GT, you wrote:
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I got to the point where on could make an oddsline better than the public (slightly) on any measure you'd care to use to determine that. But they didn't provide many betting opportunities, so I gave that up and now make them differently. They do provide a profit at the theorhetical break-even point and above, but only if I stick to the "contenders". I've never been able to make a full oddsline and have the low probability "overlays" make money.
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It looks like your experiences with odds lines are almost exactly the same as my own. I've also found that when I stick to contenders (which by my own definition are horses with hidden positives) I can make money simply by applying a theoretical break even point provided by an odds line for play or pass decision making.
You also posted:
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I would really like for you to elaborate on this -- "keyed off" of how? And the break-even point is determined how? Are you saying you are using your oddsline as-is, but only considering horses for betting that pass some additional factor filter?
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Yes. That's exactly what I'm saying.
I'm going to use a really simple model to illustrate this. In this case, "keyed off of how" is a simple UDM or spot play defined by the following 2 rules:
1. The horse must be ranked 1st in its field for Power Rating
2. The horse must qualify according to the rules in Boxcar's "B Angle" as set forth in his post from a year or two ago.
OMG I can already hear the flood of groans out there in cyberland.
But let's use THAT as an example of a working UDM and let it define whether or not a horse qualifies as a potential play.
Now, what I've done next is run that against all horses in my calendar year 2006 database broken out by OR3. Before we go any further I need to define OR3. In JCapper, OR3 stands for Odds Ratio Three or Post Time Odds divided by the program's JPRTote Odds Line. In a perfect world OR3 = 1.00 represents a theoretical break even point. Any horse with OR3 >= 1.00 represents an overlay and any horse with OR3 < 1.00 represents an underlay.
Next question: Wha does the data show?
Code:
Data Window Settings:
999 Divisor
Filters Applied: ANGLE_B= (require Angle B)
Surface: (ALL*) Distance: (All*)
From Index File: D:\2007\Q1_2007\pl_JPR1_06.txt)
Data Summary Win Place Show
Mutuel Totals 3414.00 3328.90 3164.10
Bet -3324.00 -3324.00 -3324.00
Gain 90.00 4.90 -159.90
Wins 434 744 943
Plays 1662 1662 1662
PCT .2611 .4477 .5674
ROI 1.0271 1.0015 0.9519
Avg Mut 7.87 4.47 3.36
By: OR3
>=Min <Max Gain Bet Roi Wins Plays Pct Impact
-999.00 0.00 0.00 0.00 0.0000 0 0 .0000 0.0000
0.00 0.10 0.00 0.00 0.0000 0 0 .0000 0.0000
0.10 0.20 0.00 0.00 0.0000 0 0 .0000 0.0000
0.20 0.30 -4.00 4.00 0.0000 0 2 .0000 0.0000
0.30 0.40 5.00 18.00 1.2778 8 9 .8889 3.4040
0.40 0.50 9.00 52.00 1.1731 20 26 .7692 2.9458
0.50 0.60 -11.10 114.00 0.9026 27 57 .4737 1.8140
0.60 0.70 -66.90 200.00 0.6655 32 100 .3200 1.2254
0.70 0.80 -20.20 342.00 0.9409 57 171 .3333 1.2765
0.80 0.90 -13.50 454.00 0.9703 69 227 .3040 1.1640
0.90 1.00 18.60 486.00 1.0383 69 243 .2840 1.0874
1.00 1.10 40.30 458.00 1.0880 58 229 .2533 0.9699
1.10 1.20 9.30 356.00 1.0261 34 178 .1910 0.7315
1.20 1.30 3.60 260.00 1.0138 21 130 .1615 0.6186
1.30 1.40 -40.70 180.00 0.7739 15 90 .1667 0.6382
1.40 1.50 14.20 90.00 1.1578 6 45 .1333 0.5106
1.50 1.60 -6.80 100.00 0.9320 5 50 .1000 0.3829
1.60 1.70 34.40 64.00 1.5375 5 32 .1562 0.5984
1.70 1.80 24.80 34.00 1.7294 2 17 .1176 0.4505
1.80 999999.00 94.00 112.00 1.8393 6 56 .1071 0.4103
Now, the UDMs I use in real life work a lot better than the overly simple model I've used here. But the way I use them - and my process in getting there - is almost identical to what I've shown here. Each UDM or model will have its own break even point for OR3 (and other odds ratios within the program.) In the end my play or pass decision making comes down to just 3 things:
1. Does the horse qualify according to the rules of an active UDM or model?
2. Does the horse look ok on the track (my subjective view.)
3. Does the horse have odds high enough to be above the model's break even point for a significant odds line ratio? Which BTW can even be part of the model itself.
If the answer is yes to all three, chances are I'm betting.
GT, in a nutshell... without going into any great detail about the actual factors in my models... that's what I do.
-jp
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