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Although the core model is much the same as last year’s version, some changes – for the better, I hope – have been made. Essentially, the model is a data-driven calculation using past performance numbers (team and player) deployed against future matchups, resulting in a projected margin of victory (MOV). That MOV, against the line taken from Vegas Insider’s consensus, projects an ATS pick. As always, the final pick is based on the last posted MOV projection (which won’t change) and the closing line (which frequently does change and occasionally flips the pick); and it is on this calculation that grading the model is based. Being a one-man-band, plus old as dirt, I make mistakes, and sometimes post late, although the closer to tip-off it is, the better, as late scratches impact the outcome, as well as the calculation.
As the NBA season progresses a number of factors will negatively impact the model’s calculation. Bad teams will begin to tank, while play-off bound teams will rest starters by sitting them, reducing their minutes, or stop playing defense – all of which makes “past performance” data pretty useless. When that occurs the model’s projections become misleading; and, once a number of trigger-variables hit their target, I’ll stop posting. Usually, that means running it until just before the all star break.
I’ve added a back-to-back feature to the daily projections, and changed the weekly standings to display a few new stats that may be of use. I’d appreciate comments, to include pointing out errors.
Finally, remember the model doesn’t make “predictions” – just number based projections, which should only be used as a guide and not to blindly tail. You won’t consistently make money betting the NBA if you don’t follow basketball, don’t know players and their tendencies, who’s OUT or IN, the viability of team rotations, and the situational factors of each game (home, away, nationally televised, etc.). That said, unlike football, where luck plays an enormous part, basketball outcomes only rarely depend on luck, so numbers are a good guide.
GLTA
As the NBA season progresses a number of factors will negatively impact the model’s calculation. Bad teams will begin to tank, while play-off bound teams will rest starters by sitting them, reducing their minutes, or stop playing defense – all of which makes “past performance” data pretty useless. When that occurs the model’s projections become misleading; and, once a number of trigger-variables hit their target, I’ll stop posting. Usually, that means running it until just before the all star break.
I’ve added a back-to-back feature to the daily projections, and changed the weekly standings to display a few new stats that may be of use. I’d appreciate comments, to include pointing out errors.
Finally, remember the model doesn’t make “predictions” – just number based projections, which should only be used as a guide and not to blindly tail. You won’t consistently make money betting the NBA if you don’t follow basketball, don’t know players and their tendencies, who’s OUT or IN, the viability of team rotations, and the situational factors of each game (home, away, nationally televised, etc.). That said, unlike football, where luck plays an enormous part, basketball outcomes only rarely depend on luck, so numbers are a good guide.
GLTA
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