Tom,
You should know better <G>...
OF COURSE I have data to back that up... as in every race run at all of the major circuits in North America since synthetics first appeared on the North American scene at Turfway in 2005.
I'm constantly measuring track profiles... inside path vs. outside path... speed favoring vs. speed tiring... large sample distributions of winning horses at individual distances broken down by metrics such like pctE, pctM, run style, etc.
Zast got the gist of what I told him save for a few minor details. I think he mentioned that I had a sample of of 55k horses. What I said was all starters in North America which last year was about 55k races.
If you accumulate the data and study it eventually it hits you:
Synthetic surfaces produce results that "somewhat" mimic results produced by a random number generator.
What do I mean by that?
A data distribution for all starters in races on natural dirt surfaces broken out by something really simple like rank for the horse with the single Best E2 pace fig (using JCapper HDW data) (and with no attempt to break ties) for calendar year 2009 looks like this:
Code:
By: SQL-F17 Rank
Rank Gain Bet Roi Wins Plays Pct Impact
1 -12172.20 88840.00 0.8630 8736 44420 .1967 1.5716
2 -16054.60 86084.00 0.8135 7257 43042 .1686 1.3474
3 -19870.70 85382.00 0.7673 6120 42691 .1434 1.1456
4 -20814.10 84674.00 0.7542 5516 42337 .1303 1.0412
5 -22856.10 82552.00 0.7231 4681 41276 .1134 0.9063
6 -24697.50 76834.00 0.6786 3787 38417 .0986 0.7878
7 -21488.30 63652.00 0.6624 2685 31826 .0844 0.6742
8 -16375.30 46798.00 0.6501 1751 23399 .0748 0.5980
9 -11142.30 31256.00 0.6435 993 15628 .0635 0.5078
10 -7635.50 18414.00 0.5853 496 9207 .0539 0.4305
11 -3039.50 7372.00 0.5877 163 3686 .0442 0.3534
12 -1435.00 3222.00 0.5546 72 1611 .0447 0.3572
13 -240.60 310.00 0.2239 5 155 .0323 0.2578
14 -69.40 106.00 0.3453 3 53 .0566 0.4523
15 -2.00 2.00 0.0000 0 1 .0000 0.0000
16 -2.00 2.00 0.0000 0 1 .0000 0.0000
17 -2.00 2.00 0.0000 0 1 .0000 0.0000
18 -2.00 2.00 0.0000 0 1 .0000 0.0000
19 -2.00 2.00 0.0000 0 1 .0000 0.0000
Now here's the same data distribution, all starters in races on synthetic surfaces only broken out by rank for the horse with the Best E2 pace fig (using JCapper HDW data) for calendar year 2009:
Code:
By: SQL-F17 Rank
Rank Gain Bet Roi Wins Plays Pct Impact
1 -2632.00 15242.00 0.8273 1328 7621 .1743 1.3958
2 -2790.90 14810.00 0.8116 1184 7405 .1599 1.2808
3 -2974.30 14640.00 0.7968 1064 7320 .1454 1.1643
4 -3928.30 14504.00 0.7292 910 7252 .1255 1.0051
5 -3100.80 14342.00 0.7838 846 7171 .1180 0.9450
6 -3486.80 12568.00 0.7226 656 6284 .1044 0.8362
7 -2130.10 9990.00 0.7868 474 4995 .0949 0.7601
8 -2124.60 7192.00 0.7046 290 3596 .0806 0.6460
9 -1564.90 4836.00 0.6764 186 2418 .0769 0.6162
10 -969.40 3066.00 0.6838 113 1533 .0737 0.5904
11 -760.60 1816.00 0.5812 46 908 .0507 0.4058
12 -173.40 872.00 0.8011 27 436 .0619 0.4960
13 33.70 256.00 1.1316 6 128 .0469 0.3755
14 -57.90 124.00 0.5331 2 62 .0323 0.2584
Notice that the win rate, impact values, and roi for the top ranked horses on synthetic surfaces suffers when compared to the numbers for the top ranked horses on dirt surfaces.
IMHO, this captures the essence of player frustration with synthetic surfaces.
If E2 pace figs had no effect at all on race outcomes... then the data distribution might look like this one - which is actually the result of using a random number generator to produce a random number between 1 and 100 on the set of all starters on synthetic surfaces for calendar year 2009:
By: RGN
Code:
>=Min < Max Gain Bet Roi Wins Plays Pct Impact
-999.00 5.00 -1102.70 4720.00 0.7664 299 2360 .1267 1.0149
5.00 10.00 -1621.20 5892.00 0.7248 344 2946 .1168 0.9353
10.00 15.00 -1467.30 5714.00 0.7432 354 2857 .1239 0.9925
15.00 20.00 -1531.90 5722.00 0.7323 323 2861 .1129 0.9043
20.00 25.00 -1525.00 5598.00 0.7276 358 2799 .1279 1.0245
25.00 30.00 -1453.00 5660.00 0.7433 340 2830 .1201 0.9624
30.00 35.00 -1359.80 5644.00 0.7591 373 2822 .1322 1.0588
35.00 40.00 -1406.20 5700.00 0.7533 350 2850 .1228 0.9837
40.00 45.00 -1227.30 5702.00 0.7848 387 2851 .1357 1.0873
45.00 50.00 -1777.00 5738.00 0.6903 345 2869 .1203 0.9632
50.00 55.00 -1532.50 5586.00 0.7257 342 2793 .1224 0.9808
55.00 60.00 -882.90 5714.00 0.8455 381 2857 .1334 1.0682
60.00 65.00 -1631.80 5696.00 0.7135 340 2848 .1194 0.9563
65.00 70.00 -1055.00 5708.00 0.8152 370 2854 .1296 1.0385
70.00 75.00 -1246.20 5708.00 0.7817 334 2854 .1170 0.9374
75.00 80.00 -1104.60 5796.00 0.8094 381 2898 .1315 1.0531
80.00 85.00 -1292.60 5666.00 0.7719 352 2833 .1242 0.9953
85.00 90.00 -667.50 5702.00 0.8829 389 2851 .1364 1.0929
90.00 95.00 -1006.50 5652.00 0.8219 360 2826 .1274 1.0204
95.00 999999.00 -1769.30 6940.00 0.7451 410 3470 .1182 0.9465
Take a look at results from the above samples and tell me which set of numbers... those produced by natural dirt... or those produced by synthetics... more closely mimics numbers produced by a random number generator.
Synthetics of course!
Now is this a bad thing?
Depends how you look at it.
If your selection process is married to the idea of using the top ranked horses in terms of <insert name of factor here> only... then you are going to struggle as a player and throw your hands up in disgust... and eventually stop betting synthetics... which is what a lot of players have done.
However, those who adust their selection process to make it more aligned with the way synthetic surfaces alter race outcomes...
hint: a willingness to look deeper into a field when identifying contenders helps... so does value based play or pass decision making... players who make adjustments to get the surface working FOR them and not against them... those players can find betting opportunities on synthetic surfaces....
Not easy to do because it takes a fair amount of work... But it absolutely IS doable if you are willing to do the requisite R&D.
-jp
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