Finding stats vs "Good" teams compared to "Bad" teams
Moderator: Doctor MJ
Finding stats vs "Good" teams compared to "Bad" teams
- Old Man Game
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Finding stats vs "Good" teams compared to "Bad" teams
I apologize if this is a noob question, but does anyone know of an easy way to find a player's stats against teams of a given winning percentage?
Re: Finding stats vs "Good" teams compared to "Bad" teams
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- Ballboy
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Re: Finding stats vs "Good" teams compared to "Bad" teams
What might help your analysis is define a few questions that you would like to answer and also define what constitutes a "good" versus "bad" team.
If you're looking at a specific player then it is pretty straight forward: You can pull the player's stats from a variety of websites and then define a binary (0 or 1) or categorical variable (Good, OK, Bad) for all teams based on their win percentage. I see a lot on this board using Excel, so if that is the program you are currently using, you can simply define another column and use an 'IF statement' that takes into account a team's winning percentage or whatever metric you've used to define "Good" versus "Bad". With R or another statistical package, you're able to do the same by just defining a new column.
Why this might be difficult is because a team's status as "Good" or "Bad" can change throughout the season. What you might consider instead is comparing games where the player did well versus games where they did not. Taking this approach, you might find correlations between a certain opponent and the player's performance, or opponent characteristics that correlate with the player's performance.
If you're looking at a specific player then it is pretty straight forward: You can pull the player's stats from a variety of websites and then define a binary (0 or 1) or categorical variable (Good, OK, Bad) for all teams based on their win percentage. I see a lot on this board using Excel, so if that is the program you are currently using, you can simply define another column and use an 'IF statement' that takes into account a team's winning percentage or whatever metric you've used to define "Good" versus "Bad". With R or another statistical package, you're able to do the same by just defining a new column.
Why this might be difficult is because a team's status as "Good" or "Bad" can change throughout the season. What you might consider instead is comparing games where the player did well versus games where they did not. Taking this approach, you might find correlations between a certain opponent and the player's performance, or opponent characteristics that correlate with the player's performance.
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