Forecasting National Medal Totals at the Summer Olympic Games Reconsidered
Bibliographic Data
| ID | 10763523 |
|---|---|
| Authors | Nicolas Scelles (0000-0002-6177-5307, Manchester Metropolitan University, corresponding author), Wladimir Andreff (0000-0001-6098-3078, University Paris 1 Panthéon Sorbonne), Liliane Bonnal (0000-0002-9972-2470, Université de Poitiers), Madeleine Andreff (University Paris‐Est Marne‐la‐Vallée), Pascal Favard (0000-0001-5011-8777, Université de Tours) |
| Year | 2020 |
| Volume | 101 |
| Issue | 2 |
| Pages | 697-711 |
| Publication date | 2020-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Science Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 0038-4941 • E-ISSN: 1540-6237 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ssqu.12782 |
| OpenAlex | W3010180859 |
| Language | EN |
| Citations received | 7 |
| References cited | 18 |
Objective This article aims at explaining national medal totals at the 1992–2016 Summer Olympic Games ( n = 1,289 observations) and forecasting them in 2016 (based on 1992–2012 data) and 2020 with a set of variables similar to previous studies, as well as a regional (subcontinents) variable not tested previously in the literature in English. Method Econometric testing not only resorts to a Tobit model as usual but also to a Hurdle model. Results Most variables have a significant impact on national team medal totals; it appears to be negative for most regions other than North America except Western Europe and Oceania (not significant). Then, two models (Tobit and Hurdle) are implemented to forecast national medal totals at the 2016 and 2020 Summer Olympics. Conclusion Both models are complementary for the 2016 forecast. The 2020 forecast is consistent with Olympic Medals Predictions, although some striking differences are found
Econometric model · Econometrics · Geography · Medal · Regional science · Statistics · Tobit model · Mathematics · Sport and Mega-Event Impacts · Sports Analytics and Performance · Sports, Gender, and Society
The influence of schooling on performance in chess and at the Olympics
Forecasting the Olympic medal distribution – A socioeconomic machine learning model
How Countries Compete for Success in Elite Sport
Latin American structure and Pan-Am Games
How to win the first Olympic medal? And the second
Popularity and Visibility Appraisals for Computing Olympic Medal Rankings
With a Little Help From My Friends? Understanding Individual and Team Success in the Summer Olympics
| Unique citing works | 7 |
|---|---|
| Citations per year | 1,17 |
| Citation span | 2020 - 2025 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |