The Fans’ Playing Time Projections

Tango has already covered the optimism in the FAN projections a couple of times — and why being so optimistic might not be that bad — but I wanted to look at it from another angle. I noticed that the fans project much more playing time than other projection systems. This is particularly evident at the top. CHONE projects Jimmy Rollins to have the most PAs at 682, the fans have 12 players with more PAs than that (including three with over 700), and, while CHONE has only three players with over 650 PAs, the fans have 53. Note: I understand that fans project number of games played and batting order and the system extrapolates number of PAs. I am using PAs because that is what is displayed on the projection page and makes for the easiest comparison.

How reasonable is it to project any given player will get 700 PAs? Obviously, every year some players get 700 PAs, but can we identify them beforehand? There will be more than three players who get over 650 PAs in 2010, but before the season starts can we really pick 50 players more likely than not to get 650 PAs?

I am going to assume that most people use past performance (number of games or PAs) to project how many a player will get in 2010. To see how well this works I got three groups of players. For group one I found players who had three consecutive years averaging between 725 and 675 PAs, then I looked at how many PAs they got in the next year. Group two I did the same thing for players who had three years averaging between 675 and 625 PAs. And for group three 625 to 575 PAs. Here are the number of PAs each of these three groups got in the next year. Along the x-axis is number plate appearances and along the y-axis the fraction of the group that got that many or more PAs. So each curve monotonically decreases as if you got over 101 PAs then you must have also got over 100.

The first thing to note is that the group of players with more PAs in the previous three years had more in the given year. That is, a greater fraction of group one had 400 or more PAs than group two and a great fraction of players in group two had 400 or more PAs than group three. And this trend holds for almost any number of PAs. This should not be surprising. Players in group one are probably better, healthier and hit higher in the order, on average, than those in groups one or two. So it seems perfectly valid to use past PAs as a predictor for number of PAs in the future.

But that doesn’t mean that you just use the past average as your prediction. The horizontal line at p=0.5 shows the median number of PAs for each group. These values are ticked off on the x-axis. They are 667 for group one, 630 for two and 557 for group three. Although players in all three groups still go a larger number of PAs it was less than they had averaged in the past three years — they regressed to the man. There is nothing special about three years (I just chose it to get players with a history of playing in lots of games) you would see the same drop off if you just chose players who averaged a large number PAs in the two previous or just the last year.

Next I highlight the fraction of each group that gets 700 or more PAs. That is the vertical line. The tick marks on the y-axis show the intersection points: 24% for group one, 12% for group two and 1.5% for group three. So less than a quarter of players who averaged about 700 PAs for three years got 700 PAs the next year.

Part of this is aging. In a given year, a player is older than he was three years ago, duh, and probably more likely to be injured and have fewer PAs. But part of it is that getting 700 PAs is part skill, being a good, healthy player who bats at the top of an order, and part is luck, not having a fluke injury. CHONE knows that there is a chance that any player has a crash in his playing time even with a long history of over-700-PAs, over-150-game seasons and a starting job leading-off. So it rarely projects over 650 PAs. Just because someone has played in over 150 games for a number of years we cannot expect him to play over 150 games in the next.

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Dave Allen's other baseball work can be found at Baseball Analysts.

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Awesome post, Dave. I really liked it.