The Olympics by the Numbers
Identifying trends in athlete data from the Summer Olympic Games.
The Summer Olympic Games are one of the largest sporting events in the world, with thousands of athletes from around the globe competing in various events. Olympians are considered the best of the best, the very pinnacle of physical capability — individuals who devote their entire lives to the pursuit of gold. We wanted to demystify the data concerning these athletes and find out if there were any identifiable trends in their physical traits. We also wanted to find reasons behind long standing Olympic records and along the way we came across some interesting cases involving technological doping. Thus, we designed an infographic showcasing all of our findings.
Our primary dataset included athlete information up-to the 2016 Rio Olympics. Given the popularity of the Olympics, it was surprisingly difficult to find a database containing athlete information from the 2020 Tokyo Games. Similarly, we couldn’t find data regarding Olympic records and had to manually construct our own dataset from information available online.
Early Ideations
Since our infographic was aimed at a general audience, we decided to pick visualizations that people were familiar with. The aim was to make the information as easy to read as possible, without requiring any prior knowledge from the viewer. When we started to hash out rough designs, based on relations we found through the dataset, we decided to divide the infographic into three parts based on our initial goals.
- The first two span graphs show the heights and weights of Olympic athletes categorized by various sporting events. They also show the average physical dimensions for all athletes and the mean dimensions of gold winners (where data is available).
- The third graph is a dot plot showing the age of unbroken Olympic records for various sports. We wanted to see how different factors affected athlete performance and helped them set new records.
- The final graph is a scatter plot showing record timings for the 100m sprint against the altitudes at which they were set. During our literature review, we came across a theory that was put forth after the 1968 Mexico City Olympics, that most sprinting records in the future would be set at higher altitudes since the lower gravity and air resistance at such heights is advantageous to short distance runners. This representation is an attempt to find out if the theory held well since then.
Final Infographic
The visualizations present on the infographic were designed in Tableau and later recreated in Figma for aesthetic purposes.
Findings
Do height and the weight affect athletes performance?
The first two span charts help us see if certain body types are more suitable for particular Olympic events. Starting with events where being tall is advantageous:
- Taller sprinters fare better in the second half of the race where their long stride length helps them cover distance faster. On the flip side, being shorter helps sprinters get off the block quicker.
- Since swimmers don’t start from blocks, the initial disadvantage of being tall doesn’t carry over to swimming. Larger torsos are generally more streamlined and longer limbs facilitate greater stroke length, meaning taller swimmers have a natural advantage.
Moving on the sports where shorter athletes are preferred:
- Gymnasts tend to have shorter torsos and limbs for increased mid air mobility.
- Marathoners too, fall on the shorter side, since smaller bodies expend less energy while running longer distances.
Lastly looking at sports where being average in height helps:
- Archers who are too tall or short have trouble finding a good sized bow while starting out, which might be a reason for record holders being of an average height.
Weight Comparisons:
- In order to maintain high strength to weight ratio, gymnasts are generally the lightest olympic athletes, with high muscle mass and low body fat.
- Marathoners and triathletes too, fall on the lighter sides since low body fat and muscle mass helps them dissipate heat faster.
Why are Olympic records broken so often?
On visualizing the data we found that certain sports had records broken in quick succession (as represented by the clusters being formed near the beginning of the x axis), while other sports had records that stood unbroken for decades.
On closer examination it became evident that sports which relied heavily on equipment such as rowing, cannoning, cycling and archery had gradual technological improvements over time, which aided athletes in breaking records.
On the other hand, in field events such as javelin throw, shot put and hammer throw, where the technology has remained largely unchanged for decades, athlete performance seems to have plateaued.
An interesting phenomenon we spotted while researching this graph was ‘technological doping’. Some equipments provided such a boost to athletes that it was unfair for others who could not access the same. Therefore these equipments were banned. Examples include Speedo’s LZR suits for swimming and Nike’s Vapor-fly shoes for marathoners which contributed to multiple record breaks and ended up getting banned. Serrated Tail Javelins were banned due to similar reasons.
Do sprinters really perform better at higher altitudes?
The visualization makes it evident that the theory which we was mentioned earlier, did not hold up. Most sprinting records after 1968 were set at much lower altitudes. While there are advantages that sprinters do get at higher altitudes, there are too many other factors at play for it to make any significant difference. The current record was set by Usain Bolt at the 2012 Olympic games at the height of mere 36 feet above sea level.
In conclusion, athletes falling into certain body types do have inherent advantages in certain sports, although, this can be overcome by rigorous training and developing new techniques. The performance of athletes has been increasing gradually over the years, but this effect is far more pronounced in equipment based sports.
[1] Olympic Dataset from Kaggle https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results?select=athlete_events.csv
[2] Gutiérrez, E., Lozano, S., & González, J. R. (2011). A recurrent-events survival analysis of the duration of Olympic records. IMA Journal of Management Mathematics, 22(2), 115–128.
[3] McFarland, E. (1986). How Olympic records depend on location. American Journal of Physics, 54(6), 513–520.
[4] The Economist (2021) Olympic records are being broken at a record pace https://www.economist.com/graphic-detail/2021/07/29/olympic-records-are-being-broken-at-a-record-pace
[5] The New Yorker (2021) Why Were So Many Running Records Broken During the Pandemic? https://www.newyorker.com/magazine/the-sporting-scene/why-were-so-maNy-running-world-records-broken-during-the-pandemic
[6] The Washington Post (2021) Olympians are probably older — and younger — than you think https://www.washingtonpost.com/sports/olympics/2021/07/31/oldest-youngest-olympians/
[7] The Stats Zone (2015) Olympic Sports — How Does Peak Age Vary?
https://www.thestatszone.com/archive/olympic-sports-how-does-peak-age-vAry-13812
[8] Abhishek Gautam (2020) Visual Analysis of Olympics Data
https://towardsdatascience.com/visual-analysis-of-olympics-data-16273f7c6Cf2
[10] Matthew Rautionmaa (2019) Olympic Games Data Visualization
https://nycdatascience.com/blog/student-works/olympic-games-data-visualization/
[11] Saúl Buentello (2021) 120 years of Olympic Games — How to analyze and visualize the history with R
https://towardsdatascience.com/120-years-of-olympic-games-how-to-analyzE-and-visualize-the-history-with-r-3c2a5f3bf875
[12] Chen, X., Yang, H., Ma, Y., & Zhou, B. (2010). A Magic Treemap Cube for Visualizing Olympic Games Data. International Journal of Virtual Reality, 9(3), 9–17.
[13] Pathak, P., Patil, N., Patil, A., & Patekar, M. (2019). Data Analytics of an Olympic Games. International Journal of Scientific Research in Computer Science Applications and Management Studies
