Enhance MMA ROO functions with combined knockout and submission odds probability calculation

app.py

@@ -52,7 +52,7 @@ with tab1:
     elif sport_var == "MLB":
         st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'")
     elif sport_var == "MMA":
-        st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Salary', 'Median', 'KO Potential', 'Own'")
+        st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Salary', 'Median', 'KO Odds', 'Submission Odds', 'Own'")
     # Create two columns for the uploader and template button
     upload_col, template_col = st.columns([3, 1])
     
@@ -67,7 +67,7 @@ with tab1:
         elif sport_var == "MLB":
             template_df = pd.DataFrame(columns=['Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'])
         elif sport_var == "MMA":
-            template_df = pd.DataFrame(columns=['Player', 'Salary', 'Median', 'KO_var', 'Own'])
+            template_df = pd.DataFrame(columns=['Player', 'Salary', 'Median', 'KO_var', 'Sub_var', 'Own'])
         # Add download button for template
         st.download_button(
             label="Template",

function_hold/MMA_functions.py

@@ -7,11 +7,20 @@ from pandas import concat as pd_concat
 from pandas import merge as pd_merge
 from pandas import DataFrame
 
+def moneyline_to_probability(moneyline):
+    if moneyline > 0:
+        return 100 / (moneyline + 100)
+    else:
+        return abs(moneyline) / (abs(moneyline) + 100)
+
 def DK_MMA_ROO_Build(projections_file, std_var, distribution_type):
     total_sims = 1000
     
     projects_raw = projections_file.copy()
     projects_raw = projects_raw.replace("", np_nan)
+    projects_raw['range_initial'] = (projects_raw['KO_var'] + projects_raw['Sub_var']) / 2
+    projects_raw['range_var'] = projects_raw['range_initial'].apply(moneyline_to_probability)
+
     dk_df = projects_raw.sort_values(by='Median', ascending=False)
     
     basic_own_df = dk_df.copy()
@@ -104,9 +113,9 @@ def DK_MMA_ROO_Build(projections_file, std_var, distribution_type):
     
     flex_file = basic_own_df[['Player', 'Salary', 'Median', 'KO_var']]
     flex_file = flex_file.rename(columns={"Agg": "Median"})
-    flex_file['Median'] = flex_file['Median'] - (flex_file['Median'] * (flex_file['KO_var']-.5))
-    flex_file['Floor'] = flex_file['Median'] * (1-flex_file['KO_var'])
-    flex_file['Ceiling'] = flex_file['Median'] * (1+flex_file['KO_var'])
+    flex_file['Median'] = flex_file['Median'] - (flex_file['Median'] * (flex_file['range_var']-.5))
+    flex_file['Floor'] = flex_file['Median'] * (1-flex_file['range_var'])
+    flex_file['Ceiling'] = flex_file['Median'] * (1+flex_file['range_var'])
     flex_file['STD'] = (flex_file['Median'] / std_var)
     flex_file = flex_file[['Player', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD']]
     flex_file = flex_file.reset_index(drop=True)
@@ -231,6 +240,8 @@ def FD_MMA_ROO_Build(projections_file, std_var, distribution_type):
     total_sims = 1000
         
     projects_raw = projections_file.copy()
+    projects_raw['range_initial'] = (projects_raw['KO_var'] + projects_raw['Sub_var']) / 2
+    projects_raw['range_var'] = projects_raw['range_initial'].apply(moneyline_to_probability)
     fd_df = projects_raw.sort_values(by='Median', ascending=False)
     
     basic_own_df = fd_df.copy()
@@ -323,9 +334,9 @@ def FD_MMA_ROO_Build(projections_file, std_var, distribution_type):
         
     flex_file = basic_own_df[['Player', 'Salary', 'Median', 'KO_var']]
     flex_file = flex_file.rename(columns={"Agg": "Median"})
-    flex_file['Median'] = flex_file['Median'] - (flex_file['Median'] * (flex_file['KO_var']-.5))
-    flex_file['Floor'] = flex_file['Median'] * (1-flex_file['KO_var'])
-    flex_file['Ceiling'] = flex_file['Median'] * (1+flex_file['KO_var'])
+    flex_file['Median'] = flex_file['Median'] - (flex_file['Median'] * (flex_file['range_var']-.5))
+    flex_file['Floor'] = flex_file['Median'] * (1-flex_file['range_var'])
+    flex_file['Ceiling'] = flex_file['Median'] * (1+flex_file['range_var'])
     flex_file['STD'] = (flex_file['Median'] / std_var)
     flex_file = flex_file[['Player', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD']]
     flex_file = flex_file.reset_index(drop=True)