Replication Data for: COVID-19 Countermeasures, Major League Baseball, and the Home Field Advantage
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'In the context of the COVID-19, almost all major leagues were either cancelled or postponed. Sports industry suffered a major blow with uncertainty of sporting events in the near future. Various scenarios of how and when sports might start back up have certainly been on everyone’s minds. This paper examines various scenarios of how the Major League Baseball team performance is going to be impacted in the presence of fans, or the lack thereof, in the context of physical distancing and other countermeasures in place. The paper simulates the win-loss probabilities for various scenarios under consideration as well as estimates the home effect for each team using the data for the 2015-2019 season. We show that team-home effect is symmetric between home and away and teams will not necessarily have a win or loss of any additional games in neut' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["MLB, Baseball, COVID-19, Neural Network, Logit"]} <|eot_id|>
 Here is the Description of a dataset. Description:'In the context of the COVID-19, almost all major leagues were either cancelled or postponed. Sports industry suffered a major blow with uncertainty of sporting events in the near future. Various scenarios of how and when sports might start back up have certainly been on everyone’s minds. This paper examines various scenarios of how the Major League Baseball team performance is going to be impacted in the presence of fans, or the lack thereof, in the context of physical distancing and other countermeasures in place. The paper simulates the win-loss probabilities for various scenarios under consideration as well as estimates the home effect for each team using the data for the 2015-2019 season. We show that team-home effect is symmetric between home and away and teams will not necessarily have a win or loss of any additional games in neut' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
In the context of the COVID-19, almost all major leagues were either cancelled or postponed. Sports industry suffered a major blow with uncertainty of sporting events in the near future. Various scenarios of how and when sports might start back up have certainly been on everyone’s minds. This paper examines various scenarios of how the Major League Baseball team performance is going to be impacted in the presence of fans, or the lack thereof, in the context of physical distancing and other countermeasures in place. The paper simulates the win-loss probabilities for various scenarios under consideration as well as estimates the home effect for each team using the data for the 2015-2019 season. We show that team-home effect is symmetric between home and away and teams will not necessarily have a win or loss of any additional games in neut
MLB, Baseball, COVID-19, Neural Network, Logit