Project2

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2016 Rio de Janeiro Olympics Prediction
Kenneth Thieu -kthieu@ucsc.edu
CMPS161
Abstract
Total Medal Counts from past Summer Olympics demonstrate noticeable factors that
determine how many medals a country earns. In this paper, I will attempt to prove those
observations through data analysis of such factors; in the end, attempt to predict results of the
2016 Summer Olympics.
Introduction
Every time the Olympics occur, millions upon millions of people gather around to
support their home country in going for the gold. Earning medals during the Olympics is a sign
of superiority and fame. This can also refer to demonstrating the potential and capabilities of
each country to show to the world. Indeed, earning medals itself can in fact relate to economic
prosperity and stability.
Studies in the indicators of Olympic success show that a country's Gross Domestic
Product (GDP), GDP per Capita, Population, and Location are popular and logical in
determining how many medals a country earns. The more GDP a country has, the more it can
supply potential team members to represent; the larger the population, the bigger the pool of
potential team members to choose from. GDP per capita itself is popular in measuring a
country's standard of living. What is interesting among those indicators is home location; how
much does the location of the event itself play a role in a country's medal count? Amongst the
given indicators, I would like to focus on this specific one, and how it affects the host country
in terms of not only Olympic success but economic growth.
It is already determined that the host location of the 2016 Summer Olympics is set to
be in the city of Rio de Janeiro, located in the country of Brazil. Brazil itself, as shown by total
medal count of past Olympic events, doesn't significantly stand out amongst its competitors;
bringing less than 1/5 the amount of medals than the United States. To understand why, I
want to observe Brazil using the described indicators in order to make a hypothesis on its
Olympic success in 2016. In particular, I want to predict the economic effects on Brazil
because of the home location.
Related Works
Throughout articles I read, I discovered the described indicators as being prime factors,
backed by visualized evidence. What I seek in this project is the proof of such hypotheses
using my own visualizations.
Data for this project comes from The World Bank; the website itself has indicators used
to describe each country in many aspects. Using D3, I will represent the indicators of the 5
top countries ranked by Olympic success along with Brazil in a set of line charts.
Approach
For the approach, I created a line chart for each indicator per country I included. This is
a line chart to demonstrate the change over the years from 2004 to 2012. I also created a bar
chart for medal count per country. It is by studying the changes in the GDP, Population, GDP
per Capita indicators, as well as host location, over the years will solidify a positive correlation
towards medal count.
Results
First off, let's look at the medal counts of the past three Summer Olympics.
We can see that out of the 5 countries that tend to rank in the top in terms of medal
count, Brazil is insignificant. United States serves as the highest in terms of medal counts,
followed by China and Russia. What is interesting from this data set is the chance in medal
count between years per country. Recall in 2008 that the Olympic took place in Beijing of
China. As such, the amount of medals China won in 2008 is significantly higher than 2004
and 2008. The same can be observed for the United Kingdom; because the 2012 Olympics
took place in London, the medal count in 2012 for the country is shown to be higher than past
years. Based on this trend of home court advantage, it can be said that Brazil will follow suit
and end with a huge increase in total medal count in 2016. Aside from the location advantage,
I believe what influences the country's winnings is its economic change to accommodate for
the Olympics to be hosted. This can include preparation of stadiums, courts, training of team
members, advertisement and more. All of which can lead to the economic advancement of
the country, which in turn can potentially lead to more victories and a better standard of living
for the people.
We can't make real hypotheses on economic changes of a country just from medal
count alone; we need to observe it through the described indicators. First off, lets take a look
at the GDP per country from 2004-2012.
GDP data from the World Bank in measured in current US Dollars. GDP is, by
definition, a measure of the worth of final goods and services a country produces; GDP per
capita is a good indicator of a country's standard of living. We can see a trend of increasing
GDP throughout the years. Aside from improving economic conditions, it demonstrates how
much are countries producing for each other.
However, it seems to be difficult to notice the trend in GDP for countries that aren't
America or China; their total value in GDP hasn't significantly change in the time span of eight
years, let alone increase. The United Kingdom and Brazil are quite close in terms of GDP,
which is interesting considering the amount of medals the United Kingdom has over Brazil;
The same can be applied to the Russian Federation.
What is interesting to note is the change in GDP in 2008 and 2012 for China and the
United Kingdom. Recall that they were the host countries for the Summer Olympics
respectively. China has been constantly on the rise since whereas the United Kingdom hasn't
changed up to 2012. I believe that this economic change is not limited to Olympics alone but
to the change in Population in each country; China is on the rise in GDP with its population,
which is the highest out of all the countries in the world.
From the graph on Population, it is easily proven that the size of the country correlates
to its population; China on top followed by the United States. The United Kingdom is small
compared to Brazil yet its GDP is close to equivalent. The population of Brazil is significantly
greater than the United Kingdom as well. However, there could be correlation with GDP and
Population in terms of medal count. Looking at the chart, we can see that Germany is greater
than the United Kingdom in terms of GDP and Population, yet the later ends with more
medals. In 2008, the medal count for the United Kingdom was greater than Germany but was
less in 2004; in 2012, due to the host location trend, the United Kingdom ended with
significantly more medals than past years. This shows that, despite GDP and Population
being less, the host location indeed plays a strong role in Olympic success. This is a trend
that I believe Brazil will follow in 2016.
As stated before, GDP per capita is a good indicator of a country's standard of living.
"Per Capita" is a Latin phrase meaning "per head"; thus, it is comprised of a country's GDP
divided by its population. By looking at the chart, we can see where the United Kingdom and
Germany are compared to China. Due to China's overwhelming population, along with the
Communist style of living where everything is distributed equally, it would make sense that
China is the lowest. Germany and the United Kingdom are small countries compared to
China, as measured by their population. When analyzing medal count with this set of data, it
doesn't seem to be as effective as measuring GDP. The curve for the United Kingdom overall
decreases in the eight year span whereas countries like China and Germany have seen
positive changes. Even though the United Kingdom was the host country for the 2012
Olympics, its economic prosperity didn't significantly change, but its medal count did in a
positive sense. This shows that attempting to measure GDP based on population isn't a
strong indicator for Olympic success. However, between 2008 and 2012, there has been a
positive change for the United Kingdom. When looking at Brazil, we can see that the past
three indicators have seen a positive change in the time span; the amount of medals won has
increased as well.
Conclusion
Based on these data, I would like to confirm my hypothesis that a positive change in
these three indicators together indeed show a positive change in medal count. What really
stood out for me was what the indicators had for the Russian Federation. Russia is behind
only China and the United States in terms of medal count but its population and GDP are
below that of Brazil. This is what lead me to attempt to use GDP per capita; trying to measure
standard of living per country was positive to some extent because Russia ends up more
economically successful than Brazil. It still doesn't seem effective as Germany and the United
Kingdom have greater GDP and GDP per Capita despite winning less medals. This shows
there may be stronger indicators of Olympic Success other than the generally accepted
indicators of GDP and Population. I felt that home location is the 2nd strongest indicator of
Olympic Success, behind Population and above GDP. As shown, there has been an overall
increase in medal count for China and the United Kingdom during the years where the
Olympics were hosted in their respective countries.
Applying what I learned from analyzing these indicators, I feel that Brazil as a country
will benefit in terms of economic prosperity and medal count. The home court advantage in
2016 will demonstrate an increase in total medal count for Brazil, as well as positive changes
in not only its GDP but its GDP per capita. The processes to prepare the city for hosting the
games can effectively represent how strong and ready Brazil will be for the Olympics; it is
their turn to show the world that they are also capable of success not only in Olympics but in
the Economy. The overall economic standards of Brazil will positively change for the people
due to the Olympics, and may forever lead them to success in future Olympics following 2016.
References
Graettinger Dan, 2012. "Predicting the London Olympics Medal Count and the Why's
Behind It" http://www.discoverycorpsinc.com/predicting-the-olympic-medal-c/
The World Bank. http://data.worldbank.org/indicator
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