Computer System Makes Best Sports Bets

schliz writes to tell us that a new computer system using the "Logistic Regression Markov Chain" (LRMC) has proven to be the most efficient system at predicting sporting event outcomes. The system was tested on the 2008 US NCAA basketball season and picked all four of the finalists. "Similar to other rankings systems, LRMC uses the quality of each NCAA team's results and the strength of each team's schedule to rank teams. The method has been designed to use only basic scoreboard data, including which teams played, which team had home court advantage and the margin of victory."

Making sports bets

[Z00L00K]

Is always a question of statistics with a random noise involved.

The amount of noise involved strongly depends on which sport that is involved. Basket is a sport where a lot of points is scored, which in turn means that the noise is relatively low while football (what americans call soccer for some strange reason and what americans call football is more like rugby) has a lot of noise since the ability to score a goal there is depending a lot on luck.

This essentially means that counting points is a good way to score a basketball team while counting goals won't give much clue to how good a given football team is. You must look at other factors on a football team instead. And not all those factors can be as easily measured. Of course - the other factors are also important for a basket team. Other factors involved are the composition of players, individual player mood/health/inspiration, latest matches, history between the teams, referee behavior, weather, spectators, location, timezone etc. Add to this the element of randomness caused by the impact of the ball on a surface, player positions at certain points of the game etc.

Why not test it for the past 10 years?

[Anonymous Coward]

That was my first thought as well. The four #1 seeds are theoretically the most likely to be in the final four, assuming they were seeded correctly, but of course unexpected things usually happen in sports so this is the first time that's occurred. But if I had to bet my life on picking the final four, I'd probably pick the four #1 seeds in any given year because even though the odds of that occuring are low, the odds of me choosing which #2 or #4 seeds displace a couple #1s as usually happens so that I pick the correct four teams are probably lower!

I'd say if these guys think their computer system is so good at making bets, can't they plug in data for the past 10 years worth of NCAA tournaments and see how well it does there?

Or better yet, don't write an academic paper on it, put up their own money, win millions over the next few years beating Vegas, then tell us about it in a press release from the Carribean island they bought with their winnings! You have $50 million in winnings to back you up and I'm a lot more likely to believe you've made a major advance!

Best bet is not to bet...

[Bazman]

One of our research assistants started doing something like this about ten years ago, fitting a statistical model to previous soccer match results and the home/away effect. He rounded some of us up to chip in a few pounds each week and off he went to the bookies to bet on the outcome of his model.

Now, any statistical model (such as this LRMC thing, or the techniques m'colleague used) will only give estimates of the odds. It might say that the probability of team A winning is 0.6. Now, if the bookies are offering you a return of 0.7 then it's worth a bet. If the bookies rate it 50-50 then it's not worth a bet.

  The trouble is that any statistical model worth its salt is going to produce probabilities that add up to 1.0, whereas the bookies' odds can add up to 1.2 or so. That's how they play the game and make their profits.

  So after a season where we made a few pennies profit, and got some press interest (including a team from BBC Tomorrow's World filming us playing football), my friend realised the best thing to do was not to bet at all.

  And instead he went into the business of supplying odds to bookmakers. From where he now sits at the top of a rather large business empire!

  I might pop him an email to see what his current techniques are, but back in the day it was something similar to this LRMC thing.

I'm using it

[jedijacket]

I heard about this last year and used their picks for this year's bracket. I'm tied for first in my pool, and 93.5% nationally in espn's bracket game. Just for comparison of how good their choices are. They had 100% on the first round day one.

Re:Making sports bets

[drooling-dog]

Several years ago I was playing with some iterative and least squares approaches to predicting (American) football scores and rating teams. It worked pretty well, but one thing stood out: When you use only the scores from previous games and home/visiting status as inputs to the model, you hit a pretty hard floor of about 2 touchdowns (13 or 14 points) for your standard error. That error includes the "hidden variables" that you mention, as well as the fundamental randomness of the game.

It also implies that any statistical predictions you do are going to be off by 7 or more points 62% of the time, 14 or more about 32% of the time, and 28 or more about 5% of the time. That's worth considering when betting against a spread...