An Analysis of a Player's Contribution to a Team's Success
The goal of the project is to use the box score to create a feasible metric measure a player's contribution to a win
Formula
Game Score(GmSc) Variance utilizes John Hollinger's Game Score metric as a basis to gauge a player's overall performance.
Each game a player plays is matched with their corresponding game score, and the average GmSc is measured.
Each game is then assigned ABOVE or BELOW depending on whether the GmSc is above or below average(Any GmSc equal to the average is voided).
The win percentage of above-average games is calculated along with the win percentage of below-average games, and the difference is calculated. That number is the GmSc Variance.
GmSc Variance:
GmSc Variance always fall between -1 and 1
GmSc Variance is not an indicator of a player's ability as a basketball player
Players with a GmSc Variance closer to 0 have less of an impact on their team's success between above and below-average games(If the GmSc Variance is close to 0 it doesn't matter whether the player plays above or below average, the team wins at the same rate )
Players with a GmSc Variance closer to 1 have more of an impact on their team's success for above-average games(If the GmSc Variance is close to 1 the team is more likely to win if the player plays above average)
Players with a GmSc Variance closer to -1 have more of an impact on their team's success for below-average games(If the GmSc Variance is close to -1 the team is more likely to win if the player plays below average)
These sheets show examples of how the data was organized
This scatter plot shows the GmSc Variance for each player analyzed
*A lower percentage of games played indicates a smaller sample size of games to use*
All Data Used came from Sports Reference LLC.Basketball-Reference.com