1. Russian Olympic Committee
2. Australia
3. China
4. Italy
5. Netherlands
6. Taiwan
7. Germany
8. Cuba
9. Austria
10. New Zealand
https://ig.ft.com/tokyo-olympics-alternative-medal-table/ 1. Russian Olympic Committee
2. Australia
3. China
4. Italy
5. Netherlands
6. Taiwan
7. Germany
8. Cuba
9. Austria
10. New Zealand
https://ig.ft.com/tokyo-olympics-alternative-medal-table/> Mimicking the original work by Bredtmann, Crede and Otten, we built the same model and fitted it on data for each Summer Olympic year between 1992 and 2008, and then used it to predict the medals table at London 2012. The full model outperforms a naive model that uses only the number of medals a country won and the year of the Games.
> We then fitted the same model on data up to and including the 2016 Rio Games, and used this to predict medal counts for Tokyo 2020 (using the latest available data for each input, i.e forecasts for GDP per capita and population in 2021).
Model: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-...
It wouldn’t surprise me if the vast majority of the model’s predictive power came from that, as opposed to GDP per capita, whether the country is Muslim (yes this is actually a predictor too!)