Is there any possibility of unwinding the distortion caused by site fees, time-value issues, and other market imperfections to recover the true odds implied by the betting markets, or is it just too complicated for that to be feasible?
It should be possible to turn an odds bet into an even-money bet with some financial engineering. Like "I predict that either we will have talking horses, or the last two digits in the Dow will be between 0 and 45." Probably there's a way to do it with cryptography too.
This only solves one of the issues you identify. But I've always seen LB as a publicity gimmick rather than a serious marketplace.
You can find two bookies with different odds, such that the expected value would be in your favor. I however did work for a company combating this,by alerting the bookies about such opportunities so that they adjusted their odds.
I think betting markets are prone to wishful thinking; there's no guarantee that errors of reasoning toward one side or the other will cancel out, since it's perfectly reasonable to imagine that errors in one direction are more common.
The other issue is the problem of successive gains being wiped out by a bookmaker reneging on the quoted odds; most bookies have a "palpable error" clause which allows them to void bets on inappropriate odds, at their own discretion
Differences between bookmakers' rules in some markets regarding refunds for cancelled games, retirements, ties etc. can also leave you losing both sides of a bet in some instances.
Human judgement is still better than algorithms at judging the risk of the above happening.
Just a second though, betting markets are intrinsically subject to manipulation! Both in the markets themselves and in the world that the gamblers are purportedly "observing". The betters have active agency in the world they are betting on. The only thing stopping people who participate in these "markets" from manipulating outcomes in unethical, coercive ways is: nothing at all. The betting markets only serve to raise the stakes and create a medium for perverse incentives to play out. So yeah, in some cases or might be more "accurate", but what about the risks? At what cost?
Echoing another comment, one huge problem with the current sports betting market is banning/limiting winners.
I started prop-odds.com to help the more mathematically inclined gamblers take advantage of mispriced odds or let them build and backtest their own models. So while it's actually not too difficult to beat the book, the challenge comes from evading their detection and getting banned.
I wrote a program to calculate my kelly stakes based on supposed 'true' odds (ie no bookie overround) on English football matches. Maybe it would have worked out in the long run but I gave up owing to the effect it was having on my bank. I got my true odds from the Fink Tank column in the Saturday edition of The Times and bet on betfair for convenience and the ability to lay as well as back. I have no doubt that if your true odds are accruate it would maximise your returns. The hard part of course is estimating odds
I'm not sure this still holds true with the advent of betting exchanges. The market is now pretty efficient. Sure, there's still value to be exploited if you're good enough. However, in general the wisdom of the crowd is quite close to the true odds, at least at the short end of the market.
"In terms of the Sobel and Raines model, a lower conventional bias in the exchanges relative to traditional betting markets is consistent with a higher proportion of ‘serious’ bettors on the exchanges than with bookmakers"
I am curious if the technique described in this paper (http://www.cam.cornell.edu/~sharad/papers/searchpreds.pdf) would give an advantage over the long run. I would imagine that if the majority of bets are placed for entertainment value based on guesses, this could be a quick way to rake in some dough.
> A strategy intended to beat the bookmakers at predicting the outcome of sports games requires a more accurate model than the ones bookmakers have developed over many years of data collection and analysis.
I disagree with this assumption and I think they have painted themselves into a corner because of it. To illustrate, imagine charting win rates against bins of price-implied-chances. $3 horses win roughly 33% of the time, $4 horses 25% for example. It resembles a noisy 1:1 linear relationship. Do the same for your selections and your line will be noisier, but crucially you're not taking bets where the price is worse than your estimate. This can leave a window of profitibility when you subtract the two, even when you are less 'accurate' as measured by win rate or KLD or other measures.
The goal is profitibility, not accuracy. The problem with including the odds you are betting against as a feature for your ensemble is that it dampens that window. If you're right about your selections, you'll bet less and win less. * If you're concerned about the volitility that comes with being less accurate, there are better ways to address that.
I've been doing this for a couple of years and in many ways it's a dream side-project. Location independent, no customers, automatable, and in some jurisdictions tax-free. It can be a little lonely at times though. I would love to chat with anyone else applying tech/math to beat the bookies. Sorry for the throwaway, I'll put a contact in my profile.
In college I did extensive research on this amongst Bodog, 5dimes, and another third party vendor considered 'reliable'. I'd scrape sites hourly because lines move like any market will, and I did this for all 17 weeks. I don't think there was one instance where there was an arbitrage opportunity (my algorithm would go 4 game-pairs deep, so it wasn't an exhaustive analysis but rigorous enough). Even if theres large disparity between bookies, the fact that the industry accepts -115/100 as fair would require a huge mispricing by a bookie for you to arbitrage successfully.
The most interesting thing was left out: how did they find this data? Both historical and realtime is pretty hard to find. Ten years of odds from a dozen bookies looks like a massive task.
Next: how do you mask this behavior to not be obvious. Once you have a betting stratetgy the real difficulty is turning it into one that isn't obvious.
Yep. "Assuming the initial odds are right, these guys may have cheated". That's one hell of an assumption. The odds moving is one of the strongest indicators of the initial odds not being right. Market efficiency etc.
I ran a project in this area for a few years, and saw significant issues. For example, for high-stakes predictions (eg elections) we saw significant gaming because people see it as an opportunity to move the media narrative.
We've seen this in the current US Presidential Elections, with big swings in betting markets for the presidential outcome itself, without the same swings in related outcomes (eg, you see a swing in the price for "the winning president is X" without the price for "X gets above 270 electoral votes changing at all")
Obviously this creates arbitrage opportunities, but the media narrative is the real issue. Have you considered this problem at all?
what do you think the bookmakers are using to set the odds?
If you don't have a PHD level and a large amount of money to start with, don't even try to think about it.
I've spent a few months tinkering with this kind of stuff, with a huuuge dataset, my simulations never went past the annual return of an average ETF, and by eliminating 99/99.5% of bets possible, so you'd only have a few bets that are worth it per month, a bad streak would ruin your return for the year, and you'd have to have access to a lot of bookmakers to get the best odds.
It becomes a vicious circle because the only way to be more certain about the odds is to place your bets as late as possible. Which means that fewer and fewer bets are struck earlier on, making the 'current' odds even more inaccurate. Which motivates people to wait even longer before betting...
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