WPA starts with a Win Probability (WP) model of the game of football. Every situation in a game gives each opponent a particular chance of winning, and a WP model estimates those chances. The model created here at Advanced NFL Stats uses score, time, down, distance, and field position to estimate how likely each team will go on to win the game. For example, at the start of the 2nd quarter, a team down by 7 points with a 2nd down and 5 from their own 25 will win about 36% of the time--in other words a 0.36 WP.
On that 2nd down and 5, let’s say there is a 30-yard pass, setting up a 1st down and 10 on the opponent’s 45. Now that team has gone from a 0.36 to a 0.39 WP. The WPA for that play would be +0.03.
If instead the quarterback throws an interception returned back to the line of scrimmage, the opponent now has the ball at the 25, giving the trailing team a 0.28 WP. The WPA for the interception would be -0.08.
WPA is very sensitive to the context of the game. That same interception that cost -0.08 when a team was down by 7 points in the 2nd quarter would cost much more if it the offense was leading by a point late in the 4th quarter. Putting your opponent in immediate field goal range would be nearly fatal.
Stats are tools, and each tool has its own purpose. WPA is what I call a narrative stat. Its purpose is not to be predictive of future play or to measure the true ability of a player or team. It simply measures the impact of each play toward winning and losing.
WPA has a number of applications. For starters, we can tell which plays were truly critical in each game. From a fan’s perspective, we can call a play the ‘play of the week’ or the ‘play of the year.’ And although we still can't separate an individual player's performance from that of his teammates', we add up the total WPA for plays in which individual players took part. This can help us see who really made the difference when it matters most. It can help tell us who is, or at least appears to be, “clutch.”
