Analysis of Predicted Medal Tables
We have listed the predicted medal tables for all the Sumer Olympic Games since 2000 (see medal predictions for 2000, 2004, 2008, 2012, 2016, 2021 and 2024). In order to compare the success of these predictions, we have come up with an analysis method that can be used on all the data so far, to compare the predicted to actual results. Basically, this method calculates the average percentage difference between their prediction and the actual results for the final top five results.
Our results demonstrate a large range of success in predicting the top medal winning countries.
We have analyzed the predictions from the 2000, 2004, 2008, 2012, 2016 and 2021 Olympic Games, and the results range from a percentage accuracy score of 56% up to 95%.
2021 Predictions
In 2021 there were 15 different predictions to compare. Using our percent accuracy score, the accuracy ranged from 66% to 93%. For the Tokyo Olympics, predicting performances were even more difficult than usual due to disruptions that occurred to the athletes' training, competition and qualifying events in the lead up the Games due to the coronavirus pandemic.
Total Medal Predictions
Below is the ranking of predictions for total medals won in 2021. The best (89% accuracy) was The best of these predictions was by Kuper et al. University of Groningen in the Netherlands, using an "econometric" approach.
| rank | percent accuracy score | prediction model | model method | published date |
|---|---|---|---|---|
| 1 | 89% | Kuper et al. (Uni of Groningen) | based on recent World Championships results, the number of athletes per country, and a host effect. | 2021 |
| 2 | 88% | Gracenote | recent sports results | July 16, 2021 |
| 3 | 78% | Olympic medals predictions | recent sports results | July 24, 2021 |
| 4 | 71% | BEST Sports | statistical models based on recent results | July 20, 2021 |
| 5 | 70% | Totallympics | recent sports results | 12 Dec 2019 |
| 6 | 68% | Towards Data Science | regression model based on previous Olympic Games results | 28 July 2019 |
Total Gold Medal Predictions
The best prediction for total GOLD medals won in 2021 was by the website "Olympic medals predictions", the prediction model based on the latest sport results leading up to the Olympics.
| rank | percent accuracy score | prediction model | model method | published date |
|---|---|---|---|---|
| 1 | 93% | Olympic medals predictions | recent sports results | July 24, 2021 |
| 2 | 92% | Totallympics | recent sports results | 12 Dec 2019 |
| 3 | 90% | Kuper et al. (Uni of Groningen) | based on recent World Championships results, the number of athletes per country, and a host effect. | 2021 |
| 4 | 89% | BEST Sports | statistical models based on recent results | July 20, 2021 |
| 5 | 88% | Financial Times | economic prediction model | 2021 |
| 6 | 87% | Gracenote | recent sports results | July 16, 2021 |
| 7 | 83% | Bleacher Report (July 22, 2021) | July 22, 2021 | |
| 8 | 82% | Frontiers | estimation based on Population, economic and geographic predictors | 2021 |
| 9 | 66% | Towards Data Science | regression model based on previous Olympic Games results | 28 July 2019 |
2016 Predictions
In 2016 there were 25 different predictions to compare. Medal prediction was particularly difficult for the Rio Olympics due to the unknown effect of the banning of many of the Russian athletes. The timing of the predictions was important, as the knowledge of how many Russian athletes would be competing was not known until just before the Games started. Using our percent accuracy score, the accuracy ranged from 65% to 90%.
Total Medal Predictions
Below is the top 10 predictions for total medals won in 2016, the best (90% accuracy) was Bredtmann et al., a prediction based on economic models, though adjustment was made just prior to the Games to reallocate 24 Russian medals. Just behind was Brian Cazeneuve of Sports Illustrated (88%), who used recent event results for his prediction. Good results were again achieved by the econometric model of Goldman Sachs (87%).
| rank | percent accuracy score | prediction model | model method | published date |
|---|---|---|---|---|
| 1 | 90% | Bredtmann et al. | economic model | Aug 2016 |
| 2 | 88% | Cazeneuve-Sports Illustrated | based on recent results | 29 July 2016 |
| =3 | 87% | Goldman Sachs | based on previous Olympic performance and economic growth | July 2016 |
| =3 | 87% | Olympic medals predictions | recent sports results | 4 Aug 2016 |
| =3 | 87% | Gonzales (Tuck School) | model incorporates four factors: available resources, population and per capita income, medals in the most recent Summer Olympics and a host effect | July 2016 |
| 6 | 86% | ATASS Sports | probabilities based on recent sports results | 5 Aug 2016 |
| =7 | 83% | Nielsen | results from recent world championships in Olympic sport disciplines and world rankings | 1 Aug 2016 |
| =7 | 83% | WSJ | part subjective reporting, part statistics and part computer simulation | 28 July 2016 |
| 9 | 82% | Gracenote | recent sports results | 3 Aug 2016 |
| =10 | 79% | AOC Benchmark | recent sports results | 17 Dec 2014 |
| =10 | 79% | PwC | factored in the size of economies, performance in the previous two Olympics; and host nation effect. | June 2016 |
Total Gold Medal Predictions
The best prediction for total GOLD medals won in 2016 was by the website 'Olympic medals predictions' (89%), which updated their prediction data the day before the Games began.
| rank | percent accuracy score | prediction model | model method | published date |
|---|---|---|---|---|
| 1 | 89% | Olympic medals predictions | recent sports results | 4 Aug 2016 |
| =2 | 82% | Gracenote | recent sports results | 3 Aug 2016 |
| =2 | 82% | Gonzales (Tuck School) | model incorporates four factors: available resources, population and per capita income, medals in the most recent Summer Olympics and a host effect | July 2016 |
| 4 | 81% | Nielsen | results from recent world championships in Olympic sport disciplines and world rankings | 1 Aug 2016 |
| =5 | 78% | Goldman Sachs | based on previous Olympic performance and economic growth | July 2016 |
| =5 | 78% | WSJ | part subjective reporting, part statistics and part computer simulation | 28 July 2016 |
| 7 | 77% | Barra | expert opinion | Dec 2015 |
| 8 | 76% | ATASS Sports | probabilities based on recent sports results | 5 Aug 2016 |
| 9 | 68% | Cazeneuve (SI) | based on recent results | 29 July 2016 |
| 10 | 70% | Kuper et al. (Uni of Groningen) | based on recent World Championships results, the number of athletes per country, and a host effect. | 14 July 2016 |
2012 Predictions
In 2012 we compared 19 different predictions. Using our percent accuracy score, the accuracy ranged from 54% to 95%.
The best predictions for total medals won were by Brian Cazeneuve of Sports Illustrated, who used predictions of each medal event based on recent results (94%). Goldman Sachs were also very accurate (94%) - they did not use any previous sports results, using instead previous Olympic performance and economic growth of each country. The highest accuracy score was by the Wall Street Journal (95%), which uses both athlete results and computer simulation, obviously quite successfully.
| rank | percent accuracy score | prediction model | model method |
|---|---|---|---|
| 1 | 95% | Wall Street Journal | part subjective reporting, part statistics and part computer simulation |
| =2 | 94% | Brian Cazeneuve | based on recent results |
| =2 | 94% | Goldman Sachs | based on previous Olympic performance and economic growth |
| =2 | 92% | Williams (Tuck School) | model incorporates four factors: available resources, population and per capita income, medals in the most recent Summer Olympics and a host effect |
| 5 | 90% | PwC | factored in the size of economies, performance in the previous two Olympics; and host nation effect. |
| 6 | 89% | Sports Myriad | recent results |
| =7 | 87% | Infostrada Sports (now Gracenote) | recent sports results |
| =7 | 87% | Bredtmann | economic model |
| 9 | 85% | Luciano Barra | expert opinion |
| 10 | 81% | Johnson | factors: income per capita, population, "nation-specific cultural effect", and a host nation advantage |
The most accurate prediction for total gold medals won in 2012 was also by Goldman Sachs (87%).
| rank | percent accuracy score | prediction model | model method |
|---|---|---|---|
| 1 | 87% | Goldman Sachs | based on previous Olympic performance and economic growth |
| 2 | 83% | Sports Myriad | recent results |
| 3 | 82% | Williams | model incorporates four factors: available resources, population and per capita income, medals in the most recent Summer Olympics and a host effect |
| 4 | 81% | Brian Cazeneuve | based on recent results |
| =5 | 79% | Wall Street Journal | part subjective reporting, part statistics and part computer simulation |
| =5 | 79% | Johnson | factors: income per capita, population, "nation-specific cultural effect", and a host nation advantage |
| 7 | 78% | Infostrada Sports (now Gracenote) | recent results |
| 8 | 70% | Luciano Barra | expert opinion |
Summary
Looking at the results over the years, and comparing the different prediction methods, there is still no clear best way. Now we wait for the predictions for 2024 to start coming in.
Related Pages
- Summer Olympics medal predictions for 2000, 2004, 2008, 2012, 2016, 2021 and 2024
- My analysis method for comparing the predicted to actual results
- My 2012 Gold Medal Table Prediction
- About Olympic Medal Ranking Systems
- Comparison of demographic and weighted ranking systems.
- Winter Olympics medal predictions
- medal tables from all Olympic Games
Any comments, suggestions, or corrections? Please let us know.
Upcoming Events