A database-crunching query based on ignorance...

[Milkshaker]

Firstly: I am totally ignorant whether or not what I am asking could be easily done or if such a query is routine if you have access to the right database.

Is it possible to get a list of which "jockey off" changes produce the highest ROI nationwide? (i.e. every time jockey X is replaced by any other jockey, the ROI is Y). Can this be drilled down to a particular circuit?

Would love to put some of my anecdotal theories to the test...

[ranchwest]

Firstly: I am totally ignorant whether or not what I am asking could be easily done or if such a query is routine if you have access to the right database.

Is it possible to get a list of which "jockey off" changes produce the highest ROI nationwide? (i.e. every time jockey X is replaced by any other jockey, the ROI is Y). Can this be drilled down to a particular circuit?

Would love to put some of my anecdotal theories to the test...

I've mined data that data-wise was the same type of query. It is definitely possible. Personally, I think it is easier to specifically set out to focus on that type query than to take a general database and try to retrieve that data, but it can be done either way.

This could be a simple setup or if you are talented and ambitious you could get pretty complex with it. For instance, you could break it out by moving up or down in class, by surface, by track condition, by distance, by track or circuit, by days away, etc.

[Bill F]

This is a query I ran a while back. It shows the results of selected jockeys OFF in the horse's next race. It covers all tracks and surfaces from 1-2009 thru 5-2010

I'm sure that others can post more recent results, but if requested, I could "drill down" and update with latest results (when I have the time).




Jockey Off Starts Wins Places Shows Win% Place% Show% W ROI% P ROI% S ROI% $2wAvg $2wMax $2wNet I/V A/E

ALBARADO R J 1043 207 347 477 19.85% 33.56% 46.58% 91.98% 85.26% 86.36% $9.27 $50.00 -$167.3 1.74 1.11
BAZE R A 1000 190 325 450 19.00% 32.60% 46.06% 89.27% 77.31% 79.90% $9.40 $41.80 -$214.6 1.45 1.08
BAZE T C 694 105 209 299 15.13% 30.25% 43.91% 84.17% 89.67% 90.68% $11.13 $67.00 -$219.7 1.27 1.01
BEJARANO R 905 138 269 385 15.25% 29.86% 43.16% 77.46% 77.45% 77.64% $10.16 $55.00 -$407.9 1.25 0.93
BOREL C H... 752 117 214 319 15.56% 28.69% 43.28% 73.03% 80.48% 89.13% $9.39 $55.60 -$405.7 1.35 0.88
BRAVO J...... 643 99 195 261 15.40% 30.47% 41.30% 86.46% 82.83% 78.88% $11.23 $68.20 -$174.1 1.30 1.04
BRIDGMOHAN S X 779 123 241 342 15.79% 31.06% 44.24% 71.23% 76.62% 82.04% $9.02 $37.80 -$448.3 1.39 0.86
CASTELLANO J J 857 137 254 362 15.99% 29.85% 43.35% 85.99% 81.30% 81.28% $10.76 $88.00 -$240.1 1.36 1.04
CASTRO E 991 171 307 448 17.26% 31.14% 46.14% 83.86% 85.50% 91.83% $9.72 $58.50 -$319.8 1.44 1.01
CENTENO D E 953 117 253 350 12.28% 26.60% 37.43% 62.80% 72.11% 72.66% $10.23 $63.80 -$709.0 1.05 0.76
CHAVEZ J F 420 52 92 145 12.38% 21.90% 34.86% 60.56% 64.21% 70.58% $9.78 $49.80 -$331.3 1.04 0.73
COA E M........ 986 124 283 417 12.58% 28.76% 43.03% 66.49% 84.09% 87.88% $10.57 $94.60 -$660.9 1.10 0.80
COHEN DAVID 986 188 338 485 19.07% 34.38% 50.16% 83.55% 86.80% 89.97% $8.76 $70.20 -$324.4 1.54 1.01
DESORMEAUX K J 710 122 214 301 17.18% 30.31% 43.25% 85.73% 79.02% 80.05% $9.98 $73.00 -$202.7 1.49 1.03
DOMINGUEZ R A 1267 198 396 548 15.63% 31.53% 44.34% 71.71% 75.55% 78.26% $9.18 $113.50 -$716.9 1.27 0.86
ESPINOZA V 561 99 164 238 17.65% 29.39% 43.04% 104.97% 80.53% 86.79% $11.90 $103.40 $55.8 1.44 1.26
GARCIA A...... 828 132 235 327 15.94% 28.42% 40.12% 79.40% 75.43% 73.77% $9.96 $93.50 -$341.2 1.36 0.96
GARCIA MARTIN 660 91 171 255 13.79% 25.99% 39.35% 60.63% 66.16% 74.33% $8.79 $34.80 -$519.7 1.17 0.73
GOMEZ G K... 775 150 273 375 19.35% 35.27% 48.89% 98.46% 88.07% 86.55% $10.17 $59.60 -$23.9 1.58 1.19
LEPAROUX JULIEN 1086 226 390 558 20.81% 36.04% 52.39% 88.45% 84.83% 93.75% $8.50 $49.60 -$250.9 1.80 1.07
LEZCANO JOSE 1164 181 337 473 15.55% 29.05% 41.49% 71.19% 72.24% 75.69% $9.16 $57.20 -$670.7 1.34 0.86
LOPEZ C C 661 87 199 278 13.16% 30.29% 42.97% 61.38% 75.20% 80.76% $9.33 $42.20 -$510.5 1.05 0.74
LOPEZ PASCACIO 902 97 207 316 10.75% 23.15% 35.75% 60.39% 68.36% 69.42% $11.23 $57.80 -$714.5 0.93 0.73
MARAGH RAJIV 1163 166 341 481 14.27% 29.47% 42.45% 73.11% 80.13% 82.39% $10.24 $65.50 -$625.5 1.22 0.88
NAKATANI C S 389 56 109 158 14.40% 28.02% 41.58% 73.32% 64.70% 76.13% $10.19 $119.80 -$207.6 1.20 0.88
NAPRAVNIK ANNA 925 146 278 405 15.78% 30.18% 44.90% 77.17% 75.48% 83.13% $9.78 $48.80 -$422.3 1.27 0.93
PRADO E S 787 138 243 343 17.53% 31.07% 44.43% 93.41% 81.43% 88.55% $10.65 $97.00 -$103.7 1.54 1.13
ROSARIO JOEL 1045 144 286 409 13.78% 27.42% 39.86% 63.00% 66.30% 70.23% $9.14 $35.00 -$773.4 1.12 0.76
ROSE J...... 801 119 257 348 14.86% 32.17% 44.33% 68.72% 81.06% 78.53% $9.25 $41.80 -$501.1 1.21 0.83
SMITH M E 400 43 114 161 10.75% 28.57% 41.18% 66.35% 84.80% 87.81% $12.34 $51.40 -$269.2 0.88 0.80
SOLIS A..... 399 55 113 156 13.78% 28.32% 39.69% 67.54% 74.17% 74.29% $9.80 $32.80 -$259.0 1.14 0.81
TALAMO JOSEPH 728 113 218 309 15.52% 30.07% 42.98% 81.83% 84.74% 82.59% $10.54 $59.60 -$264.6 1.28 0.99
TRUJILLO E 1055 178 323 452 16.87% 30.76% 44.05% 84.82% 83.83% 84.22% $10.05 $71.20 -$320.3 1.44 1.02
VELASQUEZ CORN. 927 147 280 386 15.86% 30.27% 42.23% 77.21% 82.16% 83.19% $9.74 $56.00 -$422.6 1.39 0.93
VELAZQUEZ J R 934 182 324 442 19.49% 34.91% 48.41% 84.03% 83.19% 86.13% $8.62 $56.00 -$298.4 1.67 1.01

[sjk]

Easy for me to run (I am tracking only the dirt starts whick changes the dataset somewhat).

Here are some of the higher returns:

off jock avg return
MAYHEW G 1.41
VERENZUELA J 0.97
FUSILIER C 0.96
JOHNSON J 0.90
LOPEZ E 0.84
SUAREZ G 0.75
BISONO A 0.72
CONTRERAS J 0.67
USKE S 0.67
FRAGOSO P 0.65
BRYAN D 0.63
CARTER K 0.62
BRACALONI N 0.60
LLOYD J 0.59
DESOUZA N 0.58
ESTRADA J 0.57
SNOW M 0.57
NELSON T 0.55
LUARK M 0.54
ORTIZ J 0.52
ROBLETTO L 0.50
SPATARO C 0.49
HIGUERA A 0.48
WHITACRE B 0.47
VEGA J 0.44
MARTINEZ H 0.44
LUZZI M 0.44
ESCOBAR M 0.43
GOMEZ E 0.43
CASTILLO O 0.42
WETHEY J 0.42
GOMEZ G 0.42
COA D 0.40
PARISH R 0.40
JAEN A 0.37
RAMIREZ J 0.36
PELTROCHE E 0.35
MCMANIGELL K 0.34
VON ROSEN A 0.33
BEAUREGARD S 0.33
BIRZER A 0.32
MCKEE J 0.32
FELIX J 0.32
ERAMIA R 0.32
REYNOLDS K 0.31
MOJICA J 0.31
NICHOLLS K 0.30
BOURQUE S 0.29
YODICE A 0.28
CAMEJO O 0.27
VAZ E 0.26
OSORIO J 0.26
LANDRY R 0.26
SHEPHERD J 0.26
MELANCON J 0.26
BOURQUE C 0.25
MIGLIORE R 0.25
BELMONTE L 0.23
SANTOS B 0.22
SOLIS A 0.22

[Milkshaker]

Thanks for the feedback & stat lists, guys. Interesting stuff.

Makes me wonder what else I am missing by not going down the database avenue in my handicapping.

[johnhannibalsmith]

...MAYHEW G 1.41...

I'm racking my brain... where does this person ride?

[sjk]

I'm racking my brain... where does this person ride?

Most recently at CT and before that for several months at Pnl.

[harntrox]

In my Db software, i assign 1st Time New Jockey as a trainer stat, and then track the Top Jockey Combos for that trainer. I see the jockey from the trainers point of view - just another piece of equipment to experiment with.

I have seen repeated patterns of certain trainers winning when they change the jockey. The trainers switching to top combos do this more consistently than the pick-up riders.

These conditions repeat themselves more often at certain tracks than others.