IntroductionForecasting the winners

What if countries merged?Conclusion

Predicting the Olympics Winners

Nicolas Hanss, Alexandre Lauga

ENAC

April 23, 2018

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IntroductionForecasting the winners

What if countries merged?Conclusion

Sommaire

1 Introduction

2 Forecasting the winners

3 What if countries merged?

4 Conclusion

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IntroductionForecasting the winners

What if countries merged?Conclusion

Overview

1 Introduction

2 Forecasting the winnersWho would have won the Rio Olympics according to ourmodel?What about Pyeongchang?Limits of our modelBetter model without outliers ?

3 What if countries merged?France and Great BritainKyrgyzstan-India-Mongolia

4 Conclusion

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IntroductionForecasting the winners

What if countries merged?Conclusion

Sample

Sample Collection

n=181 countriesThroughout the Rio and Sotchi Olympics.

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IntroductionForecasting the winners

What if countries merged?Conclusion

Sample Variables

Variables

Population

HDI

Mean years of schooling

Internet penetration

Unemployment rate

Income

Phone

Only for the winter Olympics:

Minimum monthly temperature

Maximum altitude

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IntroductionForecasting the winners

What if countries merged?Conclusion

Capturing Human Development

HDI Definition

HDI computed with:

Life expectancy

Mean years of schooling

Gross National Income

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IntroductionForecasting the winners

What if countries merged?Conclusion

Medal count

Medal count

9 points for Gold

3 points for Silver

1 point for Bronze

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Sommaire

1 Introduction

2 Forecasting the winnersWho would have won the Rio Olympics according to ourmodel?What about Pyeongchang?Limits of our modelBetter model without outliers ?

3 What if countries merged?

4 Conclusion

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Analysis of the variables

Figure: Population (in millions) 9 / 29

IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Analysis of the variables

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Analysis of the variables

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Summer Olympics Explanatory Variables

Explanatory Variables Expectations Model

POP + +POP2 + -100*(HDI> 0.85) + +SCHOOL + +INTERNET + insignificant

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IntroductionForecasting the winners

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Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Regression model and coefficients

Variables Model

C -38.35POP 0.97***POP2 -0.0008***100*HDI> 0.85 0.36***INTERNET -0.078SCHOOL 4.84**

R squared 0.415F-stat 24.92Prob. 0.00

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Regression Output

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Summer Olympics Winners

Figure: Expectation Figure: Reality

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

What about the winter Olympics?

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Analysis of the new variable

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IntroductionForecasting the winners

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Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Winter Olympics Explanatory Variables

Explanatory Variables Expectations Model

POP + +++POP2 + -100*(HDI> 0.85) +++ +PHONE + insignificantUNEMPLOYMENT - insignificantTEMP - insignificantHMAX + insignificantTEMP*(-HMAX) + +

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Regression

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Figure: Expectation Figure: Reality

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Failure of the classical assumptions

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What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Figure: Correlation matrix

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IntroductionForecasting the winners

What if countries merged?Conclusion

Who would have won the Rio Olympics according to our model?What about Pyeongchang?Limits of our modelBetter model without outliers ?

Without outliers

Figure: Model without outliers

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France and Great BritainKyrgyzstan-India-Mongolia

Sommaire

1 Introduction

2 Forecasting the winners

3 What if countries merged?France and Great BritainKyrgyzstan-India-Mongolia

4 Conclusion

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IntroductionForecasting the winners

What if countries merged?Conclusion

France and Great BritainKyrgyzstan-India-Mongolia

France & Great Britain

France

POP=40.2

HDI=0.9

HMAX=4810

TEMP=3.9

Great Britain

POP=41.7

HDI=0.91

HMAX=1340

TEMP=2.8Figure: If France and Great Britain merged

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IntroductionForecasting the winners

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France and Great BritainKyrgyzstan-India-Mongolia

Would merged countries with 0 point score?

Mongolia

POP=2

HDI=0.74

HMAX=4374

TEMP=-18

IndiaPOP=860

HDI=0.62

HMAX=8850

TEMP=17.5

Kyrgyzstan

POP=3.8

HDI=0.66

HMAX=7439

TEMP=-12.7

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IntroductionForecasting the winners

What if countries merged?Conclusion

Sommaire

1 Introduction

2 Forecasting the winners

3 What if countries merged?

4 Conclusion

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IntroductionForecasting the winners

What if countries merged?Conclusion

Conclusion

Model predictions close to reality

But limits to our model

A few variables preponderant compared to the others

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IntroductionForecasting the winners

What if countries merged?Conclusion

How to improve our model

Look more in details at each discipline

More specific data for each country : measure how they assignimportance to different sports

Expand the data with previous Olympics −→ time series data→ Take into account the host effect

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