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22 February 2024

Introducing WAA: A metric to aid in player evaluation

Cincinnati, Ohio — In any discussion about how good a football player is, there will be at least some degree of variance in opinion from person to person. This holds true for everyone, from casual fans discussing their favorite player to scouts evaluating a player’s strengths and weaknesses to coaches contemplating how well a player might fit into different schemes.

WAA aims to mitigate this subjectivity and bridge the gap between these differences in opinion. It represents the number of wins a player is worth over an average college football player and is a metric that evaluators can utilize to assess performance. It combines how well a player performed in each facet of play (using PFF grades) and how valuable each facet is to winning football games. The result is a first-of-its-kind metric that allows for cross-positional valuation and predicts future value at the player and team levels.

QB Caleb Williams, USC: PFF WAA values since 2021.

WAA can be used for various applications related to NCAA football performance, analysis and prediction. The most prominent use case is in player evaluation.

With the hectic and overwhelming nature of the transfer portal — especially in its current state — utilizing WAA to more efficiently identify and narrow the lists of players worth pursuing could help coaches, scouts and recruiters save valuable time.


WAA is calculated by replacing all of a given player’s grades with 0 and then estimating what the team’s adjusted win total would have been. That number is then compared to the team’s actual adjusted win total to illustrate how many more (or fewer) games the team would have won if they had an average player in that role instead.

Player grades are aggregated by season, team, and player to return the sum of each facet grade and number of games. WAA is calculated by subtracting each player’s grades from their team’s grades and predicting the new win percentage for each team without that player.

This is done using the win rate model to predict the win percentage using the remaining team grades. We then calculate the difference in win percentage between the team with the player and without the player and multiply it by the number of games played to get the player’s WAA value.


Rank Player WAA
1 Bo Nix, Oregon 1.44
2 Michael Penix Jr., Washington 1.35
3 Jayden Daniels, LSU 1.28
4 Carson Beck, Georgia 1.19
5 J.J. McCarthy, Michigan 1.03

Please note: PFF WAA is not available via our consumer subscription. This metric is strictly for our team clients. Please visit PFF’s B2B site for more information.

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