Introduction & Inspiration
The ancient Olympic Games were held in honor of Zeus, the father of the Greek gods and goddesses, as part of a religious festival. It took nearly 1503 years for the Olympics to return where they were held in Athens, Greece in 1896 (The Games: The Real Story of the Ancient Olympic Games – Penn Museum, n.d.). Since then, the Olympics have been held every four years— just like they were in ancient times, with the purpose of honoring the origins of the Olympic Games(Why are the Olympic Games held every four years, 2021).
The Olympics Games is a special event that brings together almost every country from all over the world that showcases incredible hard work and talent. It has always been a beautiful event for me to watch and support our amazing athletes. I decided to explore this topic further so I could understand more about those that have competed in the Olympics and find out which countries have been winning the most amount of medals.
In order to gain some inspiration for my data visualizations, I decided to spend some time looking for similar visualizations that aimed to portray the Olympics. First, I looked at a visualization created by Marc Soares. Mark’s visualization was unique, in that it included visuals of each sport in the Olympics. He also did an awesome job coloring his bar graph of the medals each country won. His square graph could have been a bit more meaningful if he were to use more than one color. You can further see his visualization here.
The next visualization I got inspiration from was Team DATA, which was Tableau’s very own internal team. It aimed to highlight the U.S.A. team that competed in this year’s Olympic Games. Team DATA did a great job visualizing information that people don’t always consider, namely height, weight, shoe size, age, and gender. You can interact with it here.
Methods/Processes/Materials
In order to start putting together my visualization, I had spent a decent amount of time trying to find a dataset that would provide meaningful results. A lot of the datasets that I had found were often very messy and contained data in multiple different files. Besides that, many of the datasets I had found did not contain a lot of numerical values— making it quite hard to visualize them if I had decided to go that route. I had stumbled upon a dataset by Marc Santolini from data.world (Santolini, 2016). He created this dataset in order to understand how the performance of teammates affects your own performance. I then connected my dataset to Tableau. Tableau beautifully organized my data so that I may be able to visualize it.
Charts and Graphs
In order to understand the data, I tried to make it as lucid as possible. One data chart or graph would not have been sufficient to create salient information. I had to use a mixture of bar graphs, circle graphs, and scatterplots.
Color
I decided to use the Automatic color palette from Tableau for my visualizations but added my own spin to it. Not designing for color-vision deficiency is often a pitfall of color use. Due to this fact, I wanted to make sure the color palette I was using would be discrete.
For one of my graphs, I had used blue to signify a winter event and an orange color to signify a summer event. For the gender and age breakdown, I had used red to signify the women and blue to signify the men— I thought this would be easier to read than just a single color. I decided to go with a single color for displaying medals and countries because I would have easily run into the issue of encoding too much information. The graph showing the percentage breakdown of the countries has a categorical color scale because it displays categories that don’t have an intrinsic order.
Results and Interpretation
1. There is little to no correlation between the total population of a country and the number of medals they have won.
Although there are no exact records of what the population of each country was back in 1896, it is safe to say that the population of each country has minimal effect on how many medals the country wins. There have been many smaller countries less populous than China, for example, that have won a greater amount of medals. This shows that there is something else at play here.
2. There are significantly more medals won in the summertime than in the wintertime.
This is as a result of the number of sporting events that are held. In the wintertime, there are 15 sports competing. While in the summertime there are 46 sports competing (Summer Olympic Sports List, n.d.). Therefore, more sporting events translate to more medals won.
3. The average age for women competing in comparable events to men seems to be lower overall.
Based on this visualization it seems that women perform better the younger they are in the sport. Of course, there could be a number of other factors at play and it is hard to pinpoint the reason for this noticeable difference.
4. The countries that dominated the Olympics included France, Britain, Soviet Union, U.S. and Germany.
This could be as a result of these countries hosting the Olympics Games the most. There is tons of data to support this notion. Some of the reasons include positive energy from the home country, lower qualifications for hosting country’s athletes, and better sleep (Hernandez, 2021).
Reflection
Putting together these visualizations was a bit of a challenge at first. Finding the data to create visualizations from was the biggest roadblock to me finishing the project. I realized it was super important to have a dataset that I understood and found interest in, before starting to visualize it. Once I started visualizing the information, a lot of the information became more clear. I was able to transform a massive set of data into something that could be used to better understand the Olympics.
For future directions, I would like to explore the individual athletes a little further. There have been many athletes that have competed in multiple Olympics and have won medals in each of those Olympics. It would be interesting if I could see their height, weight, shoe size, and other factors that may have helped them on their journey to winning multiple medals.
References
T. (2021, July 15). Get to know Team USA. Retrieved from https://public.tableau.com/app/profile/team.data5561/viz/GettoknowTeamUSA_16263537776470/TeamUSAbytheNumbers
Hernandez, J. (2021, August 07). How Home Field Advantage Gives Olympic Host Countries An Edge – And More Gold Medals. Retrieved from https://www.npr.org/sections/tokyo-olympics-live-updates/2021/08/07/1025452727/how-home-field-advantage-gives-olympic-host-countries-an-edge-and-more-gold-meda
Santolini, M. (2016, September 21). Individual performance in team – dataset by msantolini. Retrieved from https://data.world/msantolini/individual-performance-in-team
Soares, M. (2016, August 9). A Brief History of Olympic Sports. Retrieved from https://public.tableau.com/app/profile/marc.soares/viz/ABriefHistoryofOlympicSports/HistoryofOlympicSports
Summer Olympic Sports List. (n.d.). Retrieved from https://olympics.com/en/sports/summer-olympics
The Games: The Real Story of the Ancient Olympic Games – Penn Museum. (n.d.). Retrieved from https://www.penn.museum/sites/olympics/olympicorigins.shtml
Why are the Olympic Games held every four years. (2021, September 07). Retrieved from https://olympics.com/ioc/faq/history-and-origin-of-the-games/why-are-the-olympic-games-held-every-four-years