Replication Data for: Estimating Major League Baseball Team Quality through Simulation: An Analysis of an Alternative Pythagorean Expected Wins Model
<|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:'Background. Contests are games in which the players compete for a prize and exert effort to increase their probability of winning. For sport contests, analysts often use the Pythagorean model to estimate teams’ expected wins (quality). We ask if there are alternative contest models that minimize error or information loss from misspecification and outperform the Pythagorean model. Aim. This article aims to use simulated data to select the optimal expected wins model among the choice of relevant alternatives. The choices include the traditional Pythagorean model and the difference-form contest success functions (CSF). Method. We simulate 1,000 iterations of the 2014 MLB season for the purpose of estimating and analyzing alternative models of expected wins (team quality).  We use the open-source, Strategic Baseball Simulator and develo' . 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" : ["Simulation-based statistical inference, Labor Productivity, Expected Wins, Major League Baseball, Pythagorean Model, Contest Success Function"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Background. Contests are games in which the players compete for a prize and exert effort to increase their probability of winning. For sport contests, analysts often use the Pythagorean model to estimate teams’ expected wins (quality). We ask if there are alternative contest models that minimize error or information loss from misspecification and outperform the Pythagorean model. Aim. This article aims to use simulated data to select the optimal expected wins model among the choice of relevant alternatives. The choices include the traditional Pythagorean model and the difference-form contest success functions (CSF). Method. We simulate 1,000 iterations of the 2014 MLB season for the purpose of estimating and analyzing alternative models of expected wins (team quality).  We use the open-source, Strategic Baseball Simulator and develo' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Background. Contests are games in which the players compete for a prize and exert effort to increase their probability of winning. For sport contests, analysts often use the Pythagorean model to estimate teams’ expected wins (quality). We ask if there are alternative contest models that minimize error or information loss from misspecification and outperform the Pythagorean model. Aim. This article aims to use simulated data to select the optimal expected wins model among the choice of relevant alternatives. The choices include the traditional Pythagorean model and the difference-form contest success functions (CSF). Method. We simulate 1,000 iterations of the 2014 MLB season for the purpose of estimating and analyzing alternative models of expected wins (team quality).  We use the open-source, Strategic Baseball Simulator and develo
Simulation-based statistical inference, Labor Productivity, Expected Wins, Major League Baseball, Pythagorean Model, Contest Success Function