How did the games look through stats?

Tokyo 2020 OG numbers

Age at the Olympic Games
*on the blue side of the charts numbers should be considered positive numbers
5 years ago in Rio paddlers' age was more concentrated in the over 23 section, it is more evenly spread in Tokyo 2020. Especially in the women, as the three central sections have almost the same amount of paddlers. A significant amount of men, 28%, are in the oldest segment. 
Medal average is always between 27 and 29 years old.
Results by countries
Four more countries were present in Tokyo than in Rio 2016. Compared to Rio, two extra countries achieved a medal. Although, the countries that accessed a final (medalling or not) remained the same, 18. So there is more countries participating at the games, but the same number getting into the finals. Portugal, Russia and Switzerland changed their final spots in Rio 2016 with Ukraine, Netherlands and Sweden in 2021. That makes 21 different finalist countries between the two Olympic games combined.
5 teams made all the finals, and all of them medalling in at least one event.
The Olympic games is a special race in terms of number of participants, and one would say that performance density should be lower than normal ICF races. In order to find out, we've used the same system as previous bulletins, obtaining a reference across classes. In this case, 100% is the average of the best time of the course in MK1, WK1 and MC1 as they are the classes present in both Rio 2016 and Tokyo 2020, so we can compare them evenly.

Races used to establish an ICF races average were 2019 and 2020 World Cups excluding 2019 Tacen WCS.
We have compared performances at three break points of the races:
  • % necessary to win. 
  • % is necessary to get a medal.
  • % is necessary to get into the final.
Be aware that these are not absolute values, what we are really doing is establishing how hard it is to break these points compared with the best performances of the race. Having this in mind, if the best performances are relatively poor performances, it will affect the rest. But we consider that using a 100% made across classes should compensate 'anomalies' on best performances.

Said that, winning on M1K in Tokyo was harder than the previous games or the average ICF races, and quite the opposite for the bronze medal. Getting into final was a little easier, but harder than it was in Rio.

WK1 and MC1 in Tokyo presented a very similar race compared to the ICF average, and quite in line with Rio 2016.

WC1 was new on the Olympic program and data is showing that getting into medals required a significantly better performance than on the ICF average. Break point for getting into the final was as demanding as it is in a regular World Cup. 
How all this numbers apply to my work with a team?
Have a glimpse by using this web app for slalom analysis:
Analysis tool
Please, remember that we at slalomstats also can make reports for your team or federation, or at least automate them as you saw on the tool. Do not hesitate to contact us by email.

Finally, you have a lot more in our website:
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