("🏏 Cricket Stats Dashboard")
+
+# Load dataset
+df_batting = pd.read_csv("Batting_10_Teams_Final.csv", on_bad_lines='skip')
+df_bowling = pd.read_csv("new_Bowling_10_Teams_Final.csv", on_bad_lines='skip')
+
+col1, col2 = st.columns(2)
+
+# Select country
+with col1:
+    country = sorted(df_batting["Country"].unique().tolist())
+    selected_country = st.selectbox("Select a Country", country)
+
+# Filter players based on selected country
+filtered_players = df_batting[df_batting["Country"] == selected_country]["player_name"].unique()
+
+# Select player
+with col2:
+    players = ["All"] + sorted(filtered_players.tolist())
+    selected_player = st.selectbox("Select a Player", players)
+
+selected_format = 'All'
+
+# 📌 Display selected filters
+st.write(f"📌 You selected: **{selected_country}** → **{selected_player}**")
+
+# ✅ Filtering Data
+filtered_batting_df = df_batting[df_batting["Country"] == selected_country]
+filtered_bowling_df = df_bowling[df_bowling["Country"] == selected_country]
+
+# Apply player filter only if a specific player is selected
+if selected_player != "All":
+    filtered_batting_df = filtered_batting_df[filtered_batting_df["player_name"] == selected_player]
+    filtered_bowling_df = filtered_bowling_df[filtered_bowling_df["player_name"] == selected_player]
+
+grouped_batting_df = filtered_batting_df.groupby("Format").sum().reset_index()
+grouped_bowling_df = filtered_bowling_df.groupby("Format").sum().reset_index()
+
+
+if not grouped_batting_df.empty and not grouped_bowling_df.empty:
+    st.write("### 📊 Batting & Bowling Stats")
+    
+    # Create Tabs for Each Format
+    tab_list = st.tabs(["Overall"] + grouped_batting_df["Format"].tolist())  # Add "Overall" tab
+
+    # 🏏 Overall Stats
+    overall_batting = filtered_batting_df.sum(numeric_only=True)
+    overall_bowling = filtered_bowling_df.sum(numeric_only=True)
+
+    with tab_list[0]:  # Overall tab
+        st.subheader("Overall Stats")
+
+        col1, col9, col2 = st.columns([1,0.05,1])
+
+        # Batting Stats
+        with col1:
+            st.subheader("🏏 Batting Stats")
+            c1, c2, c3 = st.columns(3)
+            with c1:
+                st.metric("Total Matches", int(overall_batting["Matches"]))
+                st.metric("Total Innings", int(overall_batting["Innings"]))
+                st.metric("Strike rate", overall_batting["SR"])
+            with c2:
+                st.metric("Total Runs", int(overall_batting["Runs"]))
+                st.metric("Average Runs", overall_batting["Average"])
+                st.metric("Total Fours", int(overall_batting["Fours"]))
+                st.metric("Total Sixes", int(overall_batting["Sixes"]))
+            with c3:
+                st.metric("Total 100s", int(overall_batting["100s"]))
+                st.metric("Total 50s", int(overall_batting["50s"]))
+
+            if not overall_batting.empty:
+                # Conditional Strike Rate Trend Plot
+                if selected_player == "All":
+                    # Average Strike Rate Across Formats (for all players)
+                    format_sr = filtered_batting_df.groupby("Format")["SR"].mean().reset_index()
+                    fig1 = px.line(
+                        format_sr, x="Format", y="SR",
+                        title="Average Strike Rate Across Formats",
+                        markers=True,
+                        template="plotly_dark",
+                        line_shape="spline",
+                        color_discrete_sequence=["#00CFFF"]
+                    )
+                    fig1.update_traces(marker=dict(size=10, symbol="circle"))
+                    fig1.update_layout(
+                        title_font=dict(size=18, family="Arial"),
+                        xaxis_title="Match Format",
+                        yaxis_title="Strike Rate",
+                        hovermode="x unified"
+                    )
+                    st.plotly_chart(fig1, key="plot_strike_rate_trend")
+
+                else:
+                    # Strike Rate Trend for Selected Player
+                    player_sr = filtered_batting_df[filtered_batting_df["player_name"] == selected_player]
+                    
+                    # Ensure player has strike rate data
+                    if not player_sr.empty:
+                        fig1_player = px.line(
+                            player_sr, x="Format", y="SR",
+                            title=f"{selected_player}: Strike Rate Across Formats",
+                            markers=True,
+                            template="plotly_dark",
+                            line_shape="spline",
+                            color_discrete_sequence=["#00CFFF"]
+                        )
+                        fig1_player.update_traces(marker=dict(size=10, symbol="circle"))
+                        fig1_player.update_layout(
+                            title_font=dict(size=18, family="Arial"),
+                            xaxis_title="Match Format",
+                            yaxis_title="Strike Rate",
+                            hovermode="x unified"
+                        )
+                        st.plotly_chart(fig1_player, key="plot_player_sr")
+                
+                # Conditional Plots Based on Player Selection
+                if selected_player == "All":
+                    # Top 10 Players by Runs
+                    top_10_batsmen = filtered_batting_df.drop_duplicates(subset=["player_name"]).nlargest(10, "Runs")
+                    top_players_runs = filtered_batting_df[filtered_batting_df["player_name"].isin(top_10_batsmen["player_name"])]
+                    fig2 = px.bar(
+                        top_players_runs, x="player_name", y="Runs", color="Format",
+                        title="Runs Across Formats for Top Players",
+                        barmode="stack",
+                        template="plotly_dark",
+                        text_auto=True,
+                        color_discrete_sequence=px.colors.qualitative.Safe
+                    )
+                    fig2.update_layout(
+                        title_font=dict(size=18, family="Arial"),
+                        xaxis_title="Player Name",
+                        yaxis_title="Total Runs",
+                        hovermode="x unified"
+                    )
+                    st.plotly_chart(fig2, key="plot_stacked_runs")
+
+                # Stacked Bar Chart: Sixes & Fours Across Formats for Top Batters
+                if selected_player == "All":
+                    # Get Top 10 Batters Based on Sixes
+                    ttop_10_batsmen = filtered_batting_df.drop_duplicates(subset=["player_name"]).nlargest(10, "Sixes")
+                    top_batsmen_stats = filtered_batting_df[filtered_batting_df["player_name"].isin(top_10_batsmen["player_name"])]
+
+                    # Aggregate Total Sixes & Fours per Player
+                    top_batsmen_melted = top_batsmen_stats.groupby(["player_name"])[["Sixes", "Fours"]].sum().reset_index()
+
+                    #print(top_batsmen_stats[['Format','player_name', 'Sixes','Fours']])
+                    # Reshape Data for a Single Stacked Bar Chart
+                    top_batsmen_melted = top_batsmen_melted.melt(
+                        id_vars=["player_name"], 
+                        value_vars=["Sixes", "Fours"],
+                        var_name="Boundary Type", 
+                        value_name="Count"
+                    )
+
+                    # Create Stacked Bar Chart with Facet for Each Format
+                    fig3 = px.bar(
+                        top_batsmen_melted, 
+                        x="player_name", 
+                        y="Count",
+                        color="Boundary Type", 
+                        barmode="stack",
+                        title="Sixes & Fours Across All Formats for Top Batters",
+                        hover_data=["Boundary Type", "Count"],
+                        color_discrete_sequence=px.colors.qualitative.Pastel
+                    )
+
+                    fig3.update_layout(
+                        xaxis_title="Player Name",
+                        yaxis_title="Total Boundaries",
+                        hovermode="x unified",
+                        legend=dict(title="Boundary Type")
+                    )
+
+                    st.plotly_chart(fig3, key="plot_top_boundaries")
+
+                else:
+                    # Get stats for the selected player across formats
+                    player_stats = filtered_batting_df[filtered_batting_df["player_name"] == selected_player]
+                    #print(player_stats[['Format','Sixes', 'Fours']])
+
+                    # Ensure we reshape correctly to show both Sixes & Fours
+                    player_stats_melted = player_stats.melt(
+                        id_vars=["Format"], 
+                        value_vars=["Sixes", "Fours"],
+                        var_name="Boundary Type", 
+                        value_name="Count"
+                    )
+                    #print(player_stats_melted)
+
+                    # Create Stacked Bar Chart for Selected Player
+                    fig4 = px.bar(
+                        player_stats_melted, 
+                        x="Format", y="Count", 
+                        color="Boundary Type",
+                        barmode="stack",
+                        title=f"Sixes & Fours Across Formats for {selected_player}",
+                        text_auto=True,
+                        hover_data=["Boundary Type", "Count"],
+                        color_discrete_sequence=px.colors.qualitative.Pastel
+                    )
+
+                    fig4.update_layout(
+                        xaxis_title="Match Format",
+                        yaxis_title="Total Boundaries",
+                        hovermode="x unified",
+                        legend=dict(title="Boundary Type")
+                    )
+
+                    st.plotly_chart(fig4, key="plot_selected_player_boundaries")
+
+                # Pie Chart: Runs Contribution Across Formats
+                format_runs = filtered_batting_df.groupby("Format")["Runs"].sum().reset_index()
+                fig5 = px.pie(
+                    format_runs, names="Format", values="Runs",
+                    title="Runs Contribution Across Formats",
+                    template="plotly_dark",
+                    color_discrete_sequence=px.colors.qualitative.Pastel
+                )
+                fig5.update_traces(
+                    title_font=dict(size=18, family="Arial"),
+                    textinfo="label+value",
+                    pull=[0.01, 0.01, 0.01, 0.01]
+                )
+                st.plotly_chart(fig5, key="plot_runs_contribution")
+
+
+        st.markdown("---")  # Divider
+
+        # **Vertical Line (Divider)**
+        with col9:
+            st.markdown(
+                """
+                <style>
+                .divider {
+                    height: auto;
+                    width: 3px;
+                    background-color: #555;
+                    margin: auto;
+                }
+                </style>
+                <div class="divider"></div>
+                """,
+                unsafe_allow_html=True
+            )
+
+        # OverAll Bowling Stats
+        with col2:
+            st.subheader("🎯 Bowling Stats")
+            c1, c2, c3, c4 = st.columns(4)
+            with c1:
+                st.metric("Total Matches", int(overall_bowling["Matches"]))
+                st.metric("Total Innings", int(overall_bowling["Innings"]))
+                st.metric("Strike Rate", overall_bowling["SR"])
+            with c2:
+                st.metric("Total Wickets", int(overall_bowling["Wickets"]))
+                st.metric("Average Wickets", overall_bowling["Avg"])
+                st.metric("Total 4W", int(overall_bowling["4w"]))  
+                st.metric("Total 5W", int(overall_bowling["5w"]))
+            with c3:
+                st.metric("Best BBI Runs", int(overall_bowling["BBI_Runs"]))
+                st.metric("Best BBI Wickets", int(overall_bowling["BBI_Wickets"]))
+                st.metric("Best BBM Runs", int(overall_bowling["BBM_Runs"]))
+                st.metric("Best BBM Wickets", int(overall_bowling["BBM_Wickets"]))
+            with c4:
+                st.metric("Maidens", int(overall_bowling["Maidens"]))
+                st.metric("Eco", overall_bowling["Eco"])
+
+            if not overall_bowling.empty:
+                # Line Chart: Economy Rate Trend Across Formats
+                format_stats = filtered_bowling_df.groupby("Format").agg({"Eco": "mean", "Matches": "sum"}).reset_index()
+                
+                fig1 = make_subplots(specs=[[{"secondary_y": True}]])  # Dual axis plot
+
+                # Economy Rate Line
+                fig1.add_trace(
+                    go.Scatter(x=format_stats["Format"], y=format_stats["Eco"], 
+                            mode="lines+markers", name="Economy Rate", line_shape="spline",
+                            marker=dict(size=10, symbol="circle", color="#FF6F61")),
+                    secondary_y=False
+                )
+
+                # Number of Matches Bar
+                fig1.add_trace(
+                    go.Bar(x=format_stats["Format"], y=format_stats["Matches"], 
+                        name="No. of Matches", marker_color="lightblue", opacity=0.6), 
+                    secondary_y=True
+                )
+
+                fig1.update_layout(
+                    title="Economy Rate & Matches Across Formats",
+                    xaxis_title="Match Format",
+                    yaxis=dict(title="Average Economy Rate"),
+                    yaxis2=dict(title="Total Matches", overlaying="y", side="right"),
+                    hovermode="x unified",
+                )
+                
+                st.plotly_chart(fig1, key="plot_eco_trend")
+
+                # Stacked Bar Chart: Wickets & Matches Across Formats for Top Bowlers
+                if selected_player == "All":
+                    top_10_bowlers = filtered_bowling_df.drop_duplicates(subset=["player_name"]).nlargest(10, "Wickets")
+                    top_bowler_stats = filtered_bowling_df[filtered_bowling_df["player_name"].isin(top_10_bowlers["player_name"])]
+
+                    fig2 = px.bar(
+                        top_bowler_stats, x="player_name", y="Wickets", 
+                        color="Format", barmode="stack",
+                        title="Wickets Across Formats for Top Bowlers",
+                        text_auto=True,
+                        hover_data=["Wickets", "Format"],
+                        color_discrete_sequence=px.colors.qualitative.Safe
+                    )
+
+                    fig2.update_layout(
+                        xaxis_title="Player Name",
+                        yaxis_title="Total Wickets",
+                        hovermode="x unified",
+                        legend=dict(title="Match Format")
+                    )
+
+                    st.plotly_chart(fig2, key="plot_top_bowlers")
+
+                # Stacked Bar Chart: Wickets & Matches Across Formats for Top Bowlers
+                if selected_player == "All":
+                    top_10_bowlers = filtered_bowling_df.drop_duplicates(subset=["player_name"]).nlargest(10, "Wickets")
+                    top_bowler_stats = filtered_bowling_df[filtered_bowling_df["player_name"].isin(top_10_bowlers["player_name"])]
+
+                    # Aggregate Total Wickets & Maidens per Player
+                    top_bowlers_melted = top_bowler_stats.groupby(["player_name"])[["Wickets", "Maidens"]].sum().reset_index()
+
+                    # Reshape Data for Stacked Bar Chart
+                    top_bowlers_melted = top_bowlers_melted.melt(
+                        id_vars=["player_name"], 
+                        value_vars=["Wickets", "Maidens"],
+                        var_name="Bowling Stat", 
+                        value_name="Count"
+                    )
+
+
+                    # Create Stacked Bar Chart with Facet for Each Format
+                    fig_bowling = px.bar(
+                        top_bowlers_melted, 
+                        x="player_name", y="Count",
+                        color="Bowling Stat", 
+                        barmode="stack",
+                        title="Wickets & Maidens Across Formats for Top Bowlers",
+                        hover_data=["Bowling Stat", "Count"],
+                        color_discrete_sequence=px.colors.qualitative.Pastel
+                    )
+
+                    fig_bowling.update_layout(
+                        xaxis_title="Player Name",
+                        yaxis_title="Total Count",
+                        hovermode="x unified",
+                        legend=dict(title="Bowling Stat")
+                    )
+
+                    st.plotly_chart(fig_bowling, key="plot_top_bowling_stats")
+
+                else:
+                    # Get stats for the selected player across formats
+                    player_bowling_stats = filtered_bowling_df[filtered_bowling_df["player_name"] == selected_player]
+                    # Ensure we reshape correctly to show both Wickets & Maidens
+                    player_bowling_melted = player_bowling_stats.melt(
+                        id_vars=["Format"], 
+                        value_vars=["Wickets", "Maidens"],
+                        var_name="Bowling Stat", 
+                        value_name="Count"
+                    )
+
+                    # Create Stacked Bar Chart for Selected Player
+                    fig_player_bowling = px.bar(
+                        player_bowling_melted, 
+                        x="Format", y="Count", 
+                        color="Bowling Stat",
+                        barmode="stack",
+                        title=f"Wickets & Maidens Across Formats for {selected_player}",
+                        text_auto=True,
+                        hover_data=["Bowling Stat", "Count"],
+                        color_discrete_sequence=px.colors.qualitative.Pastel
+                    )
+
+                    fig_player_bowling.update_layout(
+                        xaxis_title="Match Format",
+                        yaxis_title="Total Count",
+                        hovermode="x unified",
+                        legend=dict(title="Bowling Stat")
+                    )
+
+                    st.plotly_chart(fig_player_bowling, key="plot_selected_player_bowling_stats")
+
+
+                # Pie Chart: Wickets & Matches Contribution Across Formats (Sunburst)
+                format_totals = filtered_bowling_df.groupby("Format").agg({"Wickets": "sum", "Matches":"sum"}).reset_index()
+
+                fig3 = px.sunburst(
+                    format_totals, path=["Format"], values="Wickets",
+                    color = "Matches",
+                    title="Wickets & Matches Contribution Across Formats",
+                    color_continuous_scale=px.colors.qualitative.Pastel
+                )
+                # Customize hover info to display both Wickets & Matches
+                fig3.update_traces(
+                    hovertemplate="<b>%{label}</b><br>Wickets: %{value}<br>Matches: %{customdata}<extra></extra>",
+                    customdata=format_totals["Matches"],
+                    textinfo = "label+value",
+                )
+                fig3.update_layout(
+                    title_font=dict(size=18, family="Arial"),
+                    hovermode="x unified",
+                    legend=dict(title="Match Format"),
+                    coloraxis_showscale=False
+                )
+
+                st.plotly_chart(fig3, key="plot_wickets_contribution")
+
+
+# 📌 **Format-wise Stats**
+for i, format_name in enumerate(grouped_batting_df["Format"].unique()):  
+    with tab_list[i + 1]:  # Each format tab
+        st.subheader(f"{format_name} Stats")
+
+        col1, col3, col2 = st.columns([1, 0.05, 1])
+
+        # 🏏 **Batting Stats**
+        format_batting = grouped_batting_df[grouped_batting_df["Format"] == format_name]
+        if not format_batting.empty:
+            format_batting_row = format_batting.iloc[0]  
+            with col1:
+                st.subheader("🏏 Batting Stats")
+                c1, c2, c3 = st.columns(3)
+                with c1:
+                    st.metric("Total Matches", int(format_batting_row["Matches"]))    
+                    st.metric("Total Innings", int(format_batting_row["Innings"]))
+                    st.metric("Strike Rate", float(format_batting_row["SR"]))
+                with c2:
+                    st.metric("Total Runs", int(format_batting_row["Runs"]))
+                    st.metric("Average Runs", float(format_batting_row["Average"]))
+                    st.metric("Total Fours", int(format_batting_row["Fours"]))  
+                    st.metric("Total Sixes", int(format_batting_row["Sixes"])) 
+                with c3:
+                    st.metric("Total 100s", int(format_batting_row["100s"]))  
+                    st.metric("Total 50s", int(format_batting_row["50s"]))
+
+                format_filtered_df = filtered_batting_df[filtered_batting_df["Format"] == format_name]
+                
+                if not format_filtered_df.empty:
+                    # Show only top 10 run-scorers
+                    if selected_player != "All":
+                        top_batters = format_filtered_df[format_filtered_df["player_name"] == selected_player]
+                    else:
+                        top_batters = format_filtered_df.nlargest(10, "Runs")
+
+                    # Line Chart: Strike Rate of Top 10 Players     
+                    fig2 = px.line(
+                        top_batters,
+                        x="player_name", y="SR",
+                        markers=True,
+                        line_shape="spline",
+                        title=f"{format_name}: Strike Rate of Top 10 Players",
+                    )
+                    st.plotly_chart(fig2, key=f"plot_{format_name}_batting_sr")
+                
+                    if selected_player == "All":
+                        top_10_batsmen_format = format_filtered_df.drop_duplicates(subset=["player_name"]).nlargest(10, "Sixes")
+                        top_batsmen_stats_format = format_filtered_df[format_filtered_df["player_name"].isin(top_10_batsmen_format["player_name"])]
+
+                        # Aggregate Total Sixes & Fours per Player
+                        top_batsmen_melted_format = top_batsmen_stats_format.groupby(["player_name"])[["Sixes", "Fours"]].sum().reset_index()
+
+                        # Reshape Data
+                        top_batsmen_melted_format = top_batsmen_melted_format.melt(
+                            id_vars=["player_name"], 
+                            value_vars=["Sixes", "Fours"],
+                            var_name="Boundary Type", 
+                            value_name="Count"
+                        )
+
+                        # Create Stacked Bar Chart for this format
+                        fig_format = px.bar(
+                            top_batsmen_melted_format, 
+                            x="player_name", 
+                            y="Count",
+                            color="Boundary Type", 
+                            barmode="stack",
+                            title=f"Sixes & Fours in {format_name} Matches (Top 10 Players)",
+                            hover_data=["Boundary Type", "Count"],
+                            color_discrete_sequence=px.colors.qualitative.Pastel
+                        )
+
+                        fig_format.update_layout(
+                            xaxis_title="Player Name",
+                            yaxis_title="Total Boundaries",
+                            hovermode="x unified",
+                            legend=dict(title="Boundary Type")
+                        )
+
+                        st.plotly_chart(fig_format, key=f"plot_top_boundaries_{format_name}")
+
+                    else:
+                        # Get stats for the selected player in this format
+                        player_stats_format = format_filtered_df[format_filtered_df["player_name"] == selected_player]
+
+                        # Reshape Data
+                        player_stats_melted_format = player_stats_format.melt(
+                            id_vars=["Format"], 
+                            value_vars=["Sixes", "Fours"],
+                            var_name="Boundary Type", 
+                            value_name="Count"
+                        )
+
+                        # Create Stacked Bar Chart for Selected Player in this format
+                        fig_selected_format = px.bar(
+                            player_stats_melted_format, 
+                            x="Format", y="Count", 
+                            color="Boundary Type",
+                            barmode="group",
+                            title=f"Sixes & Fours in {format_name} Matches for {selected_player}",
+                            text_auto=True,
+                            hover_data=["Boundary Type", "Count"],
+                            color_discrete_sequence=px.colors.qualitative.Pastel
+                        )
+
+                        fig_selected_format.update_layout(
+                            xaxis_title="Match Format",
+                            yaxis_title="Total Boundaries",
+                            hovermode="x unified",
+                            legend=dict(title="Boundary Type")
+                        )
+
+                        st.plotly_chart(fig_selected_format, key=f"plot_selected_player_boundaries_{format_name}")
+
+        # **Vertical Line (Divider)**
+        with col3:
+            st.markdown(
+                """
+                <style>
+                .divider {
+                    height: auto;
+                    width: 3px;
+                    background-color: #555;
+                    margin: auto;
+                }
+                </style>
+                <div class="divider"></div>
+                """,
+                unsafe_allow_html=True
+            )
+
+        # 🎯 **Bowling Stats**
+        format_bowling = grouped_bowling_df[grouped_bowling_df["Format"] == format_name]
+        if not format_bowling.empty:
+            format_bowling_row = format_bowling.iloc[0]
+            with col2:
+                st.subheader("🎯 Bowling Stats")
+                c1, c2, c3, c4 = st.columns(4)
+                with c1:
+                    st.metric("Total Matches", int(format_bowling_row["Matches"]))
+                    st.metric("Total Innings", int(format_bowling_row["Innings"]))
+                    st.metric("Strike Rate", float(format_bowling_row["SR"]))   
+                with c2:
+                    st.metric("Total Wickets", int(format_bowling_row["Wickets"]))
+                    st.metric("Average Wickets", float(format_bowling_row['Avg']))
+                    st.metric("Total 4W", int(format_bowling_row["4w"]))  
+                    st.metric("Total 5W", int(format_bowling_row["5w"]))  
+                with c3:
+                    st.metric("Best BBI Runs", format_bowling_row["BBI_Runs"])  
+                    st.metric("Best BBI Wickets", format_bowling_row["BBI_Wickets"])  
+                    st.metric("Best BBM Runs", format_bowling_row["BBM_Runs"])  
+                    st.metric("Best BBM Wickets", format_bowling_row["BBM_Wickets"])
+                with c4:
+                    st.metric("Maidens", int(format_bowling_row['Maidens']))
+                    st.metric("Economy Rate", float(format_bowling_row['Eco']))
+
+                format_filtered_df2 = filtered_bowling_df[filtered_bowling_df["Format"] == format_name]
+
+                if not format_filtered_df2.empty:
+                    if selected_player != "All":
+                        top_bowlers = format_filtered_df2[format_filtered_df2["player_name"] == selected_player]
+                    else:
+                        top_bowlers = format_filtered_df2.nlargest(10, "Wickets")
+
+                    # Bar Chart: Top 10 Wicket-Takers
+                    fig_bowling_1 = px.bar(
+                        top_bowlers,
+                        x="player_name", y="Wickets",
+                        color="Wickets",
+                        title=f"{format_name}: {'Player' if selected_player != 'All' else 'Top 10'} Wicket-Takers",
+                        text_auto=True
+                    )
+                    st.plotly_chart(fig_bowling_1, key=f"plot_{format_name}_bowling_wickets")
+
+                    # 📊 Line Plot: Economy Rate of Top 10 Bowlers
+                    fig_bowling_2 = px.line(
+                        top_bowlers,
+                        x="player_name", y="Eco",
+                        markers = True,
+                        line_shape='spline',
+                        title=f"💰 {format_name}: {'Player' if selected_player != 'All' else 'Top 10'} Economy Rate",
+                    )
+                    st.plotly_chart(fig_bowling_2, key=f"plot_{format_name}_bowling_economy")