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Pace In National Hunt Races


Pace In National Hunt Races by Dave Renham

After writing five articles on 5f turf handicaps it seemed sensible, as we were heading into Autumn, that I would start looking at pace in National Hunt racing. For those readers who have not read my pace articles before I will give you a brief summary of what pace in a race means.  When I talk about pace my main focus is the initial pace in a race and position the horses take up early on. www.GeeGeez.co.uk has the pace section and the stats I am sharing with you in this article are based on the site’s pace section data.

The pace data on Geegeez is split into four – Led (4), Prominent (3), Mid Division (2) and Held Up (1). The number in brackets are the pace scores that are assigned to each section.

For this article I am concentrating on course data and creating pace figures for specific course and distances – my focus for this piece is handicap chases of 2m 1½f or shorter. In some research 7 or 8 years ago, I noted a bias to front runners in these races – not as strong as some flat front running biases, but a bias nonetheless.

The first set of data I wish to share with you is the overall pace stats for handicap chases of 2m 1½f or shorter (minimum number of runners in a race 6):

Pace comment

Runners

Wins

SR%

Led

1936

362

18.7

Prominent

4145

608

14.7

Mid Division

1423

144

10.1

Held Up

4459

388

8.7

 

Now as we can see horses that led, or disputed the lead early have a decent advantage in these handicap chases. Prominent racers have a decent looking record too, while hold up horses do tend to struggle.

Another way to illustrate the data is through Impact Values – the best explanation of an impact value or (IV) is one I read many years ago in a book by Dr William Quirin called ‘Winning at the Races’. He stated that impact values ‘are calculated by dividing the percentage of winners with a given characteristic by the percentage of starters with that characteristic. An IV of 1.00 means that horses with a specific characteristic have won no more and no less than their fair share of races.’

To help explain IVs further let me use the ‘led’ stats in this article to illustrate the idea. Now, as you can see in the table above horses that have led early have won 18.7% of these races – when we combine at all the pace data there were 1502 winners from a total of 11963 runners which gives an overall win percentage of 12.56%. Hence we need to divide 18.7 by 12.56 to give us the impact value for leaders – this gives us an impact value of 1.49. Here are the impact values for each pace category:

Pace comment

Impact value

Pace comment

Impact value

Led

1.49

Prominent

1.17

Mid Division

0.81

Held Up

0.69

 

Using ‘bog standard’ win percentages, or the slightly more sophisticated Impact Values give us the same picture. In handicap chases of 2m 1½f or shorter there is a clear advantage to a more prominent running style – the nearer the front early, the better.

As when I looked at 5f flat handicap pace data, there are significant differences in the course figures for these contests too with some courses being more suited to early leaders/front runners than others. Here are the courses with the best strike rates (25 front runners minimum):

Course

Front Runners

Wins

SR%

Hexham

68

24

35.3

Taunton

39

13

33.3

Huntingdon

42

13

31.0

Lingfield

32

9

28.1

Wincanton

40

10

25.0

Plumpton

45

11

24.4

Sandown

46

11

23.9

Ludlow

82

19

23.2

 

For record Haydock’s strike rate for front runners was 38.9%, but there were only a handful of races (14). Now let us look at the courses with the best impact values which should give a more accurate measure of front running bias:

Course

Impact value for Front runners

Hexham

2.96

Taunton

2.42

Huntingdon

2.31

Cheltenham

2.29

Lingfield

2.05

Hereford

1.93

Ludlow

1.81

Wincanton

1.80

Carlisle

1.80

Catterick

1.70

Sandown

1.68

 

The order is similar, but Cheltenham appears in 4th place in this list compared with a lowly 23rd placing on the SR% list. The simple reason for this is that chases of this type at Cheltenham have many more runners on average compared to all other racecourses. This shows why Impact Values are so important and statistically accurate.

Hexham’s front running bias is very strong – indeed it should be noted that hold up horses have a dreadful record there winning just 6 of the 56 races from a total of 174 runners (IV 0.29).

At the other end of the scale here are the courses with the poorest stats for early leaders/front runners in handicap chases of 2m 1½f or shorter:

Course

Front Runners

Wins

SR%

Newcastle

44

6

13.6

Bangor

38

5

13.2

Ayr

55

7

12.7

Musselburgh

25

3

12.0

Southwell

94

11

11.7

Wetherby

50

5

10

Aintree

43

4

9.3

Newbury

40

3

7.5

Ascot

48

2

4.2

 

Very poor figures on the face of it for Ascot, Aintree and Newbury. The impact values will give us a more complete picture. The table below show courses that have an IV of less than 1.00.

Course

Impact value for Front runners

Newcastle

0.98

Musselburgh

0.96

Ayr

0.91

Southwell

0.91

Aintree

0.90

Wetherby

0.72

Newbury

0.58

Ascot

0.36

 

So the Ascot figures for early leaders is very poor, but interestingly hold up horses have not dominated at this course. The impact value for hold up horses at Ascot has been 0.91 – it is prominent runners (horses that track the pace) with an IV of 1.62 that have had most success at Ascot.

This article to date has focused on front runners. Now I want to try and give a more overall course and distance profile for each course. To do this I have created course pace averages as I did in my second article on 5f flat handicaps. I create course pace averages by adding up the Geegeez pace scores of all the winners at a particular course and dividing it by the total number of races. The higher the average score, the more biased the course and distance is to horses that lead early or race close to the pace. Here are all the courses listed:

Course

total races

course average

Hexham

56

3.18

Taunton

32

3.03

Ludlow

67

3.01

Sandown

32

2.97

Wincanton

30

2.97

Carlisle

36

2.92

Newton Abb

69

2.86

Huntingdon

32

2.84

Lingfield

24

2.83

Haydock

14

2.79

Hereford

26

2.69

Plumpton

37

2.68

Southwell

64

2.64

Exeter

22

2.64

Leicester

40

2.63

Towcester

47

2.62

Kelso

72

2.60

Perth

32

2.59

Uttoxeter

54

2.59

Sedgefield

80

2.59

Worcester

99

2.59

Ffos Las

18

2.56

Chepstow

45

2.56

Catterick

35

2.54

Stratford

53

2.51

Doncaster

21

2.48

Newcastle

37

2.46

Bangor

30

2.43

Warwick

23

2.39

Cheltenham

35

2.37

Ascot

32

2.34

Wetherby

35

2.34

Market Rasen

12

2.33

Ayr

43

2.33

Aintree

31

2.32

Newbury

31

2.32

Mussleburgh

20

2.30

Cartmel

36

2.17

 

These pace averages arguably give a more overall pace ‘feel’ to each course – it is clear though that Hexham and Taunton are two courses where there is a very strong pace bias. Being able to predict the front runner in handicaps chases of 2m 1½f or shorter at these two courses should provide you with some value betting opportunities – there are other courses that will often a strong edge too of course, but these two stand out.

I hope this article has been of interest and as with anything in life, the more you ‘put in’, the more you tend to ‘get out’. I will personally continue to work hard researching pace angles because it has the potential to really pay dividends.

 

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This article first appeared on the excellent GeeGeez.co.uk

 








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