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Introduction to the data
analysis using python
Akira Nonaka
XOXZO
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#FJOUFSBDUJWF
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Who am I ?
• XOXZO Evangelist
• A Flying Python Programmer
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About XOXZO
• Provide SMS, Telephony API
• No office
• Everybody works remotely
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Ten people
Six countries
Nine cities
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Outline
1. Tools
2. Domain knowledge
3. Value of data analysis
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5PPMT
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Tools
• Python
• numpy
• pandas
• matplotlib
• Jupyter notebook
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Why horse racing data?
• Over 30 years official data.
• Clean data. No need for scraping.
• Some chances of making money?
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Let’s take a look at running speed
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Speed
• Faster horse wins the race
• Distance and Time
• Regression analysis (linear model)
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• Horses run about 60km/h.
• I want to compare the speed of
horse A runs 1km and horse B runs
2km
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Is the relationship linear?
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Hypothesis
• They must get tired if run long distance.
• Regression analysis with quadratic model.
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quadratic coefficient is negative
convex upwards
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Check other years
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Expert advice
• Every racecourse has different shape, straight
line length and corner radius, etc.
• It is not right to compare the data of various
racecourses together.
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Analysis by racecourse
First off from Tokyo Racecourse
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Convex shape
2014 2015
Convex
downward
11 14
Convex upward 8 5
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Tokyo Racecourse
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Kyoto Racecourse
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Hanshin Racecourse
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Nakayama Racecourse
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It is almost meaningless to compare the
speed if the racecourse/distance is
different
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Lessons learned
•Fatigue is not significant factor in
horse racing.
•Knowing the target domain is very
important.
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ROI
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JRA
Pay back
Japanese horse racing system
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Human predictions are
reasonably accurate
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Win Fav Win Rate
1 32.69
2 18.85
3 13.22
4 9.41
5 7.08
6 5.45
7 3.93
8 2.86
9 2.12
10 1.45
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*O/PSUI"NFSJDB
Public betting favorites win approximately 33 percent of all
races and finish second 53 percent of the time. Second choices
win approximately 21 percent of all races and finish second 42
percent of the time. So the top two choices win 54 percent of
the races and finish second 74 percent of the time. You might
even want to consider the fact that third choices win
approximately 14 percent of all races run over the course of a
year.
http://www.predictem.com/horse/profit.php
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Strategy
• We humans sometime put too much emphasis
on certain factors and ignore others.
• That is where data analysis can make a
difference.
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Strategy X
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Accumulated
Payback
Sequence of tickets bought from Jan.1 - Dec. 31
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Lessons learned
•Find under evaluated horses.
•Win rate of strategy X is 8.8%.
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Next Goal
• Use machine learning to tune parameters of
strategy X
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