changed readme

README.md

@@ -32,7 +32,7 @@ All of this is to say that taking Jokic off the Nuggets should have more of an e
 
 Let's keep the game in Denver, put the Nuggets back at full strength, and replace Tatum with Pritchard. As you can see, the Nuggets are now projected to win 66% of the time. That sounds about right to me!
 
-![Celtics without Tatum vs full strength Denver. Celtics at home.](denver-at-home-no-tatum.png)
+![Celtics without Tatum vs full strength Denver. Celtics at home.](denver-at-home-no-jokic.png)
 
 ## Installation
 
@@ -46,7 +46,7 @@ The `example.ipynb` notebook shows how to use the model to predict the final gam
 
 To change the players and their ages, you must reference the `player_tokens.csv` and `age_tokens.csv` files.
 
-For example, if you wanted to subtract Kristaps Porzingis from Boston's team and swap who was home / away, you would take the token representing Porzingis `4416` out of the `home_team_tokens` list, and replace him with, say, Payton Pritchard `4999`. You would then have to look up Pritchard's age (26), find the corresponding age token in `age_tokens.csv`, which is `11`, and replace Porzingis' age token (which is the second to last token).
+For example, if you wanted to subtract Kristaps Porzingis from Boston's team, you would take the token representing Porzingis `4416` out of the `home_team_tokens` list, and replace him with, say, Payton Pritchard `4999`. You would then have to look up Pritchard's age (26), find the corresponding age token in `age_tokens.csv`, which is `11`, and replace Porzingis' age token (which is the second to last token).
 
 To swap home and away, you could replace the variables containing all of the player and age tokens, or just set the `swap_home_away` variable to `True`.