Journal of Quantitative Analysis in Sports
An official journal of the American Statistical Association
Editor-in-Chief: Glickman, PhD, Mark
4 Issues per year
SCImago Journal Rank (SJR) 2014: 0.265
Source Normalized Impact per Paper (SNIP) 2014: 0.513
Impact per Publication (IPP) 2014: 0.452
Volume 11 (2015)
Volume 10 (2014)
Volume 9 (2013)
Volume 5 (2009)
Volume 1 (2005)
Most Downloaded Articles
- Creating space to shoot: quantifying spatial relative field goal efficiency in basketball by Shortridge, Ashton/ Goldsberry, Kirk and Adams, Matthew
- Building an NCAA men’s basketball predictive model and quantifying its success by Lopez, Michael J. and Matthews, Gregory J.
- Predicting the draft and career success of tight ends in the National Football League by Mulholland, Jason and Jensen, Shane T.
- A generative model for predicting outcomes in college basketball by Ruiz, Francisco J. R. and Perez-Cruz, Fernando
- Introduction to the NCAA men’s basketball prediction methods issue by Glickman, Mark E. and Sonas, Jeff
Was There a Structural Break in Barry Bonds's Bat?
1University of North Texas (email)
2Appalachian State University
3Federal Reserve Bank of Dallas
Citation Information: Journal of Quantitative Analysis in Sports. Volume 8, Issue 3, ISSN (Online) 1559-0410, DOI: 10.1515/1559-0410.1305, October 2012
- Published Online:
In a recent paper, Fair (2008) utilizes monthly data on on-base percentage plus slugging percentage (OPS) to estimate the expected age profile of batting performance in Major League Baseball (MLB) and finds a peak performance at 27.6 years. However, he notes that a small group of 18 players have age-performance profiles that deviate significantly from the expected profile, most notably Barry Bonds. In this paper, we extend the work of Fair (2008) by investigating the time series properties of Bonds’s OPS to test for a deterministic or stochastic trend and to search for structural breaks. While Bonds’s performance is above average, we should not expect that deviations in his age-performance profile from that of the typical batter should contain a deterministic trend. In our investigation, we utilize unit root tests that estimate breaks using monthly data from 1986 to 2007. We find that Bonds’s OPS deviations follow a deterministic trend with two structural breaks. In particular, we find that Bonds’s OPS follows a positive trend to the age of 28.9 (June 1993), which coincides closely with the expected peak performance age. Following this, we find that Bonds’s OPS was on a plateau until a second break in September 2000. At this point, at the age of 36.1, Bonds’s OPS increases unexpectedly and then declines thereafter until his retirement in September 2007 at age 43.