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Old 01-09-2018, 12:34 PM   #16
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Originally Posted by SG4 View Post
I was wondering if any kind of stat or program exists to give jockeys something of a performance expectation rating. What I mean by this is say a jockey is on the 4th betting choice in a race & they finish 2nd, I'd give them a +2 score that race, or if you're on a favorite and finish 5th they'd get a -4 for that race. Wonder if an average score would help identify riders who may be over/underestimated by the betting public, or could possibly help identify upcoming apprentice jockeys as ones to watch.
As in all odds related plays, it would be best to determine a jocky's efficiency by comparing his actual wins to his expected wins. the forever a/e ratio using the final true dollar odds.
these comparisons should further be broken down by incremental odds, the small the more accurate, the greater the required data
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Old 01-09-2018, 01:50 PM   #17
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One of the problems with all these stats is that jockeys take money independently of the horses they ride.

We have to make sure what we want our metric to measure.

Do we want to measure betting value or do we want to measure riding skill?

A great rider could wind up on a lot of underlays because he's so popular. So the fact that his horses under-perform their odds may say nothing about his skill.
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Old 01-09-2018, 01:55 PM   #18
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I'm not saying that knowing an inside rider from an outside rider is the be all end all of things (it's not.) But the database testing I've done suggests that knowing that and measuring performance produces better results than ignoring that and measuring performance for rider alone.
Something like that would be especially useful on an inside or outside biased track.

So would knowledge of which riders pick up on biases quickly and ride to their advantage and which don't. That also gets into connections. Some owners and trainers are on top of that and give instructions on bias to the rider. Others do not. Same with pace setup.
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Old 01-09-2018, 03:00 PM   #19
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Originally Posted by classhandicapper View Post
Here's a quick sample of the kind of thing you can do in 5 minutes.

This is Jockey performance for riders that had a minimum of 25 mounts on favorites at AQU, BEL and SAR. This covers about 2 1/2 years. Doing it by rank will take a little longer. Something like this could also obviously be broken up by track, distance, surface, running style etc...

The average for all NYRA jockeys was 2.83.

So anything lower than 2.83 would be positive and anything higher would be negative. You can also see the average odds of the favorites the jockey ride to make an adjustment there.
Yup.

That's a good illustration of using the type of analysis being discussed in this thread to come up with a rider rating.

I wanted to add to my previous post and provide some data.

The sample below shows all morning line favorites that have raced at what I consider to be A and B tracks over (roughly) the past three weeks:
Code:
     query start:         1/9/2018 10:47:34 AM
     query end:           1/9/2018 10:47:35 AM
     elapsed time:        1 seconds

     Data Window Settings:
     Connected to: C:\JCapper\exe\JCapper2.mdb
     999 Divisor  Odds Cap: None
     SQL UDM Plays Report: Hide

     SQL:  SELECT * FROM STARTERHISTORY
           WHERE RANKMLINE=1 
           AND INSTR('AQU-GGX-GPX-HAW-LRL-PHA-TAM-SAX', TRACK) > 0 
           AND [DATE] >= #12-17-2017# 
           AND [DATE] <= #01-08-2018# 
           ORDER BY [DATE], TRACK, RACE


     Data Summary          Win         Place          Show
     -----------------------------------------------------
     Mutuel Totals     1043.50       1094.70       1080.40
     Bet              -1258.00      -1258.00      -1258.00
     -----------------------------------------------------
     P/L               -214.50       -163.30       -177.60

     Wins                  196           333           411
     Plays                 629           629           629
     PCT                 .3116         .5294         .6534

     ROI                0.8295        0.8702        0.8588
     Avg Mut              5.32          3.29          2.63

Nothing Earth shattering there. (The above results are about what you'd expect from morning line favorites.)


I recently wrote an algorithm (involving a little bit of AI) that calculates Cumulative Probability or F(x) for each rider given the situation he or she finds himself or herself in.

Admittedly, classifying individual rider situations is something subjective on my part.

That said, the algorithm is programmed to analyze the attributes for each mount, and from there classify that mount as belonging to a basic category such as inside speed, inside closer, middle post speed, middle post closer, outside speed, or outside closer.

From there the algorithm is programmed to pull each rider's like mounts from the database and calculate F(x) -- with the resulting F(x) representing actual performance vs. expected performance over all the times the rider was asked to perform that specific task... for example, ride an inside closer in a sprint race on the dirt at today's track.

All of that said, here is the above sample broken out by rank for Rider (Fx) as described above:
Code:
     By: SQL-F01 Rank -- F(x) for Rider, given the situation

     Rank       P/L        Bet        Roi    Wins   Plays     Pct     Impact     AvgMut
     ----------------------------------------------------------------------------------
      1       48.60     190.00     1.2558      43      95   .4526     1.4526       5.55  
      2      -56.80     152.00     0.6263      19      76   .2500     0.8023       5.01  
      3       -4.50     126.00     0.9643      22      63   .3492     1.1207       5.52  
      4      -56.20     130.00     0.5677      15      65   .2308     0.7406       4.92  
      5      -46.60     170.00     0.7259      23      85   .2706     0.8684       5.37  
      6       -7.00     142.00     0.9507      26      71   .3662     1.1752       5.19  
      7      -35.80     122.00     0.7066      15      61   .2459     0.7891       5.75  
      8      -35.00     104.00     0.6635      13      52   .2500     0.8023       5.31  
      9      -32.00      68.00     0.5294       8      34   .2353     0.7551       4.50  
     10       20.20      32.00     1.6313      10      16   .6250     2.0057       5.22  
     11       -9.80      14.00     0.3000       1       7   .1429     0.4585       4.20  
     12        0.40       8.00     1.0500       1       4   .2500     0.8023       8.40

And here is the above sample broken out by numeric value for Rider (Fx) as described above:
Code:
By: SQL-F01 Numeric Value -- F(x) for Rider, given the situation
   >=Min        < Max        P/L        Bet        Roi    Wins   Plays     Pct   Impact
--------------------------------------------------------------------------------------
-99.0000       0.0000       0.00       0.00     0.0000       0       0   .0000   0.0000
  0.0000       0.0500      -3.80     160.00     0.9763      32      80   .4000   1.2837
  0.0500       0.1000     -15.70     128.00     0.8773      22      64   .3438   1.1032
  0.1000       0.1500     -76.10     170.00     0.5524      18      85   .2118   0.6796
  0.1500       0.2000     -14.60      82.00     0.8220      11      41   .2683   0.8610
  0.2000       0.2500     -26.60      64.00     0.5844       7      32   .2188   0.7020
  0.2500       0.3000      -8.70      76.00     0.8855      14      38   .3684   1.1823
  0.3000       0.3500       9.20      74.00     1.1243      12      37   .3243   1.0408
  0.3500       0.4000     -15.80      36.00     0.5611       4      18   .2222   0.7132
  0.4000       0.4500     -17.20      32.00     0.4625       2      16   .1250   0.4011
  0.4500       0.5000     -12.40      42.00     0.7048       6      21   .2857   0.9169
  0.5000       0.5500     -16.80      96.00     0.8250      17      48   .3542   1.1366
  0.5500       0.6000      -4.00      30.00     0.8667       5      15   .3333   1.0697
  0.6000       0.6500     -24.60      40.00     0.3850       3      20   .1500   0.4814
  0.6500       0.7000      -7.60      20.00     0.6200       2      10   .2000   0.6418
  0.7000       0.7500      -6.80      14.00     0.5143       2       7   .2857   0.9169
  0.7500       0.8000     -20.20      24.00     0.1583       1      12   .0833   0.2674
  0.8000       0.8500     -11.80      22.00     0.4636       2      11   .1818   0.5835
  0.8500       0.9000       1.30      20.00     1.0650       4      10   .4000   1.2837
  0.9000    9999.0000      57.70     128.00     1.4508      32      64   .5000   1.6046

Note the outperformance by the rank=1 mounts for Rider F(x).

Also note the outperformance at the extreme edges of the Rider F(x) numeric value distribution. In theory, any F(x) value over 0.50 represents outperformance.

Yet, in this sample, the strongest outperformance occurred when F(x) was greater than or equal to 0.85.

I'm guessing outperformance only when F(x) is greater than or equal to 0.85 may turn out to be the result of small sample noise. (My gut tells me a larger sample is needed.)

That said, this is the first sample I've generated using this technique and the results are promising (at least so far.)

I also wanted to touch on outpeformance at the other edge of the sample -- specifically when F(x) is equal to zero.

A closer look at the data reveals this part of the sample is populated by riders who have a small number of mounts in the situation they are being queried for.

For example: If a rider only has three mounts as a closer with a far outside post in dirt routes at today's track -- and the query results come back as 0 for 3 with an F(x) of 0.00... That 0.00 is probably not a true representation of the rider's ability in that situation.


-jp

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Old 01-09-2018, 09:34 PM   #20
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Thanks for all the feedback! Glad this has made for an interesting discussion, and of course shows all the varied ways to approach gathering a worthwhile stat on this end.

I think my interest was more in what jockeys move longshots up, so the query of jockeys on just favored mounts may lend insight in one way, but in my expectations wouldn't be as valuable. Not to mention where were those 25 times Fernando Jara rode a favorite on the NYRA circuit in the last 3 years, I must've been on vacation all those days lol.

The most recent thought that inspired this idea was seeing some of Irad Ortiz's results lately, and it seemed like whenever he was on horses at decent odds they always outperformed expectations, which made me think he really is proving his worth as a top rider. But of course with the simplistic calculation I proposed initially of 0 points at best if you're riding a favorite, a jockey like him who is often on chalk will probably be under-rated in this method. The Wong #'s seemed to be on the right track far as something in a useful vein.

Where the best value lies far as real world application goes I think would be applying this stat to apprentices in their very nascent stages, I feel like if your eyes are open you'll start to see some of those initial longshots running well aren't just flukes & could be the markings of a solid new rider, and you can usually jump on this for a period before word is fully out among the betting public.
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Old 01-13-2018, 08:42 AM   #21
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Lots of good points made here ... just wanted to add two things

1) Another way of measuring how good a jockey is by expressing how much better than expected he does with his mounts. In Hong Kong, UK, Ireland, etc you can just compare his or her speed/performance ratings with the official ratings. You could then conclude that (hypothetical example) Ryan Moore is worth an extra 2lbs.

2) In my experience it is crucial to calculate jockey ability over different surfaces/distances. For example .... some jocks are fine on the dirt but completely useless on the turf. Some otherwise moderate jocks seem to be much better over 5F than their overall stats would suggest.
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Old 02-22-2018, 11:42 PM   #22
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Originally Posted by SG4 View Post
I was wondering if any kind of stat or program exists to give jockeys something of a performance expectation rating. What I mean by this is say a jockey is on the 4th betting choice in a race & they finish 2nd, I'd give them a +2 score that race, or if you're on a favorite and finish 5th they'd get a -4 for that race. Wonder if an average score would help identify riders who may be over/underestimated by the betting public, or could possibly help identify upcoming apprentice jockeys as ones to watch.
Hey SG4

I am looking to revisit this using Davis at Aqueduct but using the Morning Line instead of actual odds

Also, instead of the finish position I will just use 4 for off the board so if he's 6th choice in the Morning Line and he runs 4th it will be 4 - 4 = 0 and not 6 - 4 = +2

I am not giving him a +2 for finishing off the board it doesn't feel right to do that

However, I will keep 1st choice in the Morning Line finishing 6th as a -5 so 1 - 6 = -5

Quote:
Originally Posted by TheOracle View Post
Here is D Davis record at Aqueduct overall as of yesterday






Surprisingly enough, his record on a Fast Surface gives a much better return per $2 win wager than on a wet Surface!!!

I will keep an eye on his mounts from now on at Aqueduct!!!
I am curious to see what his +/- is overall and in certain race types (i.e. Maidens, Claimers, etc.).

If he is giving a huge minus in certain situations maybe you stay away and do the opposite for huge plus values

Let me know if this is similar to what you had in mind

I will also do this for the Trainers at Aqueduct!!!

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Old 02-23-2018, 02:00 AM   #23
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Originally Posted by SG4 View Post
Thanks for all the feedback! Glad this has made for an interesting discussion, and of course shows all the varied ways to approach gathering a worthwhile stat on this end.

I think my interest was more in what jockeys move longshots up, so the query of jockeys on just favored mounts may lend insight in one way, but in my expectations wouldn't be as valuable. Not to mention where were those 25 times Fernando Jara rode a favorite on the NYRA circuit in the last 3 years, I must've been on vacation all those days lol.

The most recent thought that inspired this idea was seeing some of Irad Ortiz's results lately, and it seemed like whenever he was on horses at decent odds they always outperformed expectations, which made me think he really is proving his worth as a top rider. But of course with the simplistic calculation I proposed initially of 0 points at best if you're riding a favorite, a jockey like him who is often on chalk will probably be under-rated in this method. The Wong #'s seemed to be on the right track far as something in a useful vein.

Where the best value lies far as real world application goes I think would be applying this stat to apprentices in their very nascent stages, I feel like if your eyes are open you'll start to see some of those initial longshots running well aren't just flukes & could be the markings of a solid new rider, and you can usually jump on this for a period before word is fully out among the betting public.
both brothers now at GP - larger fields, different distances
Irad has been doing well, and gets more longer priced horses with the full fields
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Old 02-23-2018, 10:42 AM   #24
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Originally Posted by SG4 View Post
I was wondering if any kind of stat or program exists to give jockeys something of a performance expectation rating. What I mean by this is say a jockey is on the 4th betting choice in a race & they finish 2nd, I'd give them a +2 score that race, or if you're on a favorite and finish 5th they'd get a -4 for that race. Wonder if an average score would help identify riders who may be over/underestimated by the betting public, or could possibly help identify upcoming apprentice jockeys as ones to watch.
We've had this in our software for years.

It is based upon what we call PIV - "Pool Impact Value." - When I say "Years," I mean "Decades."

PIV is like the formula for IVs. That is, total wins divided by expected wins...
IV= TotWins/ExWins
ExWins are the sum of 1/FieldSize.

Thus, in a 10-horse field, each horse is "expected" to win 0.10 races.

In a 5-horse field, each horse is "expected" to win 0.20 races.
PIV=TotWins/ExWins

The only difference is that ExWins are determined by the pct of pool wagered on each horse.

Thus, a horse with 40% of the pool is expected to win 0.40 races.

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Old 02-24-2018, 10:20 PM   #25
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I was wondering if any kind of stat or program exists to give jockeys something of a performance expectation rating. What I mean by this is say a jockey is on the 4th betting choice in a race & they finish 2nd, I'd give them a +2 score that race, or if you're on a favorite and finish 5th they'd get a -4 for that race. Wonder if an average score would help identify riders who may be over/underestimated by the betting public, or could possibly help identify upcoming apprentice jockeys as ones to watch.
Been lurking around the forum for a while without contributing, and this post got me thinking. I like the idea, but wanted something that penalized/rewarded runners relative to the rest of the race. Inspired by BIC, and using the public odds, I've come up with:

(ln(p) / sum(ln(pj))) - (ln(1-p) / sum(ln(1-pk))) where p is the runner we're scoring, pj are the runners we've beaten, and pk are the runners to which we've lost.

Looking Race 1 at GP yesterday (2-23-18), the scores would have been:
HTML Code:
Program #     Finish        Public Prob             Score
3                   1              .047               10.73
8                   2              .244               -1.88
2                   3              .065               4.98
1                   4              .057               3.67
4                   5              .047               2.61
5                   6              .244               -20.04
7                   7              .011               2.83
6                   8              .296               -60.29
I plan to use it in a regression to try and determine significance, but so far it seems to capture the idea that the OP is after. Feel free to refine/improve
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Old 02-25-2018, 10:15 PM   #26
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Been lurking around the forum for a while without contributing, and this post got me thinking. I like the idea, but wanted something that penalized/rewarded runners relative to the rest of the race. Inspired by BIC, and using the public odds, I've come up with:

(ln(p) / sum(ln(pj))) - (ln(1-p) / sum(ln(1-pk))) where p is the runner we're scoring, pj are the runners we've beaten, and pk are the runners to which we've lost.

Looking Race 1 at GP yesterday (2-23-18), the scores would have been:
HTML Code:
Program #     Finish        Public Prob             Score3                   1              .047               10.738                   2              .244               -1.882                   3              .065               4.981                   4              .057               3.674                   5              .047               2.615                   6              .244               -20.047                   7              .011               2.836                   8              .296               -60.29
I plan to use it in a regression to try and determine significance, but so far it seems to capture the idea that the OP is after. Feel free to refine/improve

Thanks for coming out of lurking to suggest this - seems to be onto the right path for what I was thinking.

Thanks also to others who followed up. Some of the other ideas which only used winners I don't think fully capture what I was after, I think all finish positions are useful in a review of this nature.
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Old 02-25-2018, 11:30 PM   #27
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As a bettor you do not care a lot about the ability of jockey.

If your interest in horse racing is limited to its gambling alone, the skill of the jockey must be completely transparent to your approach and at no point it should become a central topic in your research and handicapping.

When it comes to jockeys (as in any other handicapping factor) what really matters is not their absolute skill or their classification as better and worse but how these are perceived by the betting public and how this perception is reflected in the betting pools.

Take as an example the following data set which comprises of all the jockeys who have more than 100 starters at more than 8- 1 since 2017 in 'AQU', 'BEL', 'SAR', 'GP', 'SA', 'DMR', 'LRC':

https://gist.github.com/deltalover/4...ee96ed8c6f71b6

Using this table it becomes obvious that Irad Ortiz (ROI 0.79) is certainly inferion to let’s say Aby Medina (ROI 1.08) for betting purposes. My objective as a bettor is not to decide which of the two might be more talented, smart or fit; it is enough to know that the betting crowd is commiting a huge error when estimating the chances of this two, meaning that it is overestimating the ability of Ortiz while simultaneously is underestimating Medina's.
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Old 02-26-2018, 02:23 AM   #28
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Maybe a dumb question. Is there any place where I can download the day's results and put them into my own database?
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Old 02-26-2018, 02:41 AM   #29
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As a bettor you do not care a lot about the ability of jockey.

If your interest in horse racing is limited to its gambling alone, the skill of the jockey must be completely transparent to your approach and at no point it should become a central topic in your research and handicapping.

When it comes to jockeys (as in any other handicapping factor) what really matters is not their absolute skill or their classification as better and worse but how these are perceived by the betting public and how this perception is reflected in the betting pools.

Take as an example the following data set which comprises of all the jockeys who have more than 100 starters at more than 8- 1 since 2017 in 'AQU', 'BEL', 'SAR', 'GP', 'SA', 'DMR', 'LRC':

https://gist.github.com/deltalover/4...ee96ed8c6f71b6

Using this table it becomes obvious that Irad Ortiz (ROI 0.79) is certainly inferion to letís say Aby Medina (ROI 1.08) for betting purposes. My objective as a bettor is not to decide which of the two might be more talented, smart or fit; it is enough to know that the betting crowd is commiting a huge error when estimating the chances of this two, meaning that it is overestimating the ability of Ortiz while simultaneously is underestimating Medina's.
while essentially that may be true, there is still two things out there in the race......a horse AND a rider.
i have always been of the opinion the rider is the more important of the two.
and your chart could be influenced by one or two long priced winners?
not to mention it is very fluid, so it probably looks very different month to month.
or you could have riders that are profitable......depending on how you filter, but you have less than 1.
there is seven zillion ways to analyse it.
you could have a rider with negative expectation, but in the circumstances could be a great bet.
rider IS VERY very important, but it's just one factor.

personally i would never bother analysing a rider the way you have done. it does not work that way.
if all your factors as one give positive expectation then what does it matter if the rider in this case, is a losing proposition according to his/her past history.
you job is to predict the future not the past even if the past may help to an extent.
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Old 02-26-2018, 02:51 AM   #30
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while essentially that may be true, there is still two things out there in the race......a horse AND a rider.
i have always been of the opinion the rider is the more important of the two.
and your chart could be influenced by one or two long priced winners?
not to mention it is very fluid, so it probably looks very different month to month.
or you could have riders that are profitable......depending on how you filter, but you have less than 1.
there is seven zillion ways to analyse it.
you could have a rider with negative expectation, but in the circumstances could be a great bet.
rider IS VERY very important, but it's just one factor.

personally i would never bother analysing a rider the way you have done. it does not work that way.
if all your factors as one give positive expectation then what does it matter if the rider in this case, is a losing proposition according to his/her past history.
you job is to predict the future not the past even if the past may help to an extent.
You are right in the sense that a flat ROI analysis like the one I present here leaves a lot of room of improvement; removing outliers and applying a moving window based on time are two of the ways to do so. More that this though your job is to predict the error in the crowd's estimate and not the most probable outcome of the race; this is the point I am trying to make here.
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Do you bet Justify to win/single on Belmont day or do you spread?
Yes, he's a single and wins Triple Crown. - 22.89%
19 Votes
No, I'm gonna use him but spread - 33.73%
28 Votes
Toss - 39.76%
33 Votes
Doesn't run - 3.61%
3 Votes
Total Votes: 83
Non-members may not vote on this poll.
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