1. Boom & Bust: The Perils of Guaranteed Long Term Contracts Evidence from OPS100 Performance Over the Contract Cycle Heather O’Neill – Ursinus College Abstract This study focuses on panel data of 256 MLB free agent hitters under the 2006-2011 Collective Bargaining Agreement (CBA) to demonstrate that hitters, on average, increase their offensive production, measured by OPS100, during the last year of their contract and subsequently underperform the first year of the newly signed long term contract. The contract year phenomenon arises from the incentive to land a lucrative guaranteed contract for players not intending to retire. Signing a long term guaranteed contract creates an incentive to shirk (underperform) the first year of the new contract because performance and pay become unlinked and the need to boost performance for another contract is years away. A player’s intention to retire negates the incentive associated with a new contract, which mitigates the contract year boost and leads to greater shirking. Modeling OPS100 over the contract cycle requires focusing on within player behavior using seasonal statistics, intention to retire, and incorporating unobservable player traits, such as innate ability, work ethic, family background, etc. that may differ across players. Fixed effects, as opposed to OLS or pooled OLS, estimation addresses potentially biased results from omitting unobserved traits. Controlling for games played and team play-off contention, players at the end of a multiyear contact show a 6% boost in OPS100, but it declines by 1% for each percentage point increase in the probability of retiring. Players on one year contracts, however, boost their OPS100 by 13% without retirement effect. Signing a five year contract leads to a 4% drop in OPS100 during the first year of the newly signed contract and each additional year on a new contract creates another 2.5% decline in OPS100. While there is no evidence of shirking for two to four year contracts given no change in “retiring”, statistically significant shirking occurs for two to four year contracts if retiring intention increases by 8 and 3 percentage points, respectively. These findings suggest that general managers negotiating free agent contracts may wish to sign less than five year contracts to mitigate shirking behavior and estimate the likelihood of a player retiring since it impacts future performance. (+) (+) (+) (+) (-) (- ) Model & Hypotheses The population regression model for OPS (or OPS100) for player i in season t: (+) (+) (+) OPS100 i,t = β 0 + β 1 *GAMES i,t + β 2 *PLAYOFF i,t β 3 *CONTYR i,t + (+) (-) (-) β 4 *FIRST i,t + β 5 *SHIRKLENGTH i,t + β 6 *PROBRET i,t + A i + µ i,t GAMES: Playing more correlates with better performance PLAYOFF: Being on playoff contending team correlates with better performance CONTYR: Player boosts performance to garner future contract FIRST: In first year of a one year contract player boosts performance SLENGTH: Defined as FIRST*LENGTH Poorer performance the longer the contract PROBRET: Greater intention to retire reduces performance A i : Unobserved time-invariant player effects, such as innate ability, work ethic and family background µit: Stochastic error term PROBRET = α 0 + α 1 *YRSEXP + α 2 *YRSEXP2 +α 3 *DL +α 3 *OPS100 Likelihood of retiring increases at an increasing rate with MLB experience, increases with more days on the DL and falls with better performance Role of age depreciating performance enters through retirement Previous Regression Model Findings ”Just give me 25 guys on the last year of their contract; I’ll win a pennant every year.” Sparky Anderson Contract Year Only Papers Ordinary Least Squares (OLS) and Pooled OLS generally find no boost Ignoring retirement finds no boost Narrowly measured performance stats find no boost Fixed Effects + Retirement Intention + OPS find boost "The experience of individual clubs, and the industry as a whole, is that for whatever reason, the player's performance is not the same following the signing of a new multi-year contract.“ Dan O’Brian, VP (Indians) Shirking Only Papers OLS studies with Marginal Revenue Product find shirking OLS studies with non-revenue defined performances do not find shirking Some find shirking for contracts of 4 or more years Models with Contract Year & Shirking Fixed Effects with broad performance measure find both for 2 or more year contracts Greater retirement intention reduces boost and increases shirking Tales of Two Phillies Raul Ibanez’s OPS100 Jason Werth’s OPS100 Over His Contract Cycle Over His Contract Cycle Anecdotal Evidence: 4 of 7 Cases Conform to Expectations Let’s Play Ball with Robust Data & Modeling Data Sources & Simple Statistics 256 free agent hitters 6 or more years in majors yields 1,106 player/year observations - ESPN.com Major League Baseball Free Agent Tracker All playing under 2006-2011 CBA so that players face same incentive structure and employment rules OPS100 controls for home field and league, Games, Age - Baseball Reference.com Days on DL - Josh Hermsmeyer 2006-09; BackseatFan 2010; Fansgraph 2011 OPS100 lower in first year of multiyear contract 86.15 < 99.34 At face value suggests shirking BUT The average likelihood of retiring is twice as great in first year, 16.25 > 8.47 Retiring players have lower OPS100 stats Role players earn less $3.19 < $8.88 & have shorter contracts, 1.44 < 3.85 Role players have lower OPS100 stats Shirking is getting too much credit! Model correctly to yield unbiased result s Contract Year Impacts Multiyear Contract: ∆OPS100 = β 3 +β 6 *PROBRET^ 1 Year Contract: ∆OPS100=β 3 +β 4 +β 5 *LENGTH+β 6 *PROBRET^ Empirical Results (One tail p-values) (1) PROBRET^=.215 -.061*YEARSEXP +.006* YEARSEXP (.0539) (.0003) +.00034*DL -.0037*OPS100 (.1726) (.0001) Percent Correctly Predicted=.94 (2) OPS100^ = 104.707 +.0499*GAMES + 1.882*PLAYOFF (.0307) (.0556) + 5.396*CONTYR + 9.166*FIRST – 2.530*SHIRKLENGTH + (.0001) (.0001) (.0001) -.907*PROBRET^ (.0001) Buse R-Square =.77 Selected Works Cited Berri, D., & Krautmann, A. (2006).Shirking on the Court: Testing for the Incentive Effects of Guaranteed Pay.. Economic Inquiry, 44, 536-46. Krautmann, A., & Solow, J. (2009). The Dynamics of Performance Over the Duration of Major League Baseball Long-term Contracts. Journal of Sports Economics, 10(1), 6-22. Maxcy, J., Fort, R., & Krautmann, A.( 2002). The Effectiveness of Incentive Mechanisms in Major League Baseball. Journal of Sports Economics, 3(3), 246-55. O’Neill, H. (2013). Do Major League Baseball Hitters Engage in Opportunistic Behavior? International Advances in Economic Research, 19(3), pp. 215-232.. O’Neill, H. (2014). Do Hitters Boost Their Performance During Their Contract Years?” The Baseball Research Journal, 43(2), 78-85. Stiroh, K. (2007). Playing for Keeps: Pay and Performance in the NBA. Economic Inquiry, 45 (1), 145-161. Conclusions Incorporate likelihood of retiring & contract length for unbiased results Use fixed effects modeling to account for unobserved traits Contract year boost, independent of retiring : 5.4 point increase OPS100 at end of 2 or more year contract 12 point increase OPS100 at end of 1 year contract Contract year boost decreases OPS100 by 1 point per retirement increase Contracts of five years lead to shirking of 3.8 OPS100 drop, regardless of retirement, and 2.5 additional declines for each additional year on contract Two year contracts show shirking if 8+ point increase in retire probability Three year contracts indicate shirking with 5+ point increases in retiring Four year contracts show shirking starting with 3+ point increases Shirking Impact Multi-yr Contract: ∆OPS100=β4+β 5 *LENGTH+β 6 *PROBRET^ where LENGTH = 2, 3, …10