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1.As the Tokyo Olympics are facing many challenges, will the 2022 Beijing Olympics face similar or different challenges? How can we prepare for the smooth holding of the Beijing Olympics better?

While COVID-19 has not been fully overcome yet, the frequency at which pandemics occur has significantly increased during the last years. Therefore, it can be assumed that also the 2022 Beijing Olympics might face comparable difficulties to the Tokyo 2020 Olympics, which were postponed to 2021. For the organizing committee it will be crucial to implement a comprehensive hygiene concept for spectators (e.g. social distancing, masks, etc.). While only domestic visitors are admitted in Tokyo, several thousand fans from across the globe attended the European football championship in 2021. Thus, by 2022, there will be a sound data basis on the organization of large-scale events, that can be leveraged. Finally, it is vital to mention the athletes, who had to make considerable changes to their training schedules. Particularly during the first weeks after the spread of the virus, many of them suffered from performance loss, increased risk of injury, and diminished sleeping time and quality. Major lockdowns and quarantine restrictions before a tournament clearly impact the sporting performance.

2.What challenges will the pandemic bring to the Olympics? And what challenges and difficulty will the pandemic bring to forecasting the number of Olympic medals for each nation?

All nations were impacted by the pandemic, albeit to a different extent. In our article “Forecasting the Olympic medal distribution during a pandemic: A socio-economic machine learning model”, we model the COVID-19 effect based on the occurrence of infection and the economic damage caused by the pandemic. In a more granular analysis, it would also be interesting to take into account how many athletes retired early due to the postponement of the Olympic Games to 2021.

3.This article mentions that in addition to the Olympics, the prediction model also predicts ball games, etc. Are there any relevant successful examples? What do you think of the situation of the Beijing Winter Olympics in 2022?

Machine Learning in general, and the Random Forest in particular, has demonstrated a strong performance in several disciplines. In sports, there are examples of forecasting football games [1] or horseracing outcomes [2]. In our article, we apply a Two-Staged Random Forest, which accounts for the large number of nations without any medal success. This methodology is perfectly suited to also forecast the results of the Beijing Winter Games; particularly, as, by then, the impact of COVID-19 on the Olympic Games in Tokyo will become observable.

4.As the probability of vaccination in various countries increases, will the pandemic situation in some countries becomes more complex? How can it changes the distribution of the national medals?

We see that vaccination rates increase amongst the public and amongst athletes likewise. This is one important factor on the way back to major sports events as we know them from the past. In our analysis, we detect a link between low incidence numbers, respectively death rates, and Olympic success. This suggests the assumption that a successful national vaccination campaign might also find expression in Olympic medals.


[1] Groll, A., Ley, C., Schauberger, G., van Eetvelde, H., 2019. A hybrid random forest to predict soccer matches in international tournaments. Journal of Quantitative Analysis in Sports 15, 271–287.

[2] Lessmann, S., Sung, M.-C., Johnson, J.E., 2010. Alternative methods of predicting competitive events: An application in horserace betting markets. International Journal of Forecasting 26, 518–536.

Please let me know if you have any further questions.



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