When Ironman Hawaii meets the Formula 1
Jakob Ohlsen Published: 10th March 2018
Have you ever wondered which nations are most successful at the Ironman World Championship in Kona? To find the best endurance nation we need a fair scoring system which takes a big enough number of athletes into account.
When I was looking for a good scoring system I checked out a number of other sports. Although it would be a great idea to take the athletes clothing, overall performance and style into account I had to scrap the idea to make use of the figureskating-scoring system, because there is just not enough data on the athletes B-score. I then took a look at the Formula 1 and derived a scoring method which is based on the point-system used in the fastest competition of motorsports.
The Formula 1 distributes the points as follows:
1st: 25 points
2nd: 18 points
3rd: 15 points
4th: 12 points
5th: 10 points
6th: 8 points
7th: 6 points
8th: 4 points
9th: 2 points
10th: 1 point
Because I wanted to take more than ten athletes into account I decided to distribute the points not just for the overall ranking, but for each age group, including the professional athletes. So Fidel Rotondaro, who won the age group M75-79 in an astonishing time of just 14:17:55 collected 25 points for Venezuela, just as Daniela Ryf collected 25 points for Switzerland.
Going through all results of the Ironman Hawaii 2017 I ended up with this overall nation ranking:
| # | Country | Points | Points/Athlete | In Top 10 | Athletes |
|---|---|---|---|---|---|
| 1 | United States | 649 | 0.879 | 67 | 738 |
| 2 | Germany | 269 | 1.234 | 22 | 218 |
| 3 | Australia | 266 | 1.142 | 26 | 233 |
| 4 | United Kingdom | 186 | 1.248 | 17 | 149 |
| 5 | Canada | 138 | 1.2 | 16 | 115 |
| 6 | France | 124 | 1.17 | 8 | 106 |
| 7 | Denmark | 119 | 1.889 | 10 | 63 |
| 8 | Netherlands | 101 | 2.658 | 6 | 38 |
| 9 | Switzerland | 90 | 2 | 9 | 45 |
| 10 | New Zealand | 63 | 1.615 | 6 | 39 |
| 11 | Finland | 61 | 3.588 | 7 | 17 |
| 12 | Belgium | 53 | 0.946 | 5 | 56 |
| 13 | Brazil | 51 | 0.593 | 6 | 86 |
| 14 | South Africa | 51 | 2.04 | 4 | 25 |
| 15 | Austria | 49 | 1.531 | 3 | 32 |
| 16 | Italy | 40 | 1.143 | 2 | 35 |
| 17 | Japan | 40 | 0.5 | 4 | 80 |
| 18 | Mexico | 39 | 1.393 | 3 | 28 |
| 19 | Norway | 36 | 3.273 | 2 | 11 |
| 20 | Russian Federation | 32 | 1.882 | 3 | 17 |
| 21 | Venezuela | 29 | 4.143 | 2 | 7 |
| 22 | Czech Republic | 26 | 1.857 | 3 | 14 |
| 23 | Sweden | 26 | 0.578 | 3 | 45 |
| 24 | Poland | 25 | 2.273 | 1 | 11 |
| 25 | Spain | 24 | 0.429 | 4 | 56 |
| 26 | United Arab Emirates | 18 | 18 | 1 | 1 |
| 27 | Costa Rica | 10 | 1.667 | 1 | 6 |
| 28 | Chile | 8 | 1 | 1 | 8 |
| 29 | Luxembourg | 8 | 1.333 | 1 | 6 |
| 30 | Argentina | 4 | 0.267 | 1 | 15 |
| 31 | Colombia | 4 | 2 | 1 | 2 |
| 32 | Ukraine | 2 | 0.5 | 1 | 4 |
| 33 | Paraguay | 1 | 0.333 | 1 | 3 |
| 34 | Singapore | 1 | 0.143 | 1 | 7 |
