2026-09-19T18:50:09Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1202712022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
Anette Hosoi.
Ashoff, Tyler (Tyler L.)
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2019-02-05T16:02:46Z
2019-02-05T16:02:46Z
2018
2018
http://hdl.handle.net/1721.1/120271
1083220855
Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 24).
This observational study explores the relationship between home run rates and weather conditions, both on game day and over the preceding weeks. Data were collected from ESPN and Weather Underground for over 36,000 games between the 2003 and 2017 seasons. These consisted of game statistics and 59 weather variables. Random Forests was used to determine which set of these variables were important predictors of home run rates. Humidity was found to be the most important weather variable for predicting home run rates. The data suggest that a change of game day humidity from 100% to 0% can increase home run rates by 27% and ball travel by 15ft. For access to the data, please visit tylerashoff.com.
by Tyler Ashoff.
S.B.
24 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Understanding the relationship between weather conditions and home run rates in the MLB
Thesis
application/pdf
Publication
unknown
unknown
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