[AusRace] Jockeys generally
L.B.Loveday
lloveday at ozemail.com.au
Tue Jan 29 11:43:45 AEDT 2019
Sean,
I ran my program to count runs per trainer and it took 5 seconds to run - the program was pre-written (by me) and so the only time required on my part is keying "DO ADDTN". (And then COPY & PASTE the output to here). The file of 5 million runs that I extracted the data from was likely in a buffer, so it may take a few seconds longer if I booted up the computer and then ran it as my first job.
But my point is not time to extract, but that there is next-to-zero chance that the 211 unique trainer-names with the surname Smith in my database are discrete people, and the process of determining whether, and when, A Smith is the same trainer as Ms A Smith and, or, Ms Alison Smith (A Smith and Ms A Smith are listed at different times as trainer of the same horses, as are Ms A Smith and Ms Alison Smith - did different people train the horses at different times, or do the 3 names represent 1 discrete person, or 2?) is just a bridge too far for me, and the alternatives are to run with all-but certain wrongly-derived statistics or leave trainers out of the rating process:
A D Smith 359
A F Smith 80
A J Smith 58
A L Smith 66
A Smith 198
B B Smith 56
B G Smith 432
B J Smith 458
B M Smith 70
B S Smith 129
B Smith 3324
Ben Smith 538
Bob Smith (rj) 1
Brad Smith 409
C G Smith 126
C L Smith 2565
C P Smith 12
C Smith 2167
Colin Smith 155
Craig Smith 2876
D P Smith 4892
D S Smith 596
D Smith 313
Damien Smith 17
Dane Smith 542
David A Smith 251
David J Smith 190
David Smith 249
David W Smith 81
F E Smith 1149
F J Smith 183
Francis Smith 28
G C Smith 1248
G D Smith 5
G M Smith 1
G Smith 46
Gareth Smith 309
Garry Smith 30
Geoff Smith 39
Gregory Smith 44
H J Smith 281
J A Smith 524
J B Smith 2470
J C Smith 112
J E Smith 65
J L Smith 197
J Smith 33
Jeremy Smith 399
K C Smith 489
K L Smith 267
K M Smith 47
K N Smith 511
K R Smith 459
K Smith 68
K T Smith 524
Kelvin Smith 558
L A Smith 115
L C Smith 88
L J Smith 1010
L R Smith 77
L Smith 4368
Les Smith 86
M J Smith 1259
M K Smith 260
M Smith 624
M W Smith 281
Marilyn Smith 3
Matthew Smith 2552
Max Smith 50
Melissa Smith 2
Ms A J Smith 2
Ms A Smith 1836
Ms Alison Smith 1829
Ms C Smith 34
Ms D Smith 360
Ms F Smith 167
Ms H Smith 93
Ms J M Smith 140
Ms J Smith 263
Ms K Smith 6
Ms L C Smith 540
Ms L Smith 80
Ms M Smith 241
Ms R Smith 70
N T Smith 70
O R Smith 46
O Smith 5
P A Smith 243
P J Smith 24
P R Smith 7
P Smith 364
Paul Smith 763
Peter Smith 1016
R G Smith 67
R J Smith 147
R K Smith 107
R L Smith 154
R R Smith 52
R Smith 202
Rochelle Smith 944
Ronald Smith 41
Russell Smith 30
S G Smith 72
S J Smith 3
S L Smith 224
S M Smith 258
S Smith 88
T A Smith 6
T J Smith 313
T Smith 140
T T Smith 54
Trevor J Smith 11
From: Racing <racing-bounces at ausrace.com> On Behalf Of sean mclaren
Sent: Tuesday, 29 January 2019 2:06 AM
To: AusRace Racing Discussion List <racing at ausrace.com>
Subject: Re: [AusRace] Jockeys generally
hello again
ignore the final column called Runs.
i had not cross checked.
the initial query for Dec 18 generated 16460 runs for trainers nationally.
the smiths were extracted as a sub set.
thanks
On Tue, Jan 29, 2019 at 12:49 AM sean mclaren <seanmac4321 at gmail.com <mailto:seanmac4321 at gmail.com> > wrote:
trainer
state
runs
A D Smith
NSW
5
A D Smith
WA
1
B J Smith
QLND
11
B S Smith
NSW
3
B Smith
QLND
3
C Smith
QLND
35
D J Smith
NSW
1
D S Smith
NSW
5
D Smith
NSW
2
D Smith
VIC
18
F E Smith
QLND
5
G Smith
QLND
2
J Smith
NSW
2
K Smith
NSW
1
L Smith
WA
3
M J Smith
ACT
6
M Smith
NSW
16
Ms A J Smith
WA
3
Ms A Smith
NSW
8
Ms J Smith
VIC
1
P A Smith
NSW
2
P Smith
NSW
1
P Smith
VIC
1
R G Smith
WA
3
R Smith
NSW
22
S L Smith
NSW
6
hello Len
national Dec 2018 numbers for the unique Smiths.
35 mins. total
near 10 mins waiting for the query. Export to excel. Query, Sort, Format count etc etc
i can offer no further comment.
Thanks Sean
On Mon, Jan 28, 2019 at 12:50 PM L.B.Loveday <lloveday at ozemail.com.au <mailto:lloveday at ozemail.com.au> > wrote:
Easily via tables BUT " Agreed the work upfront is a tough but not insurmountable". Tough indeed.
Even with top trainers, I have problems as discussed earlier:
D Hayes
D J Hayes
D & B Hayes & T
David Hayes
David Hayes & To
D, B & T Hayes &
G Waterhouse & A
Ms G Waterhouse
G & A Waterhouse
WORSE, in a complementary data-base separately sourced, for only the last 8 years, I have additionals:
DHayes
D&BHayes
and:
GWaterhouse
G&AWaterhouse
MsGWaterhouse
Then what about this tiny non-random sample of 43 trainers out of the 11,421 I have in my current (non-archived) data base?
A D Smith
A F Smith
A J Smith
A L Smith
A Smith
Ms A J Smith
Ms A Smith
Ms Alison Smith
J A Smith
J B Smith
J C Smith
J E Smith
J L Smith
J Smith
Jeremy Smith
Ms J M Smith
Ms J Smith
K C Smith
K L Smith
K M Smith
K N Smith
K R Smith
K Smith
K T Smith
Kelvin Smith
Ms K Smith
L A Smith
L C Smith
L J Smith
L R Smith
L Smith
Les Smith
Ms L C Smith
Ms L Smith
M J Smith
M K Smith
M Smith
M W Smith
Marilyn Smith
Matthew Smith
Max Smith
Melissa Smith
Ms M Smith
I can't be bothered looking up how many additionals there are in the complementary 8-year file.
How long do you figure it would take to be 99% sure you had determined how many unique trainers are in the 43 names (and of course thus form a tiny part of the required table)?
Then do the same for at the other 11,378 names? Then match to the 8-year file?
From: Racing <racing-bounces at ausrace.com <mailto:racing-bounces at ausrace.com> > On Behalf Of sean mclaren
Sent: Monday, 28 January 2019 8:54 AM
To: AusRace Racing Discussion List <racing at ausrace.com <mailto:racing at ausrace.com> >
Subject: Re: [AusRace] Jockeys generally
And I should add that names of jockeys or trainers can be easily overcome in excel via look-up tables or in access via a table. The fuss escapes me. Agreed the work upfront is a tough but not insurmountable. The challenge for mine is placing a value on a jockey or a trainer that's in sync with the scale of my type of performance rating. Which is why leaving them in their raw state, as Roman does, is still quite appealing. Apart from its simplicity, it shouldn't be ignored that a degree of randomness is created by default and in a chaotic space (ie a horse Race) that could translate into better prices because of unfashionable jockeys / trainers. Just some thoughts.
On Sun, 27 Jan 2019 13:55 Tony Moffat <tonymoffat at bigpond.com <mailto:tonymoffat at bigpond.com> wrote:
Roman – my response to Len wasn’t intended as having a shot at you, and your assertion, but more to show that the values were aligning, at least in the case of SGuymer and his 115/1.15.
Personally, I like to involve the exposed values of runners engaged in the upcoming race and minimize, if I can, the magical addings/dividings/other things needed to construct a rank.
Let’s call it evidence based handicapping.
I do use the market – firstly, if you divide the place dividend by the win dividend and rank the result you can see at a glance those runners which have a disproportionate sum plonked for the win – my cut off value is 41% - the place dividend is 41% of the win, which is the ‘normal’ range for most out to $9, then the place div % falls away, the longer divs out there in the badlands are being bet/hunted by somebody.
Caulfield R7 yesterday – the one runner over 41% is 4AlGayel 48% from $1.5/$2.5 – skinny I know but you get the gist.
Caulfield R8 yesterday – the one runner over 41% is 8Manolo 50% from $1.4/$2.8 – skinny etc.
Randwic R9 yesterday - there are two selections over 41% - 1ST and 2ND $1.80/$1.5
Randwic R8 yesterday - the one runner over 41% is 8Sondelon 42% from $1.4/$3.3
Randwic R7 yesterday - there are two selections over 41% - Unp and Unp – so it is not perfect.
Randwic R6 yesterday - the one runner over 41% is 8Sei Stella 58% from $1.5/$2.6
SunCoast R8 yesterday- the winner was ranked 11, the 2nd was ranked 4, and the 3rd was ranked 10th
So it is not perfect.
See the story of JIM, Jim and jim about scoring off these types of bets. jim (all lowercase) has been known to move
$1k on these until he accumulates his daily take – it was $1700 – and never less than $1k if the pool is large (enough)
I rank the quinella dividends then countif those runner numbers involved in the first 10 – this may include up to 5 or more horses.
My feeling was that, when I commenced doing that, that astuteness from others caused them to select their bets and I could benefit from that.
Those other punters had made an effort I considered, in isolation though. Now the inclusion of flexi betting has affected that a lot but it still
‘seems to be’ a good strong lead. You need access to a matrix, not always allowed now.
I can do it with exacta divs as well – it is much of a muchness.
All of the data above was from final dividends. In the sometimes frantic betting scene before a race, with data changing 3 times a second, you have to take a stab occasionally, and to hope that your selection holds it’s value, they normally do.
Cheers]
Tony
From: Racing [mailto:racing-bounces at ausrace.com <mailto:racing-bounces at ausrace.com> ] On Behalf Of Roman
Sent: Friday, January 25, 2019 5:51 AM
To: 'AusRace Racing Discussion List' <racing at ausrace.com <mailto:racing at ausrace.com> >
Subject: Re: [AusRace] Jockeys generally
Hi Tony,
I respect the fact you have your way that works for you as Sean has his. That’s how the punt goes for those keen enough to go past “pluck a duck” with a cursory ten minute look or listen to various tipsters.
The one constant I can quote is that the racetrack market is what I call “linear”. I assume that’s the correct term where I mean favs win more times than 2nd favs who win more than 3rd favs and so on. Thus the SP figure is linear in that $2.50 chances win more than $4 chances who win more than $7 chances and so on. I am sure we all agree that this general premise is correct in the high 90’s percentage wise.
Therefore, the rating of jockeys and trainers can be aligned to this premise and their LOT or POT should give a reasonably clear picture of whether they are up to the market assessment. Where this can go asunder a fraction is that top trainers runners are overbet by a lazy public who think the likes of Waller Hayes and Weir can train every favourite to win. As most on this site realise many of their horses are “unders”. Nevertheless that can be factored in.
In the file I have DKWeir 7516 runners for minus 23.8%LOT, D Hayes 4710 for -17.6% LOT however at $3 or less Weir 1053 runners for -5.1% whilst Hayes with 529 runners is -11.2%.
So, if betting all odds, as I assume you do, you would use the larger set you would credit Hayes with more points. The favs punters would give DKW a better figure.
These figures are, of course, open to all sorts of personal interpretation if I add that overall from 7513 runners at $3 or less covering all trainers the LOT is 8.1%. I am not sure but would 5.1 divided by 8.1% give a figure or should it be vice versa.
Naturally, a similar process for jockeys would find some riders of $3 or less chances, for instance, better than others. From there some jockey/trainer combos would be another facet i.e. Yendall/Weir, Allen/Weir, Bowman/Waller et al but a downside for some combos would be not enough runs.
However, all said above is just one way!!
Cheers
Roman
From: Racing [mailto:racing-bounces at ausrace.com] On Behalf Of Tony Moffat
Sent: Friday, January 25, 2019 1:59 AM
To: racing at ausrace.com <mailto:racing at ausrace.com>
Subject: Re: [AusRace] Jockeys generally
Len – thanks
Kozzi’s assertion that the iv are poles apart does not hold up here – I have similar scores to yours. I leave mine at 1.15 for Guymer and you promote him by multiplying by a hundred (de-decimate?) to get 115 (I guess).
I wanted a score in the here and now and that is how/why I came to derive the iv, it is contemporaneous with other riders in this race, their presence affects its score somewhat, a little, and never majorly. It is not uniquely mine, by the way. It involves the use of all the placings, I had included the win record only, then added second place(s) to see how that ran and have reverted to this input now.
My calculations are in the mould of ‘ok, what can you do’, looking forward, and others can be described as ‘look what I done’.
The inclusion of performance at price bands might be the best but I don’t have that data, the prices of past endeavors. I can access it, the prices, but choose not to manually enter it, and who would do that.
Yes, I do iv for jockeys (as you know) and also trainer, horse, distance and form and multiply these to get a value for each runner – highest is best.
Form is a two part process. I involve their last 4 runs by multiplying the places together, remove the worst result, then rank that – this appears to be strong information, and has always been.
As a factor in a weight rating process used, I again involve their places but this time I start from a base of 9 (the worst there can be) then subtract each succeeding run from the previous product until I get a score from which I can calculate a rating to win. So 6214, comes out as -3,-4,-1,3 and when summed this is -3+-4+-1+3 = -5. The -3(minus three) came from 6-9 = -3, the -4 (minus 4) came from 6-2 = -4, the -1 (minus 1) came from 2-1 =-1, and the (+)3 came from 4 minus 1 = +3. The -5 for this runner, and the calculated scores for all runners is then multiplied by 1.5 to give a weight rating variation and this product is then added to the limit weight for this race and the allocated weight deducted from that. The best result, the highest/biggest number resulting from that is considered the best for this race, and you can zero that against the other calculated weights to sort out the weight rated best ranking.
I use a variation of this method in my own punting, having streamlined a few of the calculations, but the principles are the same, and the selections also. I back more than one runner in each chosen race, often a quinella now, and for several years, with a saver on some of the quinella inclusions.
I don’t use or include the iv selections in my punting yet, I may do soon, and include it here only for information and comment.
Cheers
Tony
FROM THE ARCHIVES
From: ausrace-bounces at ausrace.com <mailto:ausrace-bounces at ausrace.com> [mailto:ausrace-bounces at ausrace.com] On Behalf Of Nick at Twonix
Sent: Thursday, 5 November 2015 1:29 PM
To: 'AusRace Mailing List' <ausrace at ausrace.com <mailto:ausrace at ausrace.com> >; 'L.B.Loveday'
<lloveday at ozemail.com.au <mailto:lloveday at ozemail.com.au> >
Subject: Re: [AusRace] Michelle Payne
I did an analysis of 271 K Aus races rides over last 2-3 years and discovered that Male jockeys have a 2% better strike rate and a 3% better A2E (think POT betting to prices).
However Apprentices ( both Male and Female) have the same Strike Rate and A2E . Licensed Male jockeys have a 6% better A2E compared to Female jockeys.
Category Rides Wins S/Rate ExpW
A2E
Aus Races 271,662 35,340 13% 40,474 -13%
Female 40,478 4,626 11% 5,448 -15%
Apprentice 21,840 2,549 12% 2,930 -13%
Licensed 18,638 2,077 11% 2,518 -18%
Male 231,184 30,714 13% 35,026 -12%
Apprentice 54,329 6,789 12% 7,840 -13%
Licensed 176,855 23,925 14% 27,186 -12%
AN
Len, I was able to distinguish Female jockeys in AAP data as they all start with "Ms ". I am assuming that MS Dhoni doesn't ride in Aus :-)
From: Racing [mailto:racing-bounces at ausrace.com] On Behalf Of L.B.Loveday
Sent: Tuesday, January 22, 2019 9:50 AM
To: 'AusRace Racing Discussion List' <racing at ausrace.com <mailto:racing at ausrace.com> >
Subject: Re: [AusRace] Jockeys generally
"Raw wins and wins and placings" don't mean much in absence of prices - it's easy to back winners; just back every runner at 1/1 or less and you'll back around 56% of winners, and "just" lose about 5.5%.
Nor is just looking at past returns enough - factors such as those you list, and eg, track, trainer should be considered.
Here's a simplistic look at some figures that could be used:
Considering the last 1000 rides for jockeys who have had at least 1000 rides in the past 14 years (a somewhat different picture arises if only considering since the advent of SOP rather than traditional SP as SOP markets have lower market%s, especially away from Sydney/Melbourne tracks):
Best returns @ SP:
SThornton 101
MJWalker 103
WD'Avila 103
CParnham 104
VWong 104
DMoor 105
PWells 105
DWBallard 107
SFawke 113
SGuymer 115
JOliver 117
Considering only rides on horses "in the market" - gets rid of outliers like 125/1 winners:
JPStanley 100
JPracey-Holm 100
JTaylor 100
MWeir 100
RFradd 100
RonStewart 100
KWalters 102
SLisnyy 102
LJMeech 103
TPannell 103
CGallagher 104
RMaloney 106
CHall 107
BWerner 108
DWBallard 108
JLyon 109
PWells 109
SThornton 109
CNutman 110
VBolozhinsky 112
Worst returns @SP:
LGHenry 21
JeffKehoe 31
DPitomac 33
TJeffries 33
SBayliss 34
JMissen 36
MJStephens 37
ABadger 38
NRose 38
SStarley 38
ECockram 39
JKeating 39
MHackett 39
RYetimova 39
SParnham 39
Considering only rides on horses "in the market" (as I've previously said LGHenry is in a class of her own):
LGHenry 27
MJStephens 32
SBayliss 36
CBryen 41
JMissen 43
SGalvin 45
SStarley 45
ABadger 46
DPitomac 46
BPowell 47
MHackett 47
SParnham 47
BStower 48
PaulPayne 49
CQuilty 50
The big gaps - All "in market"
SFawke 113 79
WD'Avila 103 75
MJWalker 103 76
JOliver 117 91
BMertens 88 63
JTaylor 69 100
NPunch 60 95
JeffKehoe 31 72
SLisnyy 61 102
CHall 66 107
VBolozhinsky 70 112
From: Racing <racing-bounces at ausrace.com <mailto:racing-bounces at ausrace.com> > On Behalf Of Roman
Sent: Monday, 21 January 2019 9:34 PM
To: 'AusRace Racing Discussion List' <racing at ausrace.com <mailto:racing at ausrace.com> >; tonymoffat at bigpond.com <mailto:tonymoffat at bigpond.com>
Subject: Re: [AusRace] Jockeys generally
Hi all,
The fascination of it all is that two raters could have the same jockey literally poles apart depending on criterias chosen.
I have never rated jockeys nor trainers as I wonder if there is all that much between a number of them at the top level. If the SP figures is a solid determinant of the overall structure of horse racing does it not figure those jockeys that ride well on well fancied horses are giving the horses the chance of winning the market determines. Say Jockey A has 100 rides in races in town on favs and scores 35% of the time is he not a fraction better than Jockey B who rides 32%. So the next time the two jockeys meet on say favs at 2/1 and 9/4 (close) but the 32% jockey rides an on pacer and the 35% jockey rides a chronic get back type where does the ratings look now. It would be best to rate them all on their ability with leaders, on pacers, mid fielders and get back types and another set of figures comes up far more accurate, imho, than just a raw wins and wins and placings.
I look forward to Len’s reply.
Roman Koz
From: Racing [ <mailto:racing-bounces at ausrace.com> mailto:racing-bounces at ausrace.com] On Behalf Of L.B.Loveday
Sent: Monday, January 21, 2019 6:12 PM
To: <mailto:tonymoffat at bigpond.com> tonymoffat at bigpond.com; <mailto:racing at ausrace.com> racing at ausrace.com
Subject: [AusRace] Jockeys generally
Tony,
Did not get to me and I just saw it in the archives - a very different rating method to mine; I'll evaluate and comment anon.
LBL
790*150-93-96 is the revealed racing stat for Linda Meech tomorrow - to
expand this Ms Leech has had 790 rides for 150 wins in the time frame
covered by this stat. My IV for that is 1.4, essentially she is 40% advanced
on some others in this race.
No rider gets less than 1, although the calculation is often less than
that, John Keating has .6 (scores a one in the scheme). Why? - he is on a
horse in the race and Bradbury's have happened, although I use the 1 for
statistical pureness, and to get rid of some decimals. To be factual, off a
calculation, Keating is somewhere like 80% more unlikely of producing a good
ride than Meech - he has 395*17-25-33 and is .6 against Meech at 1.4 (1.4 -
.6 is the basis of the claim for 80%).
Jason Maskiell is also on 1.4 in this race, off 347*54-46-41. The factor is
0.300552251 (the average of all jockeys riding) and my fall back value is
.31 - if a jockey can't be rated (the data is missing e.g.) then I assign
that value to it early in the calculation.
Roger Biggs wrote that he used .2595, which may be the statistical base of
all jockey placings across many rides. This has changed somewhat, there is a
jockey db. on RB Ratings. I am unaware of another method to rate and rank
jockeys against all their rides. They can only ride one horse in a race so
that the iv concocted from a large number of rides seems to be correct, and
I total all the rides for all jockeys in the race then divide that into all
the places achieved by all the jockeys, and from that sub-total I
individually determine an iv.
There is a place system for ranking jockeys when on favorites, but that is
not the jockey at all. Another time perhaps. Who likes, or wants, dividends
in the sub $2 range, most of us really.
This upcoming race has riders which have achieved 4708 rides totally under
the period of review, and of those rides those riders scored, placed, in
1415. So, 1415/4708 = .300552251 is the factor to be used. Individually
Keating has 395*17-25-33 (17+25+33/395 = .1898734) and this product is again
divided by the total score .3005522512 to give the score of .6. These
numbers seem minimal, mickey mouse almost, but are a significant part of the
overall stat picture
Trainers may have two or more runners in the race. I score them the same as
jockeys, total rides into total places (123) and develop a iv score from
that.
Involving riders and trainers, getting a score from them combined, I
multiply their ivs and work with the product, ranking that.
Meech 1.4, trainer 1.3 (1.4 * 1.3 = 1.82)
Keating 1, trainer 1 (1 * 1 =1) actually .6 * .1. The trainer is yet to win
a race
Maskiell 1.4, trainer 1 (1.4 * 1 = 1.4.
Dylan Dunn = 1.1
There is some upside to Linda Meech ability, trainer ability.
This is R2 Kyneton tomorrow, a maiden and I'm not betting
in it, nor do I suggest you do.
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