Posted:
#1
Ladies and Gentlemen,
This will be my first full season working with NHL data. I'm using a formula very similar to the MLB underdog formula which has worked extremely well for me for the last two years. I compare the road team's average points scored on the road against the home team's avg points allowed at home, and vice versa, and then have a second formula that weighs the net performance of the team against their strength of schedule to get an output similar to Sagarin's rankings.
The final step is a comparison of my expectations to the line in an attempt to find a moneyline value.
In short, we're looking for underdogs with a big ML but a reasonable chance of upset. The determination of value is made by dividing the ML into 50%, which tells me the frequency of wins necessary to break even. There is an extensive discussion of my method in this regard on my thread 'Critique my Method (MLB)'.
In MLB I started off with a progressive method, and used this to great success. However, due to binomial distribution, you're bound to end up with some long losing streaks, and this can lead to some big bets.
Therefore, I'm going to attempt to increase the total number of events and stick with a fixed-amount per event. The upside is we eliminate the risk inherent in any progressive system, the downside is you lose the benefit of eliminating losses with an immediately succeeding win, a rather frequent occurence when the stats are approximately 50%. Again, check the MLB thread for an extensive, season-long discussion of this.
That having been said, I will always post picks in order of favorite to least-favorite in terms of the final value proposition of the event. I know some of you will just email and ask me which is my favorite anyway.
14 Nov 08 Underdogs:
Nashville @ 165
Florida @ 140
This will be my first full season working with NHL data. I'm using a formula very similar to the MLB underdog formula which has worked extremely well for me for the last two years. I compare the road team's average points scored on the road against the home team's avg points allowed at home, and vice versa, and then have a second formula that weighs the net performance of the team against their strength of schedule to get an output similar to Sagarin's rankings.
The final step is a comparison of my expectations to the line in an attempt to find a moneyline value.
In short, we're looking for underdogs with a big ML but a reasonable chance of upset. The determination of value is made by dividing the ML into 50%, which tells me the frequency of wins necessary to break even. There is an extensive discussion of my method in this regard on my thread 'Critique my Method (MLB)'.
In MLB I started off with a progressive method, and used this to great success. However, due to binomial distribution, you're bound to end up with some long losing streaks, and this can lead to some big bets.
Therefore, I'm going to attempt to increase the total number of events and stick with a fixed-amount per event. The upside is we eliminate the risk inherent in any progressive system, the downside is you lose the benefit of eliminating losses with an immediately succeeding win, a rather frequent occurence when the stats are approximately 50%. Again, check the MLB thread for an extensive, season-long discussion of this.
That having been said, I will always post picks in order of favorite to least-favorite in terms of the final value proposition of the event. I know some of you will just email and ask me which is my favorite anyway.
14 Nov 08 Underdogs:
Nashville @ 165
Florida @ 140
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