"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."
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.
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.