Abstract
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.
Highlights
The 2019–2020 pandemic from the novel coronavirus (COVID-19) has brought unprecedented countermeasures to every sector of the economy, including individuals, groups, institutions, and industries
While all of this will alter predictions on who’s going to the playoffs, probably the biggest impact that this plan will have on the games is the lack of the home field advantage (HFA): the advantage that the home team has over the visiting team due to the home team having fans, the familiarity of the home team to their own ball park, and the away team having to travel
We developed a simulator to estimate what might happen if: 1) The full 2020 season continued on in a parallel universe devoid of COVID-19; 2) Major League Baseball (MLB) waits and is able to return and play half a season to packed stadiums around the All Star Break, which is assuming an extremely optimistic timeline of a return to normal life; 3) a full season is played without fans, which is likely the only way they will be able to play this season
Summary
The 2019–2020 pandemic from the novel coronavirus (COVID-19) has brought unprecedented countermeasures to every sector of the economy, including individuals, groups, institutions, and industries. The experience will be completely optimized for TV viewing, and so the league will be able to experiment with proposed rule changes, including removing mound visits to make the game go faster, adding a Robo Umpire, which has already been successfully tested last season via a partnership with the independent Atlantic League (Bogage, 2019), and an expanded roster giving players more rest due to the extremely hot temperatures of Phoenix While all of this will alter predictions on who’s going to the playoffs, probably the biggest impact that this plan will have on the games is the lack of the home field advantage (HFA): the advantage that the home team has over the visiting team due to the home team having fans, the familiarity of the home team to their own ball park, and the away team having to travel. This estimation helps decision makers understand how individual team performance will be impacted as they prepare for the 2020 season under the new article can be found at the end of the article
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