Reimagining the 2024 Olympics Medal Table
The Paris 2024 Olympics ended less than a week ago and I’m mourning it while I wait for the Paralympics to begin1. Like my fellow compatriots, I was rooting for Brazil to get as many medals as possible, and we were slowly snatching them but it took us a while to get the first gold 🥇, so we were lagging at the infamous medal table, which made me wonder:
What is the importance of the medal table, anyway?
Of course I might have only questioned this because the position we were in felt uncomfortable: seeing Brazil with a few 🥈🥉 medals behind others that had a single gold 🥇. I know there is some soft power involved and in the end nothing is more thematic than competing in the medal table too, given we were already competing at everything else, but it still sounded weird.
I think there is room to debate the usefulness of the medal table ranking, one that requires a lot more development than I have time to2, but in the meantime it also sparked an innovative idea3 in my head: what if I simulated the medal table rankings using other metrics? Certainly there is one which is fairer than another, or at least it will give me fun insights.
When I set off to do it, I started listing what most people would think about, before figuring out several people had already done plenty of them before 3. I stuck to them, but also came up with new ones I hadn’t seen, morphing my initial objective from “seeing different medal tables” to “seeing how close to the top I could make Brazil stand”. Here are the statistics I picked:
- Total medal count: Simple, just summing up the three types of medal 🥇🥈🥉. It was also important as a base number for the other metrics.
- Weighed medal count: I get that gold should be more valuable than a silver, but at the same time if a country has 3 gold it sounded unfair to me to rank it higher than a country that potentially had 10 silver and 10 bronze. I initially went for the 🥇* 3 + 🥈 * 2 + 🥉, but was convinced by NYT to change the golden medal weight to 4, to give them some more special meaning of accomplishment.
- By delegation size: I wanted to see how efficient each country delegation was, after all, if a given country sends 10 athletes and all of them bring a medal back home, it seems a lot more successful than a country that sends 100 athletes and get the same 10 medals. Initially I wanted to rank them by “delegation potential”, which is to measure the potential number of medals a delegation could amass, given that in some sports like gymnastics and swimming a single athlete can win multiple medals. That seemed like it would take forever, so I used just the delegation size.
- By GDP: With reasoning similar to the above, I wanted to see how efficient a country was in “converting GDP” into medals. Here a similar more granular idea came, when discussing a friend of mine4: ranking the medal table by the percentage of their GDP invested into sports, but again this was too cumbersome to obtain.
- By Size: How efficient at getting medals given the country size?
- By Population: How efficient at getting medals given the country population?
- HDI: How does a higher Human Development Index (HDI) correlate to attaining more medals.
- By Golf Courses: I know, this does not make any sense whatsoever, but it was the statistic I thought could make Brazil fare the best. Unluckily for me Uzbekistan had only a single registered golf course up to 2021!
Without further ado, here are the different rankings I could come up to reorganize the top 20 countries at the Olympics 2024 medal table.
Kudos to OscarLeo’s tutorial on charts with flags and lipis’ flag icons
Turns out I got carried away and used way too many metrics, which left the chart almost unreadable. Here’s the rankings in “tabular format”5 for accessibility:
Country Total Weighed Size HDI Delegation Population GDP Golf Courses
0 USA 1 1 16 1 3 14 20 20
1 China 2 2 17 2 2 20 19 5
2 Japan 6 6 6 6 11 16 16 18
3 Australia 5 5 18 5 8 3 6 13
4 France 4 3 8 4 10 9 7 8
5 Netherlands 8 7 1 8 7 4 5 7
6 Great Britain 3 4 3 3 4 8 8 15
7 South Korea 10 10 2 10 1 12 10 11
8 Germany 9 9 9 9 16 13 18 14
9 Italy 7 8 5 7 12 10 9 6
10 New Zealand 13 12 10 12 13 1 4 9
11 Canada 11 11 19 11 15 11 15 19
12 Uzbekistan 16 14 12 17 6 17 1 1
13 Hungary 14 13 4 14 9 2 2 2
14 Spain 15 15 11 13 20 15 14 12
15 Sweden 17 17 13 16 14 7 11 17
16 Kenya 18 18 15 20 5 18 3 3
17 Norway 19 19 14 18 17 5 12 10
18 Ireland 20 20 7 19 19 6 13 16
19 Brazil 12 16 20 15 18 19 17 4If you want, here’s the source data and my messy code. It was fun to see how New Zealand has great results even though it is not among the biggest in many metrics. I couldn’t get Brazil further than fourth position, do you think I could have done it with any other metric? Let me know, because it seems for now I’ll just have to root harder for our athletes.
I was very hooked this time, and tried keeping track of as many sports as possible through the free coverage done by CazeTV ↩︎
Specially because there is the whole debate of accusing the USA to always pick the best “metric” to put them on top. I will not fall for this bait, or at least not today 😂 ↩︎
Turns out it was not innovative at all: Medals per capita, New York Times’ Medal Points, and so on. ↩︎ ↩︎
Yes Breno, that would be you. ↩︎
I was lazy and didn’t convert it to an actual table for the blog, nor fixed the indexing to start at 1. ↩︎