Date

2019 12:00 AM

Major

Geological and Atmospheric Sciences

Department

Geological and Atmospheric Sciences

College

Liberal Arts and Sciences

Project Advisor

William A. Gallus, Jr.

Description

The Major League Baseball (MLB) regular season is unique in the fact that it spans from April through September, with the postseason being in October. Therefore, players are exposed to a variety of weather conditions during the 6-month span. The purpose of this study is to determine the relative predictability of the 2016 World Series game outcomes (wins/losses) by using six specific player statistics across various weather conditions experienced during the 2016 regular season. An analysis of how each team’s starting players performed under different temperature anomalies, wind speeds, and wind directions relative to home plate was compiled. These three variables were used to characterize the weather conditions for each World Series game, and a weighted average was calculated to determine each player’s representative performance in each game based off the present weather conditions. Team averages of the six baseball statistics were then found and compared against each other in order to conclude which team should have won the game based off weather conditions (team with more on their side wins). The proposed weather model predicts four correct actual game outcomes from the World Series, while a reference method that uses accumulated regular season statistics (no weather analysis) predicts five correct outcomes.

File Format

Application/pdf

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Jan 1st, 12:00 AM

The 2016 World Series from Mother Nature's Perspective

The Major League Baseball (MLB) regular season is unique in the fact that it spans from April through September, with the postseason being in October. Therefore, players are exposed to a variety of weather conditions during the 6-month span. The purpose of this study is to determine the relative predictability of the 2016 World Series game outcomes (wins/losses) by using six specific player statistics across various weather conditions experienced during the 2016 regular season. An analysis of how each team’s starting players performed under different temperature anomalies, wind speeds, and wind directions relative to home plate was compiled. These three variables were used to characterize the weather conditions for each World Series game, and a weighted average was calculated to determine each player’s representative performance in each game based off the present weather conditions. Team averages of the six baseball statistics were then found and compared against each other in order to conclude which team should have won the game based off weather conditions (team with more on their side wins). The proposed weather model predicts four correct actual game outcomes from the World Series, while a reference method that uses accumulated regular season statistics (no weather analysis) predicts five correct outcomes.