Can an artificial neural network predict the outcome of sports games?

Question

I was trying to find something original and fun to do with artificial neural networks (ANNs) as a personal/learning project and I though it would be cool if I could predict the results of sports games (especially NHL games).

I'm pretty sure it would be easy to evolve an ANN that can predict which team is most likely to win (usually the team with the better record). However, what I would like to do is create an ANN that would tell how likely the outcome is, similar to bookmaker odds.

Is this something an ANN can do? In the affirmative, what kind of success can I expect? I know I can't beat the bookmaker (at least not with a software solution). I want do this as a recreational project/challenge to myself. I don't expect to bet money on sports games with this project.

Answer 1

ANNs are really good at pattern matching and prediction, so yes, odds are you could build an ANN that does what you want.

You'll need more than just team win/loss ratio to make it really effective however. Feed it stats for the players, too. For real effectiveness, try to include game-flow information... like which players are on the line for each play (for football, for example).

Ultimately, the biggest problem you'll run into (aside from the whole "writing the ANN" issue) is getting the data you need to feed it.

Answer 2

Way back in the days of the IBM XT I played with a shareware ANN program to try and improve my chances on the British football (soccer) pools. This is a form of betting where you try and predict which football matches will result in draws. I assigned each team a number then looked back thorough past results and from them generated a single digit for the result. From memory it was 0 from a home win , 1 for an away win and 2 for a draw. Each result went on a single line in a training file. I would then run the training file through the program and generate the ANN settings. I would then look up the following Saturdays matches and feed them into the ANN then look for matches predicted as draws.

As the weeks went on my predictions of draws did definetly become more and more accurate. However ...

1) The XT was so slow that by Christmas it was taking 24 hours to generate the ANN settings from the training data. I really had better things to do with my precious (and expensive) PC.

2) Although it was better at predicting draws it wasn't predicting enough to actually win any money. Looking back I suppose the program had just worked out that Manchester United would always beat Sheffield United. This was more football knowledge than I had but not enough to win any money.

3) Entering the results into the training data and then generating the forthcoming matches data was taking me ages and to be honest sport bores me rigid.

So I gave up and didn't become a millionaire.

These days however PC's are much faster and much of the training data could be scraped from the web. But I still doubt it is a route to a fortune but its certainly an interesting project.

Ian

Answer 3

I think it's indeed all about data, but there's no end to what you could feed it with in order to be more accurate : winning/loosing streaks, players biorhythms, player's girlfriends mood before the game, minor/major injuries they suffered in the recent past, extra-sportive events that are bothering the players, etc, etc, etc.

But I don't think you can accurately predict which team is more likely to win, it would be just a more-or-less educated guess.

Answer 4

I've done some stock market predictions with an AI and my conclusion is that it is not very hard to make an AI that gets good results with the historical data. Making winning transactions in the future is a different ballgame.

Answer 5

My belief is that the unpredictability of an event is due to lack of information and understanding...If you have all the knowledge, then yes it could be done. Or, the more knowledge you have, the better it can be done.

So in theory, the answer is yes.

However, in practice, you can get a PhD and have a whole career working on this question and you still may not succeed.