Adjusted WPA, 2004-2006

In my last post I introduced the idea of adjusting Win Probability Added (WPA) based on a player's position. While in the previous post I used only data from 2006 to calculate these adjustments, I have now calculated these adjustments for 2004-2006.

I have updated the average WPA/AB for each position. The table below shows WPA per 100 ABs, simply because it's more readable.

To apply this data, I went through the leaders in WPA from 2004-2006 (the Top 20 each year). In applying this data to the premier hitters in the game I decided to use plate appearances rather than at-bats, as the best hitters generally walk a lot, and the large discrepancy between PA and AB will skew their adjustment.

Below are the 04-06 leaders in Adjusted WPA/100 PA, looking at the players who have finished in the Top 20 in any of the last three years. Minimum 1600 PA (Bonds would be the leader without this criteria, with a ridiculous 1.43 Adj WPA/100 PA.) Data taken from FanGraphs and Baseball-Reference.

The usual suspects. I was somewhat surprised to see Abreu on this list, but that's probably just because his power has tailed off over the last couple years, and this year he's not hitting at all. But all the walks certainly help.

The top 10 in Adjusted WPA over the last three years:

How is Bonds at the top of this list? A ridiculous 12.21 Adjusted WPA in 2004, which comes out to 2.11 Adj WPA/100 PA. Jeter gets a sizeable boost from his positional adjustment- he moves from 15th on the unadjusted WPA list to fourth on mine.

How does Alex Rodriguez's 2006 season look? A measley 0.69 Adj WPA.

The 2006 AL MVP race is also interesting. Jeter actually leads Morneau in unadjusted WPA (6.03-4.53), and after the adjustment it isn't even close (6.62-2.87).

Morneau is actually behind teammate Joe Mauer in Adj WPA (3.49-2.87), and Johan Santana's 4.12 WPA leads both of them. Not the BBWAA's finest moment.

Over in the NL the adjustment doesn't make all that much of a difference, as Howard and Pujols play the same position. The result is as expected- Pujols 8.04, Howard 6.88.

Fun with WPA

One of my new favorite statistics is Win Probability Added (WPA). The concept of WPA is very simple- it is the effect a player has, in a given circumstance, on his team's chances of winning a game.

For example, if a hitter comes up with runners on first and second and two out in the bottom of the seventh inning of a tie game, his team has a 63% chance of winning. If that batter hits a home run, that percentage goes up to 95%. In this at-bat, this hitter had produced a WPA of .32.

Recently there has been more focus on WPA. The percentages above were calculated using this site. A couple years ago The Hardball Times' Dave Studeman wrote this fantastic overview of WPA. And there is even an entire site devoted to WPA- FanGraphs.

These sites piqued my interest in this statistic, but I found something missing. Stats like VORP and MLVr are adjusted for positions, but I had never seen this done with WPA.

I took the 2006 WPA statistics from FanGraphs, and sorted them by position. For each position, I then calculated the average WPA that came from an at-bat at that position. The results are as follows.







These results are pretty much in line with what I expected. I would have figured DH and 1B would be flip-flopped, but that is probably just an error caused by the small sample size. Later I will look at previous seasons.

The next step is to adjust actual WPAs using this data. My method of doing this was very simple- I took the player's at-bats multiplied by them by the per at-bat average for their position. Subtracting that number from their WPA gives us "Adjusted WPA".


Here are this season's current top 25 in unadjusted WPA, again courtesty of FanGraphs.




And here are the same 25 players, after their WPAs have been adjusted for their position. The final column is how far up or down their ranking has moved with this adjustment.

Not surprisingly, the order is significantly effected by adjusting for position. The middle infielders and catchers jump up the list, and corners fall back.

I plan on using seasons prior to 2006 fo make these adjustments more accurate, but I think these are pretty fair, and provide further insight to an interesting statistic.