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May 10, 2010
Ahead in the Count
If They Stay or If They Go
In February, I wrote an article evaluating multi-year dealsgiven out to players with at least six years of service time, and I discovered something interesting. I found that players who re-signed with their current teams aged better than players who signed contracts with new teams, and not by a small margin. This finding gained some extra attention (and extra scrutiny) when I used it to question whether the Phillies might not have erred as terriblyas sabermetricians had suggested when they extended Ryan Howard's contract for five years and $125 million last month. The primary question that people asked was whether there was any bias in the ages of players who signed multi-year contracts with their current teams versus the ages of players who signed multi-year contracts with new teams. In fact, there is some difference in the ages of these groups of players.
While not a particularly large difference, the re-signed players were younger on average in the two-year and three-year deals, which were the contracts that showed major differences in aging. Does this explain the effect?
Let’s first focus on two-year contracts. This was the group where the aging difference was the most lopsided, with the re-signed players actually improving during their deals. I split this group of two-year contracts into different age ranges. Most players who signed two-year deals were older, so it was difficult to get very large sample sizes. I split them into a group of 14 players who were between 26-31 years old during the first year of their two-year contracts, a group of 23 players who were between 32-34 years old, a group of 20 players who were between 35-37 years old, and a group of 14 players who were between 38-47 years old.
Even in very small samples, we see a very large difference. Players who were re-signed by their current teams aged better than those players who signed deals with new clubs. In fact, each re-signed subgroup actually improved during their contracts, while three of four sub-groups of the newly signed players regressed during their contracts.
Does this hold for three-year contracts? The answer appears to be yes.
Even in a small sample size, we still see the same effects. Additionally, the older players who received three-year contracts appeared to drop off even more suddenly at the end.
Last time, we found that four-year contracts appeared to show little evidence of re-signed players aging better. Does breaking this down into players in different age groups reveal an affect?
This does not appear to provide any evidence either way, as we are now dealing with such small sample sizes that we cannot find any effect beyond the noise. Of course, this does not mean that there is no such effect on four-year deals, but it is certainly does not prove that there is.
Recently, well-respected sabermetrician Mitchel “MGL” Lichtman has stated that if this effect were true, it would be the “one of the most interesting and significant things to come out of sabermetrics since DIPS.” Of course, Lichtman also professed a profound skepticism of whether the results could be interpreted as true.
To me, this is not a matter of true and false. The results above are reflective of past events. They happened. Inasmuch as the contracts’ terms are reported to the media truthfully and WARP3 is computed in the way it is (and the results were the same for FanGraphs’ WAR), these results happened. The teams that re-signed their players did think that their knowledge of the players indicated they would be good bets, and they turned out to be just that. Thus, it is true that re-signed players aged well, as their teams believed. That does not imply that the future will necessarily show this same effect. In fact, the very publication of this series of articles might change this outcome, as other teams might target players more aggressively if their know those players' current teams are bidding for their services. All I can say conclusively is that this happened on average for the 140 contracts that ranged from two-four years long and concluded after the 2007-09 seasons.
Whether it will continue is not clear, because it is a market outcome, not a baseball outcome. When Lichtman alludes to DIPS, he is referring to a baseball outcome. If pitchers are unable to exert much control over BABIP, that will remain true as long as pitchers are trying to get hitters out (of course, if pitchers minimized their FIPs, this might not remain true). Once a market effect is discovered, it can be changed. While this market inefficiency is at least based on inside information and therefore stands a larger chance to stand the test of time, general managers can react to the market and make different decisions about signing other teams’ free agents.
In fact, this effect may not have existed in earlier years as re-signings may have been based on factors that no longer control clubs’ decision-making process. All we can say for sure is that these outcomes in the tables above are real for the years tested, and the effect appears to be large enough to suggest it is not random.
I will continue looking at this topic, and invite others to do the same. Determining this effect is no small issue, and may be a huge step in understanding a side of baseball economics that is not based on information you can find on Retrosheet. Sabermetrics has largely focused on aiding teams to make better decisions based on data generated on the field, but has remained unenlightened about data generated off the field. This could be a significant bridge to that information.