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For the NFL, I found that a coefficient of 15% generated the most accurate prediction of the coming week’s spreads.
#Power rankings sports calculator trial
I then determined what that credibility coefficient was by trial and error optimization. Revised “best estimate” spread = original spread + (credibility coefficient) x (deviation from expected) I assumed that the betting market would recallibrate itself according to the following formula:
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One would expect that the market would factor that result into future estimates of both New England’s and New York’s strength. So, the outcome of the game deviated from the market’s expectation by 13.5 points. However, the Giants ended up winning by 4 in that game. For example, in week 9 of the 2011 NFL season, New England was favored by 9.5 points over the New York Giants. How the Betting Market Reacts to Game Results (Gamblers are Bayesians)Īlthough the approach above generates a set of rankings, it ignores some potentially useful information that could be used to better match the coming week’s point spreads. Weight = 1 / (games ago + 0.5), so the most recent game gets a weight of 2, the prior game a weight of 2/3, etc.Weight = 1 / (days ago + 1), so today's game gets a weight of 1, yesterday's game a weight of 0.5, etc.Weight = 1 / (games ago + 1.5), so the most recent game gets a weight of 2/3, the prior game a weight of 2/5, etc.Weight = 1 / (weeks ago + 0.2), so current week gets a weight of 5, prior week a weight of 0.83, etc.Weight = 1 / (weeks ago + 0.4), so current week gets a weight of 2.5, the prior week a weight of 0.71, etc.The market's evaluation of those games changes over time, and I'm always looking for what the market is thinking as of today, so I weight recent games more favorably.
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I look back over the season's games and use standard linear regression techniques to come up with a set of rankings that are most consistent with the point spreads for those games. That is basically what I am doing with the Betting Market Power Rankings, only with messier data. So, if you were to make a rudimentary power ranking from those point spreads, you could come up with the following: However, since the market thinks Paper is better than Rock by 5 points and Rock is better than Scissors by 3 points, we could make a guess that Paper would be favored over Scissors by 8 points (= 5 + 3). Paper is not due to play Scissors, so we don't know how the betting market evaluates the relative strengths of those two teams. Rock plays Scissors tomorrow night, and in that game, Rock is favored 3 points. Paper plays Rock tonight and Paper is favored by 5 points. Imagine a sports league with only three teams: Team Rock, Team Paper, and Team Scissors.