My journey applying AI to horse racing
towardsdatascience.com
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I had a friend who had a private box at a horse track. One of the benefits of this box was that you had a personal betting machine. This let you bet on the best odds just seconds before the race every time. I made a lot of money doing that.
You can kind of do it in Vegas too because the sports books aren't usually that busy.
In fact, that hardest part of this strategy is actually figuring out who the favorite is! The odds are usually listed as fractions, but they have different denominators, so you quickly have to convert them all the the LCD and then order them.
But yes, the closer you bet to post time, the better your outcome with this strategy will be.
I assume you are American as everyone in the UK has a personal betting machine and it’s in their pocket.
That said, the state's take-out is so high in most states that you need a massive edge to actually make money. The slight edge a private betting machine would bring probably isn't enough.
It must be crazy having the odds change on you after your bet.
Source: I worked on those APIs to integrate with 20+ exchanges over three companies and 10 years. The syndicates and HNWIs were always the same people over that decade.
Tabcorp is an Australian Wagering Company that offers real-time horse racing APIs: https://studio.tab.com.au/
Others are a little less public and you need to sign up with an account and prove you are a syndicate. Hong Kong Jockey Club, UniBet, Amtote.
I don't normally talk about this history as I was active in this industry until four years ago. There are however people who have come out in public:
Bill Benter: https://www.bloomberg.com/news/features/2018-05-03/the-gambl...
Jelko: https://www.smh.com.au/national/meet-the-joker-the-australia...
Most of the other families and players are extremely private or are of Eastern European I wont talk about them publicly.
This is a list of common bet types that are targets for these types of players: - Trifecta - Big Six - Quadrella - First 4
Here is a blog on working the combinations of the Big Six: https://practicalpunting.com.au/pp-online/a-z-of-betting/exo...
What are you up to now Shaun? Are you still in Hobart?
technologically the book is a couple of decades out of date, but it's probably worth a read.
Tabcorps TABStudio - http://studio.tab.com.au/ (You need to register as a tabcorp customer but it's "free"). Its basically a JSON REST API
NZ TAB have their batch mode, at filebet.tab.co.nz, which is nothing more than a file upload system.
The ATG, and the other Scandinavian totes provide coupon upload systems (where you generate a coupon file with your selections in it, using third party software), but if you win they will end up banning you.
Most providers keep their APIs hidden or require signing NDAs or other types of contracts, I'm referring to companies like Amtote, Churchill Downs, PMU, BetFred, PGI, LeTurf etc
Usually they're quite surprised when you contact them about doing "integration work", a lot of the APIs are designed for retailer shops to integrate with. For example, I've done some integration work with BetFred, where my client never wants to cancel a bet (placed at the last possible moment), however in order to pass their integration tests, I have to fully support cancelling a wager, just like any retail shop would.
On a side note, I have used (at least one of) the APIs shaunray was referring to that he had worked on.
https://www.smh.com.au/national/meet-the-joker-the-australia...
The goal is to find underpriced bets, where the collective estimate of the odds is far from the prediction systems's estimate.
Picking the favourite to win is a measure of how well the algorithm is at predicting the odds.
"In harness racing, you are playing against all the other players. You are not playing the house. The odds of any given horse winning is directly related to the amount of money on it."
He seems to be ignoring the overround which is effectively the house and then commission when you are banned and have to resort to the exchanges.
FWIIW the author is wrong that this problem is unstudied. There are actual hedge funds which do nothing but this and a quick google search provides numerous academic examples; even a github repo. "Deep learning" is probably the worst approach I can think of to the problem.
I'm also guessing he misunderstood the data if betting on the favorite compounds like that. If you make the race pay off at something other than the actual odds, that would probably do it.
Examples from the literature:
https://github.com/dominicplouffe/HorseRacingPrediction
https://www.sciencedirect.com/science/article/pii/S016792361...
Also. The simulated betting on on the favourite on those 26000 races was with one dollar per race. If the favourite win, the balance increases with 1$*the odds. If the favourite does not win, the balance decreases with 1$. Nothing strange about it, and as I tried to explained, no compounding involved. Flat betting. 1 $ per race. Anyway. It was simulated on historic data and also a side note as it didn’t really have anything to do with the project itself. Appreciate the comment.
I spent a few years in a hedge fund building algorithmic trading strategies, and whenever I saw a graph (we called them 'account curves') like that, it inevitably meant that there was a bug somewhere. Usually the strategy is somehow non-tradable, either because the market is closed or the system is borrowing data from the future.
The graph shows you making about $55,000 over 26,000 races (i.e. about a 100% return) with no big swings. If the effect was that big, wouldn't people know about it already? Despite the fact that you can't apply the strategy everywhere, couldn't you settle for making a little money at your local betting shop?
Your theory is that there are more informed bettors betting at the last minute. That suggests that the market odds spike towards the 'correct' odds as betting is about to close. If someone proposed your 'bet on the favourite' strategy to me, I would have asked to see evidence of that spike. Are you able to get access to real-time odds to test the theory?
Also, I dont suggest anyone go out and place real money on anything like this.
The main point of the article is that its not that hard to get the basics of machine learning and actually doing things with it.
Stated win rate betting on the post time favorite is 37%
This equates to a loss of 16,380 of original 26,000. Earnings must then come from the 9,620 bet on favorites that won.
Assuming the 55,000 is winnings (and not a total including original 9,620), this would equate to an average odds of better than 11/2. If reduced by the 9,620 then odds come down to a bit over 9/2
My experience in horse racing (regular and harness) is that odds on the favorite of 11/2 (or even 9/2) are extremely rare and certainly not the average. A realistic figure is 3/2 over the various field sizes (smaller fields tend to go close to even money, larger to 2/1 or so).
So yeah, the data as presented appear flawed.
Like the guy beneath me: I've seen those curves before -they're always a mistake.
The odds reflect the horse's supposed chance of winning or placing (or whatever else it takes to get a payout), not its expected position -- so this isn't a case where you can be aware that the horse is underrated, but have no way to make a +EV bet on that knowledge.
The first order of business in these things is certainly to spot the overlay/value pick/+EV situation. The second order of business is to manage bankroll/vol to be able to realize the EV over time -- but that is generally speaking much easier and more mechanical than the core insight of (repeatably) finding the EV...
Isn't this a misstatement in the other direction? Favourites can be underrated too.
They're probably not, or at least not enough for you to beat the house cut, but that's true of every bet -- they're all likely to be net losers unless you have special information, or a special way of using it.
The thing that makes it easy to simulate but impractical to execute is that getting enough bets in fast enough and late enough to tip the odds to your favor to give you an edge while limiting losses is difficult to do. It's even harder to do without this wagering itself affecting the odds. For one there often just isn't enough money wagered on a race. In the heyday of the HK races you'd often have 100 million+ HKD wagered on every single race, much of that coming from the general population -- individuals going to the track. There are only a few big event races in the US or Europe that will attract that kind of betting pool. Even HK is no longer like that.
https://www.bloomberg.com/news/features/2018-05-03/the-gambl...
using the same dataset as betters with a NN is not really better than running a regression on it, so this doesn't really surprise me.
nn are able to find patterns with things others than historical series. taking this forward would need to combine historical race sets external sources that could have correlated information available that's not easy to extract by simple regression, like news and articles whenever available or meteorological data or whatever, just feed it everything and let the nn sort itself the useless data out
Simulated flat betting 1$ on 26 000 races over 15 years shows a hefty return on investment
If this is true, why don’t we all just go and hire people in Sweden to put in bets for us at the last minute, based on the favorite horse, and pay them out of the profits? We pay them to do it and we collect the winnings.
If this strategy works it may work elsewhere too. Why not just do that all day long with an army of people? And you aren’t hurting who is the favorite either.
the take away of the story was that the method was probably known by crime syndicates and used for money laundering, as they have cheap pseudo-slave labour available. but if you're a well educated person with a fulfulling job, you'd go insane soon (and of course, job security - the second the company changes their system you're out).
so with betting, you'd have to invest a lot of time and energy for it to become profitable. as he wrote, you'd have to be at the race tracks and wait until the last possible moment, then driving to the next stadium. and if it was _that_ easy to create a real winning system that depended on local help, the swedes would do it themselves - so your hired goons might stay as long as they needed to understand your system and then continue on their own (lowering your margins in the process).
if the process could be completely automated, i.e. with online betting, the story might be different. but i'm sure there are already a lot of syndicates looking into that (even the analog version). for them it doesn't even have to be profitable. 80% return is good enough for money laundering and they can out-finance the legal competition.
> His next thought was utterly predictable: "I remember thinking, I'm gonna be rich! I'm gonna plunder the lottery!" he says. However, these grandiose dreams soon gave way to more practical concerns. "Once I worked out how much money I could make if this was my full-time job, I got a lot less excited," Srivastava says. "I'd have to travel from store to store and spend 45 seconds cracking each card. I estimated that I could expect to make about $600 a day. That's not bad. But to be honest, I make more as a consultant, and I find consulting to be a lot more interesting than scratch lottery tickets."[1]
I simulated this myself on the HK tracks: if you bet randomly _and_ don't ignore track take, your expected return on the long run is precisely $BET - $TRACK_TAKE, which was about 80% in HK. ie: you lose 20% of your money on average on each bet.
Anyone who is telling you they have cracked the parimutuel pools, and "here's how to do it", is trying to sell you something else. Anyone who has actually cracked the parimutuel pools knows how they work, and that if you share your "tips", or selections, you only serve to diminish your own returns, so you are not going to do it.
I'd rather bet on Professional Wrastling than harness racing.