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Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions
In 2017, Sports Illustrated (SI) made headlines when their remarkable prediction from 2014 that the Houston Astros (a team in one of the lowest Major League Baseball divisional rankings) would win the World Series, came true. The less-publicised story was that in 2017, SI predicted the Los Angeles D...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8706002/ https://www.ncbi.nlm.nih.gov/pubmed/34941801 http://dx.doi.org/10.3390/sports9120163 |
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author | Jones, Justine Johnston, Kathryn Farah, Lou Baker, Joseph |
author_facet | Jones, Justine Johnston, Kathryn Farah, Lou Baker, Joseph |
author_sort | Jones, Justine |
collection | PubMed |
description | In 2017, Sports Illustrated (SI) made headlines when their remarkable prediction from 2014 that the Houston Astros (a team in one of the lowest Major League Baseball divisional rankings) would win the World Series, came true. The less-publicised story was that in 2017, SI predicted the Los Angeles Dodgers to win the Major League Baseball (MLB) title. Assessing the forecasting accuracy of experts is critical as it explores the difficulty and limitations of forecasts and can help illuminate how predictions may shape sociocultural notions of sport in society. To thoroughly investigate SI’s forecasting record, predictions were collected from the four major North American sporting leagues (the National Football League, National Basketball Association, Major League Baseball, and National Hockey League) over the last 30 years (1988–2018). Kruskal–Wallis H Tests and Mann–Whitney U Tests were used to evaluate the absolute and relative accuracy of predictions. Results indicated that SI had the greatest predictive accuracy in the National Basketball Association and was significantly more likely to predict divisional winners compared to conference and league champions. Future work in this area may seek to examine multiple media outlets to gain a more comprehensive perspective on forecasting accuracy in sport. |
format | Online Article Text |
id | pubmed-8706002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87060022021-12-25 Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions Jones, Justine Johnston, Kathryn Farah, Lou Baker, Joseph Sports (Basel) Article In 2017, Sports Illustrated (SI) made headlines when their remarkable prediction from 2014 that the Houston Astros (a team in one of the lowest Major League Baseball divisional rankings) would win the World Series, came true. The less-publicised story was that in 2017, SI predicted the Los Angeles Dodgers to win the Major League Baseball (MLB) title. Assessing the forecasting accuracy of experts is critical as it explores the difficulty and limitations of forecasts and can help illuminate how predictions may shape sociocultural notions of sport in society. To thoroughly investigate SI’s forecasting record, predictions were collected from the four major North American sporting leagues (the National Football League, National Basketball Association, Major League Baseball, and National Hockey League) over the last 30 years (1988–2018). Kruskal–Wallis H Tests and Mann–Whitney U Tests were used to evaluate the absolute and relative accuracy of predictions. Results indicated that SI had the greatest predictive accuracy in the National Basketball Association and was significantly more likely to predict divisional winners compared to conference and league champions. Future work in this area may seek to examine multiple media outlets to gain a more comprehensive perspective on forecasting accuracy in sport. MDPI 2021-12-01 /pmc/articles/PMC8706002/ /pubmed/34941801 http://dx.doi.org/10.3390/sports9120163 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jones, Justine Johnston, Kathryn Farah, Lou Baker, Joseph Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title | Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title_full | Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title_fullStr | Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title_full_unstemmed | Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title_short | Predicting Seasonal Performance in Professional Sport: A 30-Year Analysis of Sports Illustrated Predictions |
title_sort | predicting seasonal performance in professional sport: a 30-year analysis of sports illustrated predictions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8706002/ https://www.ncbi.nlm.nih.gov/pubmed/34941801 http://dx.doi.org/10.3390/sports9120163 |
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