from Amazon
Tuesday, June 05, 2007
Another Aging Study
Guest-blogger Steve Walters over at the Wages of Wins blog links to an aging study by Ray Fair (PDF). I was asked to review the paper a few months ago, which I have reprinted in the comments section, and will repost here:
“but surprisingly there seems to have been no rigorous attempt to estimate them”
There are several articles noted here:
http://www.tangotiger.net/#Forecast
The choice of “10 years” has its own selective sampling issues, as only certain quality of players will be in that pool. That pool of players is hardly representative of the population of MLB players. See this mini-study for more information:
http://www.tangotiger.net/archives/artAging.shtml#1013
The effect is for the curve to be flatter than it should be.
You acknowledge injury as a possible outcome, but ignore it afterwards. It’s a big deal, especially for pitchers.
A 9% increase in ERA from age 26 to 37 (3.50 to 3.81) is pretty much impossible to believe. That is extremely flat. The sampling issues noted above need to be addressed.
You talk about the 90s (steroid-era), but you also acknowledge that you did not adjust for the change in run environment. The 1993-2006 time period is a huge offensive era. Without adjusting for the context, it’s going to look like hitters are going better in those years. As well, the new parks are more offense-friendly these days.
While the overall model by age won’t change if you adjust for parks and year, you can’t then ignore these issues when looking at 1990s players in particular. They need to be adjusted, if you are going to focus on them.
While you choose 10+ year periods for each pitcher, you don’t have the same pitchers in each age group. You can have a 10yr period from ages 23-32 or 25-34, or a 15yr period from 22-36, etc. As noted in one of my linked articles, you need to pair the age groups to have the same pitchers and the same weights in each age group. So, select the same pitchers at age 23 and 24, and weight them equally. Then, select the same pitchers at age 24 and 25, etc. The pitchers of 23/24 do not need to be the same as 24/25.
And the comparisons of ERA to chess is not appropriate. Losing 15% in ERA would be the equivalent of losing 7.5% in OBP. It’s just not a 1:1 comparison.
OPS is not a good measure to use for ranking players, in addition to the other problems I noted earlier. Linear Weights would have been a better choice.
ERA also has its own problems (being fielder-dependent as well as the sequence-of-events dependent), and a “component ERA” similar to Linear Weights, would have been more appropriate.