Team Performance Relative to Expectations and Its Impact on Player Personnel Decisions in Major League Baseball

2020 ◽  
Author(s):  
Michael A Roach
2011 ◽  
Vol 14 (2) ◽  
pp. 167-175 ◽  
Author(s):  
Christopher N. Annala ◽  
Jason Winfree

2018 ◽  
Vol 7 (2) ◽  
pp. 62
Author(s):  
Xing Lu ◽  
Jason Matthews ◽  
Miao Wang ◽  
Hong Zhuang

We use the U.S. Major League Baseball team level data in 1985-2015 and find an inverse U-shaped relationship between team payrolls and winning percentages. Furthermore, when investigating the winning effects of pitcher and hitter payrolls, we find the similar curvilinear relationship between pitcher/hitter salaries and team performance.


2008 ◽  
Vol 22 (3) ◽  
pp. 303-321 ◽  
Author(s):  
Dennis Smart ◽  
Jason Winfree ◽  
Richard Wolfe

Smart and Wolfe (2003) assessed the concurrent contribution of leadership and human resources to Major League Baseball (MLB) team performance. They found that player resources (defense/pitching and offence/batting) explained 67% of the variance in winning percentage, whereas leadership explained very little (slightly more than 1%) of the variance. In discussing the minimal contribution of leadership to their results, the authors suggested that future studies expand their operationalization of leadership. That is what is done in this study. Finding that the expanded operationalization has limited effect in explaining the contribution of leadership, we take an alternative tack in attempting to understand leadership in MLB. In addition, we estimate a production frontier (based on offensive and defensive resources), determine the efficiency of MLB managers relative to that frontier, and investigate the extent to which manager efficiency can be explained by manager characteristics. Finally, manager characteristics are related to manager compensation.


2017 ◽  
Vol 20 (1) ◽  
pp. 3-24 ◽  
Author(s):  
Duane W. Rockerbie ◽  
Stephen T. Easton

This article considers whether publicly financed new facility investments encourage professional sports team owners to increase their investments in costly talent. We develop a model of a sports league that incorporates publicly financed facility investments, the unique characteristics of the talent market, and revenue sharing to explore the complementarity between new facility amenities, the team budget decision, and team performance. Our empirical results suggest that publicly financed new stadiums do little to improve team performance, not due to restrictions in the talent market, but rather due to a lack of fan response.


F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 414 ◽  
Author(s):  
Justin Ehrlich ◽  
Shankar Ghimire

Background: In the wake of COVID-19, almost all major league sports have been either cancelled or postponed. The sports industry suffered a major blow with the uncertainty of sporting events being held in the near future. Various scenarios of how and when sports might recommence have been discussed. This paper examines various scenarios of how Major League Baseball team performance is going to be impacted by the presence of fans, or the lack thereof, in the context of physical distancing and other COVID-19 countermeasures Methods: The paper simulates, using a neural network and a logit regression model, the win-loss probabilities for various scenarios under consideration and also estimates the home effect for each team using data for the 2017-2019 seasons. Results: The model demonstrates that individual team home effect is symmetric between home and away and teams will not necessarily have a win or loss of any additional games in neutral stadiums, as teams with a high home field effect will lose more neutral games that would have been at home but will win more neutral games that would have been away. However, the result of individual games will be different since home effect is asymmetric between teams. Our simulation demonstrates that these individual game differences may lead to a slight difference in Play-Off Berths between a full season, a half season, or a full season without fans. Conclusions: Without fans, any advantage (or disadvantage) from home field advantage is removed. Our models and simulation demonstrate that this will reduce the variance. This stabilizes the outcome based upon true team talent, which we estimate will cause a larger divide between the best and worst teams. This estimation helps decision makers understand how individual team performance will be impacted as they prepare for the 2020 season under the new circumstances.


2015 ◽  
Vol 29 (6) ◽  
pp. 619-632 ◽  
Author(s):  
Nicholas Watanabe ◽  
Grace Yan ◽  
Brian P. Soebbing

From the perspective of economic demand theory, this study examines the factors that determine daily changes in Twitter following of Major League Baseball teams as a form of derived demand for a sport product. Specifically, a linear regression model is constructed by taking consideration of factors relevant to fan interest: team performance, market characteristics, scheduling, and so on. The results reveal specific determinants that have significant relationship with Twitter following. From a team management perspective, factors such as the content of social media messages, certain calendar events, and postseason appearances can be used to enhance fan interest on social media. In so doing, it brings together communication inquiries and economic literature by delineating a comprehensive and nuanced account of interpreting sport social media from a consumer demand perspective.


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