Dave
Gelding
Those of you who use sectional data on the AW may find this worth reading.
Most of you reading this will be aware that I wrote a book earlier this year on All-Weather racing — built around pace, draw, race shape and sectional interpretation. Recently I've been building a research database from RaceIQ data: 20,693 runners across 2,407 races, all six UK AW tracks, covering the best part of two years.
I've now used that database to formally audit ten of the principal claims from the book. I'm sharing the results in a new series on Hidden Performances.
The findings that I think will interest people here:
Pace shape and running style interaction: the database confirms that even-pace conditions produce front runner win rates of 37-44% at sprint distances. But in slow-fast conditions those same front runners drop to 6-7%. The gate speed metric (0-20mph) maps to first-furlong position with surprising consistency — Rank 1 gate speed produces a front runner 54% of the time.
The draw reversal problem: draw bias at AW tracks is not fixed. At Kempton 6f, mid draw outperforms in even-pace (15.8%) but underperforms in slow-fast (7.0%), while low draw reverses. This pattern appears across multiple courses and distances. Any draw system that doesn't account for projected pace shape is working with incomplete information.
The 479 trapped closers: the database identified 479 horses that produced a C2F Move of +4 or more in even-pace races but didn't win. 89% of horses showing that profile in even-pace conditions lost. In slow-fast conditions the equivalent figure produced winners 34% of the time. Whether those specific horses represent a quantifiable angle in their next race is the question I'm now investigating with the full dataset.
Newcastle — where I had to revise my original view: the book suggested hold-up horses were more viable at Newcastle. The data doesn't support it in the simple way I wrote it. The differences that do exist appear to be explained by Newcastle's specific draw and pace interaction patterns rather than a general hold-up bias.
The following is the full article :
There is a problem with writing a book about horse racing.
You can watch racing for decades.
You can develop theories.
You can see patterns that appear to repeat themselves.
You can test ideas yourself.
And eventually, you can become convinced that you have found something that works.
But there is a very obvious question.
What if you’re wrong?
That question has been sitting in the back of my mind since I published my book on All-Weather racing.
So rather than simply tell readers that the ideas in the book work, I decided to do something much more uncomfortable.
I put the book itself to the test.
Not against a handful of races.
Not by selecting examples that happened to support the theory.
But against almost two years of All-Weather racing.
The database contains 20,693 runners across 2,407 races, covering all six UK All-Weather tracks.
And I have tested ten of the principal claims and ideas contained within the book.
The objective was simple:
Find out what stands up.
And just as importantly:
Find out what doesn’t.
The Book Behind the Research
For those who don’t know, I wrote UK All-Weather Racing: A Specialist’s Guide to Finding Value on the All Weather.
It is deliberately a niche book.
I’ve spent many years studying All-Weather racing, and the book brings together the approach I developed from watching the racing, analysing results and trying to understand why certain horses and certain race situations repeatedly produced better opportunities than others.
It isn’t intended to be another conventional form book.
The approach is built around understanding how an All-Weather race is likely to unfold.
Pace.
Position.
Draw.
Race shape.
Speed.
Finishing performance.
Race quality.
Class.
And increasingly, sectional data.
When I wrote the book, these were my observations and theories.
I believed they had substance. I knew from my personal betting records that I had made a profit following the principles laid out in the book
But belief and betting records aren’t necessarily proof.
And now I have something I didn’t have when I first wrote the book.
A research database large enough to test them.
Thanks for reading Hidden Performances! Subscribe for free to receive new posts and support my work.
The Ten Claims
I selected ten of the major claims or principles from the book and asked whether the historical data supported them.
They were:
1. Early pace and position matters most
Front runners should be structurally favoured on sharp All-Weather tracks, particularly when the race is likely to be genuinely run.
2. Hold-up horses are riskier
Especially in All-Weather sprints, horses ridden well off the pace face a structural disadvantage.
3. Vs.Par and Time Index matter
These are among the most useful RaceIQ indicators for assessing the underlying quality of a performance.
4. FSP% above 102% is significant
A strong finishing-speed figure can identify horses that have finished better than the bare result suggests — but only when interpreted in the context of the pace of the race.
5. Draw cannot be viewed in isolation
The value of a draw depends upon the interaction between draw, pace and running style.
6. Newcastle is different
The course has characteristics that make its race shape and positioning dynamics different from the other UK All-Weather tracks.
7. Strong-race class droppers can provide value
A horse coming out of a genuinely strong race and dropping in class can represent a particularly interesting opportunity.
8. Some winners are false winners
A horse can win without producing a performance that should necessarily be trusted next time.
9. Stride and biomechanics matter
Physical performance indicators such as stride length may contain information about a horse’s underlying ability.
10. Trainers target certain races
Some trainers appear to perform particularly well when targeting stronger races.
Ten claims.
One database.
No cherry-picking.
So What Did We Find?
The first thing I want to make clear is that I am not going to pretend that every statement in the book has been proven correct.
That would defeat the purpose of doing this research.
Some claims have been strongly supported.
Some have been confirmed but require qualification.
And one in particular has not been confirmed in the simple way I originally thought.
I actually think that makes the results more interesting.
Because if I had simply gone into the database looking for evidence that everything I had written was right, this would be little more than confirmation bias dressed up as research.
That’s not what I want Hidden Performances to become.
Claim One: Early Pace Matters
Strongly confirmed
One of the fundamental arguments in the book is that early pace and position are enormously important on the All-Weather.
The database provides some striking evidence.
In Even-pace 6f races, front runners won at:
43.8%
Hold-up horses?
0.2%
That’s from 417 hold-up runners.
At 5f Even pace, front runners won at 39.3%, while hold-up horses won at just 0.4%.
At 7f Even pace, the front-runner figure was 37.7%.
At 1m it was 31.5%.
Those aren’t marginal differences.
They are structural.
But there is a crucial second part to the story.
Because when the race becomes Slow-Fast, the picture changes dramatically.
At 5f:
Front Runners — 7.0%
Mid-Pack — 20.4%
At 6f:
Front Runners — 6.3%
Stalkers — 17.2%
At 7f:
Front Runners — 5.5%
Stalkers — 15.1%
So the conclusion isn’t simply:
Position matters. But what the pace does to that position matters just as much.
That is something the database has allowed me to understand much more clearly.
The 0–20mph Discovery
One of the most interesting findings concerns the RaceIQ 0–20mph metric.
The fastest horse from the stalls — Rank 1 — became a front runner 54% of the time.
The fifth-fastest gate horse became a front runner just 17% of the time.
The relationship is remarkably clear.
0–20mph Rank 1st
Front Runner: 54%
Hold-Up: 7%
0–20mph Rank 2nd
Front Runner: 41%
Hold-Up: 10%
0–20mph Rank 3rd
Front Runner: 32%
Hold-Up: 13%
0–20mph Rank 4th
Front Runner: 22%
Hold-Up: 20%
0–20mph Rank 5th
Front Runner: 17%
Hold-Up: 28%
This gives us something potentially very useful.
Rather than relying solely on a horse’s historical run-style designation, we can look at its actual ability to get out of the stalls quickly.
The data suggests that gate speed is a major component of how the field sorts itself during the opening stages.
That gives another layer to the race-shape analysis.
The Two-Phase Race
Another finding from the research particularly interested me.
The book discusses races in terms of two broad phases.
Phase 1
Getting a position.
Phase 2
Efficiency, stamina and finishing.
The database allowed this to be quantified.
Across all All-Weather races:
32% of winners were Phase 1 positional winners.
67% gained positions during the closing stages.
At first glance, that might appear to contradict the emphasis on early position.
It doesn’t.
Because the pace shape determines which phase becomes decisive.
In a Slow-Fast race, the horses that conserve energy for the finishing phase can make up significant ground.
In an Even-pace race, there is far less opportunity to do that.
And this produces one of the most important principles emerging from the research:
But the data shows just how important it is.
The 479 Horses That Finished Fast — And Still Lost
This was another finding I found particularly fascinating.
The database identified 479 horses that gained four or more positions during the final two furlongs of Even-pace races but still failed to win.
These are horses that produced a significant late move.
Yet they couldn’t overcome the disadvantage created earlier in the race.
In other words:
**They finished strongly.
But they finished strongly too late.**
That creates a potentially interesting future research angle.
If one of these horses subsequently finds itself in a Slow-Fast race, where early energy conservation becomes more important and the finishing phase becomes more decisive, does its previous run become a positive signal rather than a negative result?
That is exactly the type of question the research database now allows me to investigate.
And it wasn’t something I set out to prove when I wrote the book.
The data has taken the research somewhere new.
Claim Two: Hold-Up Horses Are Riskier
Confirmed
The evidence here is exceptionally strong.
In Even-pace sprints, hold-up horses were almost completely shut out.
At 5f and 6f, there were multiple course-and-distance combinations where the historical win rate was effectively zero.
But again, the pace qualification matters.
When races become Slow-Fast, hold-up horses become much more competitive.
So once again, the book’s underlying principle survives — but the database gives us a much more precise definition.
It isn’t:
Claim Five: Draw Only Makes Sense in Context
Strongly confirmed
This is another area where the data has been particularly revealing.
I’ve always been wary of simplistic draw systems.
“Low is good here.”
“High is good there.”
Those statements can be dangerously misleading.
The database found numerous examples where the draw advantage reversed depending upon the pace shape.
Kempton 6f provides an excellent example.
In Even-pace races:
Low draw — 8.6%
Mid draw — 15.8%
But in Slow-Fast races:
Low draw — 15.2%
Mid draw — 7.0%
Same course.
Same distance.
Different pace.
Different draw result.
The research therefore strongly supports one of the book’s central ideas:
Draw isn’t a standalone variable.
It is part of the race shape.
And Then There Was Newcastle...
This is where the audit became particularly useful.
I wrote that Newcastle was different and that hold-up horses were more viable there.
The database didn’t completely support that.
At sprint distances, Newcastle hold-ups were slightly better than elsewhere.
But the difference wasn’t large enough to justify the stronger claim.
At some longer distances, they actually underperformed.
So this is one area where I have had to refine my original thinking.
Newcastle does appear to have distinctive characteristics.
But the research suggests those differences are more closely related to the interaction between pace, draw and positioning than simply saying:
But it matters.
And this is precisely why I wanted to carry out the audit.
So Does the Book Stand Up?
After testing the ten claims, my overall conclusion is encouraging.
But I don’t want to oversell it.
The research broadly supports the underlying framework.
Several of the central principles have been strongly confirmed.
Others have been confirmed but with important qualifications.
And some need more work before I would describe them as proven betting angles.
That distinction is important.
Because supporting a theory isn’t the same as proving profitability.
A horse category might produce a 20% strike rate.
That doesn’t tell us whether backing those horses at their historical prices would have produced a profit.
Likewise, identifying a trainer who wins more frequently in stronger races doesn’t automatically create a betting edge.
To establish that, we need to test:
The Book Was the Hypothesis
This is probably the most important point I want to make.
When I wrote the book, I wasn’t starting with a giant database and building a theory around the results.
Much of the thinking came from years of watching All-Weather racing and trying to understand what was happening beneath the surface.
The RaceIQ data then gave me a way of understanding and testing those observations.
Now, with almost two years of comprehensive results captured, I can finally ask a much harder question:
Was I actually seeing something real?
The early answer is:
In many cases, yes.
But the database has also shown me where the original ideas need refining.
And I think that is exactly what good research should do.
It shouldn’t simply confirm what you already believe.
It should make your understanding more accurate.
This Is Only Part One
The All-Weather season is, of course, continuous.
But we’re now in the quieter part of the year.
There are still AW races being run, but the volume is relatively low compared with what is coming.
By September and October, the AW programme begins to build significantly again.
That gives me an opportunity.
Rather than simply writing more articles telling you what I think, I’m going to use this period to dig much deeper into the research database.
This is going to become a series.
The next articles will take individual chapters and concepts from the book and put them under the microscope.
We’ll look at the evidence.
We’ll look at where the book was right.
We’ll look at where it needs qualification.
And where possible, we’ll go beyond simply asking whether something works and start asking the question that really matters to anyone betting:
Does it actually make money?
Part Two: Coming Soon
The next article will take a much deeper look at race shape, pace and the first part of the race.
In particular, I’ll be looking at the relationship between:
0–20mph
draw
running style
pace shape
position
and what I am calling the two-phase model of an All-Weather race.
And there is one particular group of horses that has emerged from the research that I think could be very interesting:
Horses that finished strongly, gained significant ground late — but were beaten because they had given away too much ground earlier in the race.
There are 479 of them in the current research.
The question is whether their next race can provide the conditions that their previous race didn’t.
That’s where the research gets particularly interesting.
If You Haven’t Seen the Book
For those who have followed Hidden Performances for a while, you may already know that I wrote a book specifically about All-Weather racing.
For anyone discovering my work through this article, the book is:
UK All-Weather Racing: A Specialist’s Guide to Finding Value on the All Weather
It is the original source of many of the ideas being tested in this research series.
I’m deliberately not going to turn these articles into advertisements for the book.
I’d much rather let the research speak for itself.
But if you want to see where these ideas originally came from, you can find the book here: UK All-Weather Racing: A Specialist's Guide to Finding Value on the AW: Amazon.co.uk: Watts, Dave: 9798242338234: Books
Most of you reading this will be aware that I wrote a book earlier this year on All-Weather racing — built around pace, draw, race shape and sectional interpretation. Recently I've been building a research database from RaceIQ data: 20,693 runners across 2,407 races, all six UK AW tracks, covering the best part of two years.
I've now used that database to formally audit ten of the principal claims from the book. I'm sharing the results in a new series on Hidden Performances.
The findings that I think will interest people here:
Pace shape and running style interaction: the database confirms that even-pace conditions produce front runner win rates of 37-44% at sprint distances. But in slow-fast conditions those same front runners drop to 6-7%. The gate speed metric (0-20mph) maps to first-furlong position with surprising consistency — Rank 1 gate speed produces a front runner 54% of the time.
The draw reversal problem: draw bias at AW tracks is not fixed. At Kempton 6f, mid draw outperforms in even-pace (15.8%) but underperforms in slow-fast (7.0%), while low draw reverses. This pattern appears across multiple courses and distances. Any draw system that doesn't account for projected pace shape is working with incomplete information.
The 479 trapped closers: the database identified 479 horses that produced a C2F Move of +4 or more in even-pace races but didn't win. 89% of horses showing that profile in even-pace conditions lost. In slow-fast conditions the equivalent figure produced winners 34% of the time. Whether those specific horses represent a quantifiable angle in their next race is the question I'm now investigating with the full dataset.
Newcastle — where I had to revise my original view: the book suggested hold-up horses were more viable at Newcastle. The data doesn't support it in the simple way I wrote it. The differences that do exist appear to be explained by Newcastle's specific draw and pace interaction patterns rather than a general hold-up bias.
The following is the full article :
There is a problem with writing a book about horse racing.
You can watch racing for decades.
You can develop theories.
You can see patterns that appear to repeat themselves.
You can test ideas yourself.
And eventually, you can become convinced that you have found something that works.
But there is a very obvious question.
What if you’re wrong?
That question has been sitting in the back of my mind since I published my book on All-Weather racing.
So rather than simply tell readers that the ideas in the book work, I decided to do something much more uncomfortable.
I put the book itself to the test.
Not against a handful of races.
Not by selecting examples that happened to support the theory.
But against almost two years of All-Weather racing.
The database contains 20,693 runners across 2,407 races, covering all six UK All-Weather tracks.
And I have tested ten of the principal claims and ideas contained within the book.
The objective was simple:
Find out what stands up.
And just as importantly:Find out what doesn’t.
The Book Behind the Research
For those who don’t know, I wrote UK All-Weather Racing: A Specialist’s Guide to Finding Value on the All Weather.It is deliberately a niche book.
I’ve spent many years studying All-Weather racing, and the book brings together the approach I developed from watching the racing, analysing results and trying to understand why certain horses and certain race situations repeatedly produced better opportunities than others.
It isn’t intended to be another conventional form book.
The approach is built around understanding how an All-Weather race is likely to unfold.
Pace.
Position.
Draw.
Race shape.
Speed.
Finishing performance.
Race quality.
Class.
And increasingly, sectional data.
When I wrote the book, these were my observations and theories.
I believed they had substance. I knew from my personal betting records that I had made a profit following the principles laid out in the book
But belief and betting records aren’t necessarily proof.
And now I have something I didn’t have when I first wrote the book.
A research database large enough to test them.
Thanks for reading Hidden Performances! Subscribe for free to receive new posts and support my work.
The Ten Claims
I selected ten of the major claims or principles from the book and asked whether the historical data supported them.They were:
1. Early pace and position matters most
Front runners should be structurally favoured on sharp All-Weather tracks, particularly when the race is likely to be genuinely run.2. Hold-up horses are riskier
Especially in All-Weather sprints, horses ridden well off the pace face a structural disadvantage.3. Vs.Par and Time Index matter
These are among the most useful RaceIQ indicators for assessing the underlying quality of a performance.4. FSP% above 102% is significant
A strong finishing-speed figure can identify horses that have finished better than the bare result suggests — but only when interpreted in the context of the pace of the race.5. Draw cannot be viewed in isolation
The value of a draw depends upon the interaction between draw, pace and running style.6. Newcastle is different
The course has characteristics that make its race shape and positioning dynamics different from the other UK All-Weather tracks.7. Strong-race class droppers can provide value
A horse coming out of a genuinely strong race and dropping in class can represent a particularly interesting opportunity.8. Some winners are false winners
A horse can win without producing a performance that should necessarily be trusted next time.9. Stride and biomechanics matter
Physical performance indicators such as stride length may contain information about a horse’s underlying ability.10. Trainers target certain races
Some trainers appear to perform particularly well when targeting stronger races.Ten claims.
One database.
No cherry-picking.
So What Did We Find?
The first thing I want to make clear is that I am not going to pretend that every statement in the book has been proven correct.That would defeat the purpose of doing this research.
Some claims have been strongly supported.
Some have been confirmed but require qualification.
And one in particular has not been confirmed in the simple way I originally thought.
I actually think that makes the results more interesting.
Because if I had simply gone into the database looking for evidence that everything I had written was right, this would be little more than confirmation bias dressed up as research.
That’s not what I want Hidden Performances to become.
Claim One: Early Pace Matters
Strongly confirmed
One of the fundamental arguments in the book is that early pace and position are enormously important on the All-Weather.The database provides some striking evidence.
In Even-pace 6f races, front runners won at:
43.8%
Hold-up horses?0.2%
That’s from 417 hold-up runners.At 5f Even pace, front runners won at 39.3%, while hold-up horses won at just 0.4%.
At 7f Even pace, the front-runner figure was 37.7%.
At 1m it was 31.5%.
Those aren’t marginal differences.
They are structural.
But there is a crucial second part to the story.
Because when the race becomes Slow-Fast, the picture changes dramatically.
At 5f:
Front Runners — 7.0%
Mid-Pack — 20.4%
At 6f:
Front Runners — 6.3%
Stalkers — 17.2%
At 7f:
Front Runners — 5.5%
Stalkers — 15.1%
So the conclusion isn’t simply:
It is much more interesting than that.
Position matters. But what the pace does to that position matters just as much.
That is something the database has allowed me to understand much more clearly.The 0–20mph Discovery
One of the most interesting findings concerns the RaceIQ 0–20mph metric.The fastest horse from the stalls — Rank 1 — became a front runner 54% of the time.
The fifth-fastest gate horse became a front runner just 17% of the time.
The relationship is remarkably clear.
0–20mph Rank 1st
Front Runner: 54%
Hold-Up: 7%
0–20mph Rank 2nd
Front Runner: 41%
Hold-Up: 10%
0–20mph Rank 3rd
Front Runner: 32%
Hold-Up: 13%
0–20mph Rank 4th
Front Runner: 22%
Hold-Up: 20%
0–20mph Rank 5th
Front Runner: 17%
Hold-Up: 28%
This gives us something potentially very useful.
Rather than relying solely on a horse’s historical run-style designation, we can look at its actual ability to get out of the stalls quickly.
The data suggests that gate speed is a major component of how the field sorts itself during the opening stages.
That gives another layer to the race-shape analysis.
The Two-Phase Race
Another finding from the research particularly interested me.The book discusses races in terms of two broad phases.
Phase 1
Getting a position.Phase 2
Efficiency, stamina and finishing.The database allowed this to be quantified.
Across all All-Weather races:
32% of winners were Phase 1 positional winners.
67% gained positions during the closing stages.
At first glance, that might appear to contradict the emphasis on early position.
It doesn’t.
Because the pace shape determines which phase becomes decisive.
In a Slow-Fast race, the horses that conserve energy for the finishing phase can make up significant ground.
In an Even-pace race, there is far less opportunity to do that.
And this produces one of the most important principles emerging from the research:
That sounds obvious.
But the data shows just how important it is.
The 479 Horses That Finished Fast — And Still Lost
This was another finding I found particularly fascinating.The database identified 479 horses that gained four or more positions during the final two furlongs of Even-pace races but still failed to win.
These are horses that produced a significant late move.
Yet they couldn’t overcome the disadvantage created earlier in the race.
In other words:
**They finished strongly.
But they finished strongly too late.**
That creates a potentially interesting future research angle.
If one of these horses subsequently finds itself in a Slow-Fast race, where early energy conservation becomes more important and the finishing phase becomes more decisive, does its previous run become a positive signal rather than a negative result?
That is exactly the type of question the research database now allows me to investigate.
And it wasn’t something I set out to prove when I wrote the book.
The data has taken the research somewhere new.
Claim Two: Hold-Up Horses Are Riskier
Confirmed
The evidence here is exceptionally strong.In Even-pace sprints, hold-up horses were almost completely shut out.
At 5f and 6f, there were multiple course-and-distance combinations where the historical win rate was effectively zero.
But again, the pace qualification matters.
When races become Slow-Fast, hold-up horses become much more competitive.
So once again, the book’s underlying principle survives — but the database gives us a much more precise definition.
It isn’t:
It is:
That is a much more useful piece of information when trying to analyse a race before it happens.
Claim Five: Draw Only Makes Sense in Context
Strongly confirmed
This is another area where the data has been particularly revealing.I’ve always been wary of simplistic draw systems.
“Low is good here.”
“High is good there.”
Those statements can be dangerously misleading.
The database found numerous examples where the draw advantage reversed depending upon the pace shape.
Kempton 6f provides an excellent example.
In Even-pace races:
Low draw — 8.6%
Mid draw — 15.8%
But in Slow-Fast races:
Low draw — 15.2%
Mid draw — 7.0%
Same course.
Same distance.
Different pace.
Different draw result.
The research therefore strongly supports one of the book’s central ideas:
Draw isn’t a standalone variable.
It is part of the race shape.And Then There Was Newcastle...
This is where the audit became particularly useful.I wrote that Newcastle was different and that hold-up horses were more viable there.
The database didn’t completely support that.
At sprint distances, Newcastle hold-ups were slightly better than elsewhere.
But the difference wasn’t large enough to justify the stronger claim.
At some longer distances, they actually underperformed.
So this is one area where I have had to refine my original thinking.
Newcastle does appear to have distinctive characteristics.
But the research suggests those differences are more closely related to the interaction between pace, draw and positioning than simply saying:
That is a subtle distinction.
But it matters.
And this is precisely why I wanted to carry out the audit.
So Does the Book Stand Up?
After testing the ten claims, my overall conclusion is encouraging.But I don’t want to oversell it.
The research broadly supports the underlying framework.
Several of the central principles have been strongly confirmed.
Others have been confirmed but with important qualifications.
And some need more work before I would describe them as proven betting angles.
That distinction is important.
Because supporting a theory isn’t the same as proving profitability.
A horse category might produce a 20% strike rate.
That doesn’t tell us whether backing those horses at their historical prices would have produced a profit.
Likewise, identifying a trainer who wins more frequently in stronger races doesn’t automatically create a betting edge.
To establish that, we need to test:
- prices
- returns
- ROI
- drawdown
- sample size
- and, ultimately, out-of-sample performance.
The Book Was the Hypothesis
This is probably the most important point I want to make.When I wrote the book, I wasn’t starting with a giant database and building a theory around the results.
Much of the thinking came from years of watching All-Weather racing and trying to understand what was happening beneath the surface.
The RaceIQ data then gave me a way of understanding and testing those observations.
Now, with almost two years of comprehensive results captured, I can finally ask a much harder question:
Was I actually seeing something real?
The early answer is:In many cases, yes.
But the database has also shown me where the original ideas need refining.
And I think that is exactly what good research should do.
It shouldn’t simply confirm what you already believe.
It should make your understanding more accurate.
This Is Only Part One
The All-Weather season is, of course, continuous.But we’re now in the quieter part of the year.
There are still AW races being run, but the volume is relatively low compared with what is coming.
By September and October, the AW programme begins to build significantly again.
That gives me an opportunity.
Rather than simply writing more articles telling you what I think, I’m going to use this period to dig much deeper into the research database.
This is going to become a series.
The next articles will take individual chapters and concepts from the book and put them under the microscope.
We’ll look at the evidence.
We’ll look at where the book was right.
We’ll look at where it needs qualification.
And where possible, we’ll go beyond simply asking whether something works and start asking the question that really matters to anyone betting:
Does it actually make money?
Part Two: Coming Soon
The next article will take a much deeper look at race shape, pace and the first part of the race.In particular, I’ll be looking at the relationship between:
0–20mph
draw
running style
pace shape
position
and what I am calling the two-phase model of an All-Weather race.
And there is one particular group of horses that has emerged from the research that I think could be very interesting:
Horses that finished strongly, gained significant ground late — but were beaten because they had given away too much ground earlier in the race.
There are 479 of them in the current research.The question is whether their next race can provide the conditions that their previous race didn’t.
That’s where the research gets particularly interesting.
If You Haven’t Seen the Book
For those who have followed Hidden Performances for a while, you may already know that I wrote a book specifically about All-Weather racing.For anyone discovering my work through this article, the book is:
UK All-Weather Racing: A Specialist’s Guide to Finding Value on the All Weather
It is the original source of many of the ideas being tested in this research series.
I’m deliberately not going to turn these articles into advertisements for the book.
I’d much rather let the research speak for itself.
But if you want to see where these ideas originally came from, you can find the book here: UK All-Weather Racing: A Specialist's Guide to Finding Value on the AW: Amazon.co.uk: Watts, Dave: 9798242338234: Books
