11,364 research outputs found
A Bayesian Variable Selection Approach to Major League Baseball Hitting Metrics
Numerous statistics have been proposed for the measure of offensive ability
in major league baseball. While some of these measures may offer moderate
predictive power in certain situations, it is unclear which simple offensive
metrics are the most reliable or consistent. We address this issue with a
Bayesian hierarchical model for variable selection to capture which offensive
metrics are most predictive within players across time. Our sophisticated
methodology allows for full estimation of the posterior distributions for our
parameters and automatically adjusts for multiple testing, providing a distinct
advantage over alternative approaches. We implement our model on a set of 50
different offensive metrics and discuss our results in the context of
comparison to other variable selection techniques. We find that 33/50 metrics
demonstrate signal. However, these metrics are highly correlated with one
another and related to traditional notions of performance (e.g., plate
discipline, power, and ability to make contact)
openWAR: An Open Source System for Evaluating Overall Player Performance in Major League Baseball
Within baseball analytics, there is substantial interest in comprehensive
statistics intended to capture overall player performance. One such measure is
Wins Above Replacement (WAR), which aggregates the contributions of a player in
each facet of the game: hitting, pitching, baserunning, and fielding. However,
current versions of WAR depend upon proprietary data, ad hoc methodology, and
opaque calculations. We propose a competitive aggregate measure, openWAR, that
is based upon public data and methodology with greater rigor and transparency.
We discuss a principled standard for the nebulous concept of a "replacement"
player. Finally, we use simulation-based techniques to provide interval
estimates for our openWAR measure.Comment: 27 pages including supplemen
Sports, Inc. Volume 4, Issue 1
The ILR Cornell Sports Business Society magazine is a semester publication titled Sports, Inc. This publication serves as a space for our membership to publish and feature in-depth research and well-thought out ideas to advance the world of sport. The magazine can be found in the Office of Student Services and is distributed to alumni who come visit us on campus. Issues are reproduced here with permission of the ILR Cornell Sports Business Society.https://digitalcommons.ilr.cornell.edu/sportsinc/1005/thumbnail.jp
Are NFL Athletes Receiving Over-Valued Contracts?
Many sport research studies have been conducted that examine the performance of professional athletes and their corresponding effect on franchise winning percentages, team revenues, economic repercussions, performance-based compensation, and much more. Research in the National Football League, however, has been found to be somewhat limited due to the numerous possible positions and resulting vastness of position-specific variables. The NFL lockout in 2011 caused many to question the specific relationship between professional athlete performance and salary distribution. This study’s purpose was to find a collection of variables with which all NFL athletes could be compared, and to identify relationships existing between a player’s performance and his value/salary. Data was collected from USAToday.com, Pro-football-reference.com, and AdvancedNFLStats.com. This data was then organized and manipulated into a format that allowed all players in the league during the 2009 season to be compared. Of the nine variables considered for this study, four were found to have a significant relationship with a player’s value/salary. These results were utilized to create a Player Valuation model and then analyze the overall salary distribution throughout the NFL. From this, it was observed while there are many athletes in the NFL that receive extravagant salaries well over their projected value, there is a much larger portion of the league that is undervalued and receive less than their projected value. It was then concluded that a super-star variable would be necessary to create a more accurate Player Valuation model, and the reason there is a larger proportion of NFL players receiving a lower salary than they deserve is due to franchise cap limits. These cap limits place pressure on franchises to push down the salaries of non-superstar athletes in order to compensate for the salaries required for the super-star athletes on their rosters
Sports, Inc. Volume 7, Issue 1
The ILR Cornell Sports Business Society magazine is a semester publication titled Sports, Inc. This publication serves as a space for our membership to publish and feature in-depth research and well-thought out ideas to advance the world of sport. The magazine can be found in the Office of Student Services and is distributed to alumni who come visit us on campus. Issues are reproduced here with permission of the ILR Cornell Sports Business Society.https://digitalcommons.ilr.cornell.edu/sportsinc/1008/thumbnail.jp
Sports Forecasting
A great amount of effort is spent in forecasting the outcome of sporting events, but few papers have focused exclusively on the characteristics of sports forecasts. Rather, many papers have been written about the efficiency of sports betting markets. As it turns out, it is possible to derive considerable information about the forecasts and the forecasting process from the studies that tested the markets for economic efficiency. Moreover, the huge number of observations provided by betting markets makes it possible to obtain robust tests of various forecasting hypotheses. This paper is concerned with a number of forecasting topics in horse racing and several team sports. The first topic involves the type of forecast that is made: picking a winner or predicting whether a particular team beats the point spread. Different evaluation procedures will be examined and alternative forecasting methods (models, experts, and the market) will be compared. The paper also examines the evidence about the existence of biases in the forecasts and concludes with the applicability of these results to forecasting in general.Sports forecasting, gambling markets, prediction markets
Sports, Inc. Volume 9, Issue 2
The ILR Cornell Sports Business Society magazine is a semester publication titled Sports, Inc. This publication serves as a space for our membership to publish and feature in-depth research and well-thought out ideas to advance the world of sport. The magazine can be found in the Office of Student Services and is distributed to alumni who come visit us on campus. Issues are reproduced here with permission of the ILR Cornell Sports Business Society.https://digitalcommons.ilr.cornell.edu/sportsinc/1012/thumbnail.jp
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