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General Betting
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26 Mar 11
14:31
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Date Joined:
04 Apr 03
Simplified but a question about probability. Approaching things generally.
A team plays 5 matches, losing the 1st match and winning 4 in a row.
In simple teams, the team wins 80% of its matches (4 for 5)
It wins the 6th match.
Now, based on readings from:
1 to 5, the team will win 80% of its matches
from 2 to 6, the team will win 100% of its matches
1 to 5 says that with the 6th match being a win, the team will win 3 of the next 4 matches
2 to 6 reading says it will win 5 out of 5 starting at match 7.
Based on this premise (I will add to the scenario after):
What is the probability of winning the 7th match?
My first impression is 87.5% since the team is showing "improvement".
As mentioned, give your views on the above premise then build from there.
A team plays 5 matches, losing the 1st match and winning 4 in a row.
In simple teams, the team wins 80% of its matches (4 for 5)
It wins the 6th match.
Now, based on readings from:
1 to 5, the team will win 80% of its matches
from 2 to 6, the team will win 100% of its matches
1 to 5 says that with the 6th match being a win, the team will win 3 of the next 4 matches
2 to 6 reading says it will win 5 out of 5 starting at match 7.
Based on this premise (I will add to the scenario after):
What is the probability of winning the 7th match?
My first impression is 87.5% since the team is showing "improvement".
As mentioned, give your views on the above premise then build from there.
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Replies: 12
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I'm not really sure what you're getting at here, but I'll lay you 1.15 all day.
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You seem to be making the arbitrary value of '5' historical matches as the point at which to start taking a rolling window of probability? If you just did this with '6', you'd get a different number. Why not 6? Because you've 5 fingers?
(that's the reason we count in 10s btw). A more realistic approach might be a weighted system with each historical match given a lesser weighting going back in time. I'm sure some people have thought of this, not sure if that's a mathematically defined probability method though. |
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that's the reason we count in 10s btw
Speak for yourself. I count hexadecimally. |
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That's only because you have 5 nipples, a medallion, and wear an open necked shirt
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SHAPESHIFTER, is this one of those ''I know the answer, are you as clever as me questions '' ?
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To my mind the question cannot be accurately answered due to lack information about the terms of each previous match.
However, an inaccurate answer ( ) by converting Win and Lose into a 3 points, Zero points form would be 65.85%. |
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This isn't a question of probability :)
At its simplest the team has won 5 of 6 matches, suggesting one estimate for the 'true' probability is 83.33%. But of course this assumes all opponents are equal measure, and is a very small sample. Let's just pretend all opponents were the same, what's the confidence interval around our estimate of the true value of the probability they win any given match? Well, roughly speaking a 90% confidence interval here is 0.607 to 0.937. So that gives you an indication of the spread. So lay as if they have a 94% chance and back as if they have a 61% chance, otherwise you may find yourself without value. This of course makes many assumptions that are unlikely to hold in the real-world, however it shows the danger of small sample sizes, and why betting based on arbitrary statistics can be very poor indeed. |
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I'm tempted to jump in front of Bayes with a 1.16 lay....
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maximum, could you repeat that ?
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That's an extreme example Maximum, though correct of course..
The probablity of winning the 7th match - or any match - depnds upon the difference in abilty between the teams. The most difficult of the 6 games may have been Wolves at Home ,game 7 might be Barcelona Away. If we assume that the fixtures are of comparable difficulty then it is interesting as there has been a study - by Kevin Pullein no less  - of these kind of sequences . Pullein looked at teams that had won 4 in a row (and lost 4 in a row) to see how often they won/lost the following fixture. He found that they were only very marginally more likely to win/lose the next match in the sequence than at any other time in the season. It was certainly nowhere near the difference between 80% and 87.5% . Pullein's conculsion was that basically that if Team A was 2.0 at Home to Team B at the beginning of a month, then met them again 1 month later having won 4 in a row since, they should * only be fractionally shorter than 2.0 .And if they met again a month on with Team A now on a 4 match losing run, they should only be fractionally bigger than 2.0. *assuming the players/manaers were much the same. I can't recall the precise details, so am paraphrasing a bit there, but the article was in KP's Racing Post Column areound Oct/Nov 2007. |
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Sorry, I have tried to post a few times but firefox and betfair not friendly these days.
kenilworth, have a view but not "the answer" (Only Brian Cox seems to be close to the 'answers' these days  ).As mentioned, starting with a basic view. Thus, the "number of matches" is put at five (every sport is different. For example, I put NHL over 8 which is two weeks, baseball 10 which covers three series/teams). As for the weighting: I'm actually working on something similar to the Pythagorean expectation over a number of matches to set a foundation of form. The teams are then compared in their probability to win. So you could end up with TEAM HOME with 85% and TEAM AWAY with 65%. As mentioned, it needs to be established on how a team arrived at this percentage. This comes down to the "cross section of games". That's where I think the rolling can come in. If you have a rolling (using 5 for now): 1-5 2-6 3-7 4-8 5-9 For the tenth game, you actually have the weighting of 8 matches. So a winning streak of the first 5 would still have a bit of bearing on the % established for the 10th. From there, the formula of value has to be brought into the equation |
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Of course Tobermory has the right answer (as usual),
such a boring old fart he is at times. |