Bill Benter is arguably the most successful sports bettor of all time. Its estimated he made close to Billion betting on horses in Hong Kong. His story is well documented, but the models he used and the reasons for his success are often overlooked. In this video I break down the circumstances that made his his model profitable and the specifics of the exact machine learning model that he used. At the end I also analyze the feasibility of creating another model like this in 2022.
0:00 Intro
0:41 Who is Bill Benter?
1:22 Lesson 1: The Law of Large Numbers
2:30 Blackjack to Horse Racing
2:50 Bankroll Management
4:07 How did His Billon Dollar Model Work?
4:57 Secret Sauce
6:00 Improving the Billon Dollar Model
6:35 $ $ $ $ $ $
7:12 The Million Dollar Ticket
8:05 Could you replicate this?
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Articles Referenced:
– https://www.gwern.net/docs/statistics/decision/1994-benter.pdf
– https://www.tepinvestments.com/blog/beating-the-risk-of-ruin-mr-bill-benter-horse-racing-and-the-kelly-criterion
– https://en.wikipedia.org/wiki/Kelly_criterion
– https://www.youtube.com/watch?v=4B0mGYZqElo&ab_channel=BloombergQuicktake
– https://www.wired.com/2002/03/betting/
– https://www.wired.com/2002/03/betting/
– https://www.marca.com/en/lifestyle/2021/01/02/5ff0d37446163fb99b8b458c.html
– https://www.bloomberg.com/news/features/2018-05-03/the-gambler-who-cracked-the-horse-racing-code
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Thanks for watching everyone! Do you like data science related stories like this? Let me know other ones you would like me to deep dive into in the comments below!
one very important aspect that he acknowledges at the outset is that Happy Valley is a 'closed system' , meaning horses arrive on the island and stayed for the whole season (which was not that long, and they did not have races every night). This certainly would have allowed him to better establish an accurate hierarchy (ie horse A has placed higher than horse B every time) compared to the typical scenario of horses coming in, racing, and then off to another track (as happens in the US and UK). Regarding suitability to today, you forget that the UK has Exchanges which operate differently than the Tote system Benter had to bet under. The HK Jockey Club took out 18% off the top, and Benter still overcame that 'hole' and walked away a rich man. The UK exchanges take out 1% plus a commission of 3-5% depending on who you bet with. A much shallower hole to deal with.
Thanks Ken, very good video
The entry to Machine Learning and sports betting can be steep if you are not a coder, here is an easier way to gain an ML approach to sports betting https://youtu.be/PzdcwGLDifk
great content!
saudações from brazil o/
This is awesome. Honestly, I've always wanted to try sports betting lol (but to anyone reading, I didn't say that :P)
Ken, have you ever attended the Sloan Analytics Conference in Boston? A professional bettor that appeared on the “Betting With an Edge.” Podcast and YouTube channel mentioned it. He indicated it was a conference for the analytics folks from the American pro sports leagues.
I'm sorry and I don't mean to be rude or distract from your message because I truly respect and admire what do. But I've been a follower of yours for a while now, and I think you're really hot. ❤
A quick note on Correlated/Colinear Features. These can be a huge pain for applications such as Sports Betting, where we are weighing certain factors relative to other factors. Concepts such as introducing dropout, random noise, and using clustering to engineer/select features might be helpful. Doing that would reduce the costs of running a model, improving ROIs even if drops absolute performance
Thanks Ken, this is superb story to share it my brother to introduce him to applications of ML in real world before data chaos
This is so. freaking. sick. Awesome vid as always my guy!
Love this!
Great video Ken. I want to ask you for an opinion. I started an internship in a data virtualization project, but my goal Is to work as a data scientist or data analyst. What you think about It? Is It good starting point to enter in this area?
Very cool video. Enjoyed the video thoroughly
Bookies have full DS teams these days…
Hey ken, Can you check the 2nd example of Kelly criterion. It looks like, you have mistakenly put 1 in down. I am really getting confused when doing this math. Please, help..
So much big brain talk, finance is one of the sector I really want to excel in professionaly and personally, nonetheless great video!
man people back in the days are amazing. how do they even collect data back then? all on paper?
Ken, we need to make a ML model to predict Papaya futures!!
#PapaysIncToTheMoon 🍈🚀
Mom, I'm not a degenerate gambler who had to move back home because I lost all my money, I'm a data scientist!