I am going to test a post-season capping method I have used before with some success (not great, but decent) but with some new tweaks. This differs from my usual conference play because of the neutral sites. However I will also test this method on the NIT and the Classic tournaments even though those are played mostly at home sites. In this method I evaluate past performances at each venue and theorize what that same performance would yield if played at a given venue versus today's opponent. Complicated and somewhat subjective, with margins for error. *EXAMPLE: Indiana lost a 2 pt nailbiter, ON THE ROAD, to a very tough Purdue squad. Theoretically, if that same Indiana performance was displayed against a weaker opponent like Wyoming, and on a neutral site, that would surely result in a win. Now I do understand that this would be prone to very LARGE margins-of-error if only looking at one or 2 games. So I evaluate the bulk of their respective conference schedules to increase the sample size and reduce my margin of error (MoE) I also look at game results when KEY PLAYERS were missing, which likely caused a loss or a close win (to either team) **And of course I always check the lineups to make sure all the key guys are expected to play and in good condition. I then score each team with "theoretical wins and losses" based on their schedule and strength of those opponents *IF* against today's opponent. I then get a NET wins projection for comparison. Such as Indiana vs Wyoming Tuesday, I get 15 - 3 vs. 2 - 12. Essentially this means that theoretically if Hoosier's 18 previous performances were all played against Wyoming, they *most likely* would have gone 15 - 3 (give or take a little for MoE) or rather, Indiana +12 net wins vs Wyoming -10 net wins. Then I can evaluate whether or not a bet on the moneyline holds good value.
Of course anything can happen in basketball. Motivational ups and downs, in-game injuries, early foul trouble to key players, BAD shooting day, etc, etc, and those things can easily upset "good value" and some losses will certainly occur. But it stands to reason that if the numbers are strong on your side with every bet then you should win the majority of them and enough to stay ahead of the juice.
TAMCC -7 wins vs Tx-Southern -4 wins = too close; pass
Tuesday, March 15, MENS: INDIANA -170 *BEST BET
If YOU have a method that works for you, then go get'em and I hope you turn some really good profits this month!
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I am going to test a post-season capping method I have used before with some success (not great, but decent) but with some new tweaks. This differs from my usual conference play because of the neutral sites. However I will also test this method on the NIT and the Classic tournaments even though those are played mostly at home sites. In this method I evaluate past performances at each venue and theorize what that same performance would yield if played at a given venue versus today's opponent. Complicated and somewhat subjective, with margins for error. *EXAMPLE: Indiana lost a 2 pt nailbiter, ON THE ROAD, to a very tough Purdue squad. Theoretically, if that same Indiana performance was displayed against a weaker opponent like Wyoming, and on a neutral site, that would surely result in a win. Now I do understand that this would be prone to very LARGE margins-of-error if only looking at one or 2 games. So I evaluate the bulk of their respective conference schedules to increase the sample size and reduce my margin of error (MoE) I also look at game results when KEY PLAYERS were missing, which likely caused a loss or a close win (to either team) **And of course I always check the lineups to make sure all the key guys are expected to play and in good condition. I then score each team with "theoretical wins and losses" based on their schedule and strength of those opponents *IF* against today's opponent. I then get a NET wins projection for comparison. Such as Indiana vs Wyoming Tuesday, I get 15 - 3 vs. 2 - 12. Essentially this means that theoretically if Hoosier's 18 previous performances were all played against Wyoming, they *most likely* would have gone 15 - 3 (give or take a little for MoE) or rather, Indiana +12 net wins vs Wyoming -10 net wins. Then I can evaluate whether or not a bet on the moneyline holds good value.
Of course anything can happen in basketball. Motivational ups and downs, in-game injuries, early foul trouble to key players, BAD shooting day, etc, etc, and those things can easily upset "good value" and some losses will certainly occur. But it stands to reason that if the numbers are strong on your side with every bet then you should win the majority of them and enough to stay ahead of the juice.
TAMCC -7 wins vs Tx-Southern -4 wins = too close; pass
Tuesday, March 15, MENS: INDIANA -170 *BEST BET
If YOU have a method that works for you, then go get'em and I hope you turn some really good profits this month!
Yes, off to a reasonable start on Day 1, although that can change with Day 2 and Day 3 of this method test, so will be interesting to see how this plays out. Yesterday the method identified numerous significant differences in hypothetical projections of records unique to a given level of opponent, triggering several bets. My bets went 5 - 2 - but importantly - winning all 4 designated *BEST BETS!
Some matchups are ignored because of prohibitive moneylines. Unanticipated "key player" absences may trigger buybacks.
Yes, off to a reasonable start on Day 1, although that can change with Day 2 and Day 3 of this method test, so will be interesting to see how this plays out. Yesterday the method identified numerous significant differences in hypothetical projections of records unique to a given level of opponent, triggering several bets. My bets went 5 - 2 - but importantly - winning all 4 designated *BEST BETS!
Some matchups are ignored because of prohibitive moneylines. Unanticipated "key player" absences may trigger buybacks.
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