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How R is changing the sports betting world
Sports betting & R: How R is changing the sports betting world Marco Blume UseR_2017
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Who is Website Screenshot Use the R font in an image
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The largest sportsbook you’ve never heard of
Unique model that relies heavily on data science Integration with risk modelling Website Screenshot Use the R font in an image
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Why are we at UseR_2017? Sports betting is a perfect R problem
Website Screenshot Use the R font in an image
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How do you think bookmakers work?
Recreational bettors Betting both sides / Risk free High margins Easy money Hyper-competitive bots, models & pros High frequency trading algorithms Low margins Complex modelling & data science
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What Differentiates Pinnacle?
Standard Business Model Ban (or limit) winning customers Only accept recreational bettors Marketing (and brand) focus High cost of placing bet Pinnacle Business Model Accepts professionals We lose to pros “Paying for” proprietary info Machine Learning, Data Science The lowest margins (circa. 1.5%)
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Where R fits in our trading model
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Problem Solving – The example of live betting
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US Elections 2016 Betting Market
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US Elections 2016 Betting Market – Election Night
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Sharing our love of R with our customers
Pinnacle.API (CRAN) Get real-time odds from Pinnacle into data frame Place real wagers Few lines of code Odds.Converter (CRAN) Convert between different odds types and probabilities American odds, Decimal, Malay, Hong Kong, Indonesian, Probability
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Introducing Package image
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Introducing Pinnacle.Data
Historical odds from MLB & US Elections (2016) Complimentary with other baseball datasets e.g Lahman & Baseball-reference Fun dataset to use for examples / learning More data to come Package image
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We’re excited to see what the community comes up with
Pinnacle.Data – What can you discover? Find new relationships between key events & the odds Build your own profitable betting model We’re excited to see what the community comes up with Package image
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