Sports Betting Strategies & Efficient Market Hypothesis PDF

Next week we're going to be looking at how to actually generate forecasts for match results in different sports and comparing the accuracy of our forecast with the bookmaker odds. So before we do that, it might be useful to say a little bit about how reliable bookmakers are in terms of their predict...

Next week we're going to be looking at how to actually generate forecasts for match results in different sports and comparing the accuracy of our forecast with the bookmaker odds. So before we do that, it might be useful to say a little bit about how reliable bookmakers are in terms of their predictions of outcomes, I'm think about what that says about an efficient market. So the very idea that you could build betting strategy, that would beat the bookmakers, contradicts something called the efficient market hypothesis, and there are many studies published in trying to test whether you can beat the bookmakers, whether you can defeat the efficient market hypothesis, whether that hypothesis really is correct. Probably the bad news is that the results are pretty mixed and generally suggests that the opportunities to beat the bookmakers are relatively few would fall between. Even if it's possible to beat them slightly, usually it's not easy to see a way to make a consistent profit. I say unfortunately because of course many people are attracted to the idea of forecasting by the idea of profitable betting strategies. If you think that the bookmakers odds are actually the true probabilities. If you saw they are accurately reflected the probabilities of the outcomes, then clearly wouldn't be possible to generate a profit, and when you take into a fact that there are taxes and the bookmakers making a profit, it's even more difficult to see how you could have a positive return and the most likely return is expected to be negative. For a profitable betting strategy to work then what we have to think is that the probabilities implied by the bookmakers odds are not the true probabilities and that the punter can identify those true probabilities for themselves and use them to generate a profitable strategy. The written notes to go alongside this videos would to actually work through a particular example of what a profitable strategy would be, what it would mean to have a profitable strategy in a bookmaking market. The efficient market hypothesis, as we apply to gambling, implies that it's not possible for punters to get an above average rate of return, and that's essentially because the bookmaker odds should already incorporate all of the relevant information that's available in the market, and so because they reflect all the information is available, they are the best measure of probabilities that we have. Now, this efficient markets hypothesis actually originated in the analysis of stock market returns. Indeed, many people think that they can buy stocks in such a way to beat the market, and most of the research on the efficient market hypothesis and the stock market has generally found that you can make a systematic return on the stock market. In that sense, stock markets are rather like betting markets, all of the information that's available is incorporated into the price to the values, the probabilities today, and therefore, it's not possible for anyone individual to systematically outperformed. You'd get lucky. Of course, you can get lucky and beat the market. That can happen, and in fact, you could be beat the market many times, it becomes less and less likely over time that you can do it consistently, but it's not beyond the bounds of probability that you could be successful for some period of time. But on average, over time, efficient market hypothesis says that it's not possible to beat the markets, and as it applied to the sports betting market, there's quite a lot of research which seems to broadly confirmed this conclusion. A betting strategy must be defined as a mechanism for betting overtime on different possible outcomes with a view to generating a profit. So what people usually do who tried to generate and test the efficient markets hypothesis in sports gambling, they actually try to generate a model which is calibrated using data from the past, and then they test this against the subset of the data which you haven't yet used and in order to see whether those forecasts are correct. So for example, one way to think about that would be you could calibrate a model of the probable results of in the Premier League based on the 2016-2017 season, and then you could use that model to predict the outcomes of the 2017-2018 season, and you could see how accurate those predictions were. That would be one way to figure out if your model was a good model or not. Now, many models rely on statistical methods, that's what we're going to do. We're going to use logic regressions, which we've talked about already in Week one, and we're going to use older logic regressions. But many people actually we'll just use expert judgment, which means that they will rely on their own intuition in order to try to beat the market, and many people believe that by using their intuition they could do that. Some people will actually even mix these two things up. They have a statistical model that they if you like, enhance with their expert judgment, and in some ways, those are often thought to be some of the best strategies. Some of the most successful strategies. Generally, strategies in bookmaking, in betting tend to be to try to identify situations where there is a large discrepancy between the bookmaker odds, and probabilities as you believe them to be based on your model, and that way you can make a lot of money from a single bet. The idea that you can make large amounts of money from making lots of small bets based on small differences is undermined by the problem of taxes and the bookmaker profit. You're losing as the more bets you lay, the more of those costs you're incurring. Bets placed on small differences are not likely to be that profitable over time. As I said, there's quite a lot of evidence of this and some of these theoretical strategies actually show positive returns, although many find that it's not possible. Even where it is possible to make a small return in theory, often it's very hard to turn this into a profit in practice. The other thing about this to bear in mind is that a strategy should really have a stopping point as well, you have to say when you've won enough in order to validate your strategy. The idea that you can go on winning forever is probably too much of a fantasy to be something you should really ever want to rely on. But there is the idea that you could win over a certain number of bets, and then once you think you made enough money then you can stop. Of course, the problem with that strategy is that most people don't want to stop, they want to carry on. Certainly if you gamble for fun, there's not much fun in giving up on a gambling forever just because you've succeeded in making a certain amount of money. I think it's always important to bear in mind, always come back to this point of what if you do bet on sports, why do you do it? Do you do for fun, which is perfectly reasonable or you tried to actually make money? What a lot of the evidence says is that if you're trying to make money it's liable to be quite a difficult role that you're trying to push your away alone. As I've mentioned it several times, the challenges involve the problem of beating the odds, given the existence of commissions and taxes. Bear in mind also that if you go into bookmakers, they have the right to refuse to accept bets. They do refuse fixed bets if they think that the punter is actually knows more than they do. Bookmakers keep an eye on who is making money and who is losing money. Again, it becomes very difficult even if you do hit upon some wonderfully profitable strategy, it's quite unlikely that you'll be able to pursue that consistently with many bookmakers, you'll find yourself getting effectively excluded from the market by the bookmakers. There's nothing illegal about them doing that, they're perfectly entitled to accept the bet if they think it's bad news for them. One thing that's found is that strategies that appear to work when you use historical data often turn out not to be very successful in practice. In conclusion, the evidence of the efficient markets hypothesis, although it's somewhat mix, generally it suggests that it's very hard to make money systematically from gambling on sports. Generally, the bookmaker odds may not be perfect. They may not actually incorporate all of the best information that's available, but they incorporate enough of that information to imply that making a profit on them by exploiting these differences is going to be difficult. There are few examples in practice of anybody being able to consistently making a profit against the bookmakers. But one thing that's useful for us is to think of the bookmaker odds is actually being a benchmarks. Rather than thinking that we're trying to beat the bookmakers, let's think about devising models which can just match the bookmakers. If we had a model which could just match the bookmaker odds, then in some sense, that model would be efficient. That would at least help us to understand what determines the outcomes of games and in some ways that's what we should really be aiming to do. We should be trying to find the best explanation that we can for variation of outcomes in the games and use that in order to inform, well, for coaches to have better plans for winning games, for us as commentators or analyst to explain to people what's going on, and just for our own satisfaction in order to understand sports better. Finally, just here are list of references if you're interested about efficient markets and sports, as I said, there's quite a lot been written. These papers are very technical in nature, but they are certainly something that as you become more familiar with sports analytics and sports betting markets, you might want to look at some of these and in order to get a better sense of what's really going on. That completes this week. Next week we're going to go on to, as I said at the beginning, we're going to go on to look at generating our own forecasts of game outcomes, and seeing how well those forecasts perform against the bookmakers odds, which we're going to take as our market efficient benchmark.