NCAAB spread/ML calculations using totals and locations

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • samserif
    SBR Hustler
    • 09-19-11
    • 63

    #1
    NCAAB spread/ML calculations using totals and locations
    Justin7 mentioned in another thread that ML calculations should consider totals. I'm also seeing ML differences that depend on location (home, visitor, neutral). Whether these differences are significant or not... well, that's why I'm posting this.

    Using a window of closing spreads from -5.5 to -4.5 and a window of total scores from 110 to 130 (which might be used to evaluate a -5 spread and a 120 o/u), here's what I'm seeing using data scraped since 1997 from Covers.com:

    VISITOR wins: 257 Losses: 118 Prob: 0.685 Odds: -218
    HOME wins: 600 Losses: 296 Prob: 0.670 Odds: -203
    NEUTRAL wins: 155 Losses: 72 Prob: 0.683 Odds: -215

    At first glance, this says that home teams for this particular subset are slightly overrated: they win less frequently (0.670) for the given spread(s) and given total(s) than visitors (0.685) or teams playing at neutral sites (0.683). I know the relatively small sample means this could be meaningless, but I'm seeing the same effect on other subsets of the data. For example, using spreads from -2.5 to -3.5 on the same totals:

    VISITOR wins: 383 Losses: 204 Prob: 0.652 Odds: -188
    HOME wins: 553 Losses: 382 Prob: 0.591 Odds: -145
    NEUTRAL wins: 177 Losses: 117 Prob: 0.602 Odds: -151

    and for spreads from -1.5 to -2.5 for the same (110-130) range of totals:

    VISITOR wins: 348 Losses: 223 Prob: 0.609 Odds: -156
    HOME wins: 435 Losses: 393 Prob: 0.525 Odds: -111
    NEUTRAL wins: 151 Losses: 140 Prob: 0.519 Odds: -108

    My first test in evaluating anything gleaned from data mining is to ask, "Is there any kind of reasonable theory that would explain this?" If, for example, I discovered that teams with more than four vowels in their names did better than teams with fewer than four vowels, the answer to this would be a quick "no" (or more likely, a "NFW!"). In this case, I can come up with some theories (spreads are slightly biased to over-favor home teams) but nothing that's absolutely convincing. And, there's always the possibility that it's all within the range of error. I confess: I haven't done the math on this (yet).

    Thoughts? I'm sure this has been investigated before.
  • samserif
    SBR Hustler
    • 09-19-11
    • 63

    #2
    One more thing, because I know someone will bring this up: the probabilities and the odds that I've listed above are observed probabilities from a small sample and their directly corresponding no-vig odds. I don't intend to use them as tools without more thought, engineering, and confidence intervals. I just put up the raw numbers to show how they suggest a relationship, not to claim that these samples are accurate estimators of the true values.
    Comment
    • Justin7
      SBR Hall of Famer
      • 07-31-06
      • 8577

      #3
      I saw a similar problem doing ML conversions. With a given spread and total, a road favorite performed materially different from a similar home favorite. There were also peculiarities with home versus away conversions (e.g., a game spread converts differently depending on whether the favorite is home or favorite, even at some of the lower spreads).

      I never came up with a satisfactory explanation.
      Comment
      • evo34
        SBR MVP
        • 11-09-08
        • 1032

        #4
        What was the ATS performance of each sub-group? I.e., is your finding that certain location/spread/total combos have been over/under-valued in general (ML and ATS equally affected), or that there is a disconnect between odds of winning and margin of victory for these games?
        Comment
        SBR Contests
        Collapse
        Top-Rated US Sportsbooks
        Collapse
        Working...