Going For Gold At The Paralympics
A Short History of the Paralympics told by Data
After a long delay due to the global pandemic, we finally saw the Olympics and Paralympics come back in Tokyo 2021. And what a fantastic event it was, giving us moments we will never forget, such as, in the Men’s high jump Italy’s Gianmarco Tamberi and Qatar’s Mutaz Essa Barshim decided to share the first place position rather than go into a jump off, USA gymnast Simone Biles making a comeback to win bronze on balance beam after withdrawing from multiple events to focus on her mental health, and the debut of skateboarding and karate were fantastic to see. These are all special instances from the Olympics that will forever be remembered, however, there are other games.
In the last decade, the Paralympics have gained huge popularity, despite this, the Paralympics are often overshadowed by the Olympics. It comes as no surprise that there is less viewership of the Paralympics, less interest on social media from the general population and the Paralympians themselves are not as iconic as previous Olympians such as Usain Bolt. This is a shame as the Paralympics should be just as, if not more impactful than the Olympics, there are just as many inspirational role models from the Paralympics like GB women swimmer Ellie Simmonds winning gold at the young age of 13 in Beijing 2008. The Paralympics symbolises that there are no obstacles for disabled people to achieve at the highest level. Awareness has been improving and this made me wonder. Does every country have similar statistics and correlation between the Olympics and Paralympics?
I wanted to investigate this as I feel strongly that the awareness and appreciation of disability should be high, I wanted to investigate if there have been any awareness since the beginning of the games and how it has improved over time. The discrimination and lack of awareness towards disability were really high at the time the Paralympics started (1960). So, it is important to see if improvements have been made and this is what I am seeking. I am attempting to identify countries that do much better in the Olympics than the Paralympics, see if there are countries ignorant of the Paralympics. If there are countries that are, I hope to find out what factors contributed to this.
Data Collecting
To start off this project, I will need to gather the data for the Olympics and Paralympics countries, sport and medal winners. Look into all possible aspects of information that can be gathered, how many entrants, winners per entrant, etc. and go on to compare how the countries perform each year.
I obtained the Olympic database from Dataworld.com, in this database there was data on trigram (e.g. GBR), country, year, event, rank, athlete name, gender, age, sport, gold, silver, bronze, total and the athlete URL. Sports were generally grouped, for example, all athletic events are categorised as athletics instead of 100m, 200m, etc.
The Olympic data was very easy to find, there were hundreds of sources available on the internet. On the other hand, the Paralympics data sets were nowhere to be seen. This also indicates the lack of awareness and popularity for the Paralympics which is one of the problems and the reason I started this project. I was able to find Paralympic data on Kaggle but only about how many entrants and medals each country has per year. It had the year, host city, host country, country, trigram, gold, silver, bronze, total medals, men, women, total entrants. The information lacking is the sport they won the medals in. To gather this missing data, I scraped data from the IPC Historical Results Archive. For this, I had to go through every year and sports event to find which country had won how many of each medal. From this, I was able to map the year and country to add a sports column in the database. This does come with its own set of limitations as it does not tell me which country has entered a sport if they have not won a medal.
Cleaning
Onto the cleaning process, all columns that were not required were discarded. This left year, country, sport, gold, silver, bronze, and total medals for both Olympics and Paralympics. However, the Paralympic database has total entrants, unlike the Olympics. Sport and entrants are different data. I checked for nulls and there were none. I kept only the summer events as that was all I was interested in. The first Paralympics was in 1960 so I discarded all the events beforehand. On the other hand, the latest event data I had for the Olympics was 2012 so I discarded everything after that in the Paralympics data. One issue I faced was in the Olympic database there’s a column is listed as athletes, this meant there were situations in team sports where it will show a country winning multiple medals. For example, Argentina will have 18 Gold medals from men’s football in 2004 Athens when it should only be one. Team sports included football, water polo, hockey and so on. As sports titles were generalized, I was not able to distinguish the difference between 100 metres gold medal and a 4x100 metres gold medals as they were both titled athletics. This is one of the limitations and reduces the accuracy. A similar process was carried out on the Paralympics dataset, with sports such as wheelchair basketball being an example.
The Start of the Paralympics
The first piece of information I looked for was the Olympics entrants information to find how many events each country participated in each year. An entrant is not an athlete, it is how many athletes or teams participated per country. Using this I wanted to compare the entrants’ numbers at the beginning of the Paralympics lifespan.
Just to have a quick history lesson about the Paralympics, the first-ever official event was held in Italy in 1960. Before this, there were many clubs for the sensory impaired. It was not until after World War 2 that there was a large increase in disabled sportspeople, as many were veterans of war or had diseases such as polio. In 1948 an event called the Stoke Mandeville Games was held where wheelchair participants could join and do archery. This was a yearly event, in 1952 a Dutch team joined making it international for the first time. In 1960 it was renamed as the Paralympics and more sports were introduced.
So, in the first-ever official Paralympics, there was a total of 209 entrants whilst the (1960) Olympics had 4,582 entrants. The Paralympics only had 17 countries attending, mostly from Europe with the United States of America, Australia, Argentina and Zimbabwe (known at the time as Rhodesia) also joining. In this event, Great Britain made up most of the entrants, in the Olympics, it was the United States of America. Even though the Olympics had more than 20 times the amount of Paralympics’ entrants, this was not surprising, the Olympics was already an esteemed worldwide event and the Paralympics had just started, and awareness and support offered towards disability were almost non-existent in many countries.
Since awareness was low and the Paralympics was new, I wanted to see how it grew over the next decade, from 1960 to 1972. The numbers of entrants were 209 (1960), 266 (1964, 2.3% increase), 775 (1968, 191% increase) and 922 (1972, 19% increase). Going from 17 countries attending Rome in 1960 to 40 in Mandeville United States of America and Stoke in Great Britain in 1972. At this point, Great Britain and the United States of America had the most entrants with more than 230 each, which is really large considering the next highest country was France with 139.
Next, I wanted to visualize which countries attended, looking from 1960 to 1968, as in 1968 was the huge increase year in entrants for the Paralympics. The maps of the world here show every country that attended, the darker shade of blue meaning they take up a larger proportion of the events’ entrant.
You can see in the Olympics that almost the whole planet attended — as by 1968 most African countries had some entrants, numbers continued to grow. The Paralympics looks very different in comparison as the noticeable countries are the United States of America, Australia and Argentina along with the majority of Europe in 1960, and after that, the newcomers were the likes of Paralympics host countries, India, Canada and South Africa. The interesting thing about South Africa was the country paradoxically was allowed to attend the Paralympics despite being banned from competing at the Olympics. South Africa had been banned from the Olympic Games following the passing of United Nations General Assembly Resolution 1761 which, in 1962, condemned the country’s policy of apartheid. South Africa then became absent from the Paralympics from 1980 due to the apartheid. When the country started to dismantle this policy, South Africa was able to attend the Olympics and Paralympics once again in 1992.
The next element I examined was host cities and if that affected certain countries attending the event. In these maps, the host cities are shown in the red rings. I thought of this analysis as in the 1960 Rome Paralympics many of the countries attending were from Europe, which gave me the idea that countries will attend the Paralympics if they were nearby. This is not true, as in the 1964 Paralympics hosted in Tokyo, outside the host country Japan no other Asian country attended. This follows with the 1968 Paralympics held in Tel Aviv. The 1968 Paralympics was not hosted in Mexico City where the Olympics were held, this was due to technical difficulties — these difficulties were not pointed out but were possibly due to the high altitude of the games.
Please find the dashboard for this here.
Post-2000s Entrants
After looking at the beginning of the Paralympics, let’s look at the other end with the more recent events, games post-2000s. I was intrigued to see how the world holds up in the big data age, as the whole world now has had time to catch up and produce similar numbers to their Olympic teams. The latest event I have to show is 2012 and for the Olympics, there was 8,501 entrants and the Paralympics 4,243. It is expected that the Olympics will have more as there are 26 sports compared to the Paralympics’ 20, however, this does not justify the Olympics having more than double the entrants of the Paralympics. On a positive note, the Paralympics have grown massively and continue to increase entrant numbers in every event with an average 32% increase.
A statistic I thought would be interesting to look at is the difference in entrant numbers between the Olympics and Paralympics for each country. It is no surprise that in early events there is a large difference as many countries had a very small or no Paralympic team. Where these figures highlight differences is post-2000s (So 2004, 2008 and 2012). Looking only at the countries that have large entrant numbers (more than 40 in the Olympics) and have at least 30 entrants less in the Paralympics than the Olympics.
The result was that 31 countries had 30 entrants or less in the Paralympics in all 3 events. The biggest differences were for the United States of America, Italy and Germany, but are they really the countries with the largest contrast? The absolute difference is not the best measurement to see this, so looking again at these 31 countries and using the percentage difference gives us totally different results.
The countries that had large differences were mainly due to having larger Olympic teams, so their percentage difference better represents a country’s attitude to the Paralympic team and this shows with the United States of America as being one of the smallest. So, with this, the 3 largest are now Kazakhstan, Romania and Uzbekistan. To give some figures, in 2004 Uzbekistan had 69 entrants in the Olympics but only 1 entrant in the Paralympics. Another example is in 2008 Kazakhstan had 105 Olympian entrants and only 3 Paralympian entrants. These are inexcusable differences but investigating further the factors seem to be around the country’s economic development. These countries (Uzbekistan, etc) are all less economically advanced and also have a high population. Looking at another country that is considered poor and has a population of over a billion, India. India has consistently a difference of more than 45 between the Olympics and Paralympics from 2000 onwards, with an average percentage difference of 28.5%. This proves further lesser economically developed countries have a tougher time making up entrant numbers for the Paralympics.
Please find the dashboard for this here.
Medals
Having spoken a lot on entrants, it is time to look at medal success. The first thing I did before finding medal information was to categorise sports. Olympic sports are categorised into 5 categories based on popularity, gauged by:
- Television Viewers (40%)
- Internet Popularity (20%)
- Public Surveys (15%)
- Ticket Requests (10%)
- Press Coverage (10%)
- Number of National Federations (5%)
The category determines the share of Olympic revenue that the sport’s International Federation receives, some examples of categorisation are athletics are in category A, Boxing in category C and Fencing in category D. There are no determined categories for the Paralympics. I thought categories would be really interesting to look into as it brings the idea of countries paying more attention to the more popular sports. Using the Olympics’ categorisation as a starting point, I placed every Paralympic sport into a category. Some examples are Football 5-aside in category B and wheelchair fencing in category D.
Having done that, I found the total gold medals won by each country in each category and produced maps. Here are category A and category D and E, where the darker shade of blue shows the higher percentage of total gold medals. The left is the Olympics and the right the Paralympics.
These graphics are interesting, looking at category A which is just above, first you can see the distribution is very similar between the two event’s maps with the exception that some countries, in particular, more economically developed countries have a darker shade of blue in the Paralympics’ map meaning they have a higher gold medal success rate. In both events, the United States of America is far ahead as the most successful country.
The maps above represent category D and E sports (category E did not have enough events/gold medals to compare to category A), in the Olympics map it is not the United States of America that’s ahead of every other country as they are closely tied with multiple countries including Italy and Hungary. Generally, the map shows it is more evenly distributed across Europe and Asia. Comparing this to the Paralympics, a lot fewer countries have won a gold medal in these categories and the countries that dominate this set of events are Great Britain and France. So, the United States of America are not among the top which is rather strange but nevertheless interesting to see, it brings the idea of the United States of America paying more attention to the more popular sports, especially in the Paralympics. Thinking back to the country’s economic state, it is further supported with this map, almost all the countries there are more economically developed and/or have a large population. The patterns concerning categories suggest it is easier for countries to compete in lower categories sports and this is particularly the case in the Paralympics.
Please find the dashboard for this here.
Success
A further definition of success would be around efficiency and, in this case, could be viewed as entrants per medal and entrants per gold medal per country. This could show how much training a country has offered to their athletes to enable them to fulfil the country’s expectations.
Looking at the table above which shows the top 10 countries in entrants per medal, a table for the Olympics and the table below for the Paralympics. Starting with the Olympics and once again the United States of America is the current leader not just in entrants per medal but also entrants per gold medal, they are truly some way above other countries. The Soviet Union is first but does no longer exist as a country. Russia is just behind the United States, with China being an impressive (current) third. Romania and Hungary makes a surprise appearance and Great Britain was able to just sneak into the top 10.
In the Paralympics, it is Poland who is the current top as West Germany no longer exists, the United States are second but they do have a much larger sample size than Poland. China is third, however, there is speculation around widescale doping use so things may change in the future. Great Britain could be considered the top 3 due to the circumstances and that is with the largest scale outside the United States. These tables show that it is the more economically developed countries once again doing well in both Olympics and Paralympic. The difference seems to be that some countries are paying more attention to the Olympics and others show evidence that they treat both events equally. Germany is one of the countries that seem to be less interested in the Paralympics as they completely omit the Paralympics table. Italy is another country that was in the Olympics table but completely absent from the Paralympics.
Please find the dashboard for this is in this here.
Limitations
Through this research, I encountered certain limitations, first and most importantly is the data I have. This is largely referring back to where I had to change some sports athletes into a team to create a more accurate medal count. The team technique I used worked well but it is not perfect and there was no way for me to split up and identify what was a team event in some sports such as swimming or athletics. This meant my accuracy in medals and entrants number was not perfect but I felt they were accurate enough and I believe they will not significantly distort the results. A lack of financial data is an annoyance as it would have been really interesting to discover the funding of each country and sport as I think this is an extremely important factor for success. However, many countries keep their funding figures hidden from the public and with those which release information, there was not enough for me to create an accurate model to predict results based on a country’s funding.
The next step I would like to take is looking at gender. I was focusing on finding if there was any discrimination against disability and it is no secret that women have faced discrimination in the past (and still up to this day). It will be interesting to see how countries transform over time. Knowing now how much influence a country economic state has over the two sports events, I am intrigued to see how to add a country’s Human Development Index which is a measurement of how developed a country is. I feel this will be an important part of discovering the reasons behind countries Olympic and Paralympic success.
Conclusion
In conclusion. A lot of the results I gathered suggests countries economic state influences their performances in the Paralympics. This explains a lot as there are multiple factors of succeeding in the Paralympics. First and most importantly is the funding offered but this is true for Olympics and Paralympics, the most impactful difference is the medical facilities available in lesser economically developed countries is incomparable to richer countries. This means there are many disabled people having opportunities taken away and as a consequence limiting the country’s chances of succeeding in the Paralympics. Another reason which applies to all countries is the awareness and appreciation of disability. This is notably evident in poorer countries as generally, they have a less inclusive society. It was not until recently in 2012 and onwards that considerable action was taken to tackle conventional stereotypes and promote Paralympians as icons. In the very end, there are positive signs as more countries are becoming inclusive and improving their Paralympic performances through entrant numbers and then medal counts. The future is bright for Paralympic sport as it continues to grow.
This project was part of my data science training with Digital Futures. Digital Futures helps individuals from all backgrounds to kickstart their career in tech. If you like what we are doing, join us at digitalfutures.com.
