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Pace in National Hunt Racing part 3


 

Pace in National Hunt Racing part 3

by David Renham

 

This is the third installment in a series of articles on pace in National Hunt racing. In order to help compile this article I am using some pace data from Proform (www.proformprofessional.co.uk) which as I have stated before is the best piece of software I have found for anything pace related.

 

To recap, we have seen that front runners (horses that take an early lead) have a decent edge in chases. In this article, I am sticking to handicap chases, and looking to find ways of correctly predicting the front runner – or at least predicting the front runner a decent percentage of the time.

 

Proform pace rankings

 

As I mentioned last month an additional feature of the Proform software is that for each race, pace figures for each horse are calculated using the last three races. Scores are given as follows:

 

4 – for early leaders/front runners

2 – for prominent racers

0 – for hold up horses

 

Last month I looked at how these rankings fared in predicting the front runner in handicap chases. For the record the top ranked pace horse went onto lead 33.4% which is a decent enough starting point. However, to take advantage of the front running bias we need to try and improve this figure. Hence I have looked at all the top rated horses with their equivalent pace figures to see whether this makes a difference. Here are the findings:

 

Top ranked horse – pace score

% the horse was the early front runner

12

55%

10

42%

8

35%

6

29%

4 or lower

25%

 

Clearly the actual pace figures make a huge difference. Top rated pace horses with 12 points are twice as likely to lead as those top rated with 6 or fewer points. Also 55% is an extremely decent figure in terms of predicting the front runner. The question is can we improve upon this 55% figure? I have decided to add some filters to the group of horses that are top rated with a maximum score of 12 points to see if I can improve upon this 55% figure.

 

 

 

Age

 

My feeling was that handicap chasers peak between 8 and 10 depending on the distance so I had expected to see a higher front running percentage for these age groups. This is what I found for the horses that had gained 12 points over their last three runs:

 

Horse Age

% the horse was the early front runner

4&5

40

6

45.9

7

58.0

8

56.7

9

57.3

10

59.4

11

57.6

12+

55.6

 

Essentially, there is a slight improvement in terms of front running percentages from age 7 onwards. Younger horses aged 4 to 6 are probably less likely to have a preferred running style over fences which accounts for their lower figures. Hence we can improve our chances of predicting the front runner by eliminating horses 6 and younger, but essentially it does not improve our chances significantly.

 

Betting market

 

So how about the betting market? Does this make a difference? I had expected to see better results for top 3 or 4 in the betting so let us see what I found:

 

Position in Betting Market

% the horse was the early front runner

Favourite

70.4

2nd favourite

61.9

3rd favourite

55.0

4th favourite

60.2

5th in betting

56.1

6th in betting

51.3

7th in betting

50.0

8th or higher in betting

42.4

 

Using the betting market as a filter certainly seems to improve our chances of predicting the front runner. Favourites with a pace score of 12 go onto lead over 70% of the time, and in general the table suggests that the more fancied the runner, the more likely it is to take an early lead.

 

 

Weights

 

Higher weighted runners are the classier horses in the race, and higher weighted runners tend to win more races than lower weighted ones. Hence would this factor make a difference in terms of our chances of correctly predicting the front runner? I have grouped the figures to make it easier to interpret:

 

Position in Weights

% the horse was the early front runner

1-2

60.4

3-5

60.7

6-7

52.4

8+

45.1

 

The top 5 in the weights combine to push the figure over 60% so it does improve our chances if we focus on the top end of the weights.

 

Race type LTO

 

The actual race type LTO I perceived to quite important – indeed if I had the time and computer skills I would like to have looked back at the last three race types as this I feel would have been even more beneficial. However, the LTO race type is what I am going to look at here:

 

Race type LTO

% the horse was the early front runner

Hurdle race

39.3

Chase

58.1

Handicap race

59.2

Novice race

44.7

 

These four race-types produced decent samples so I felt the data was more valid. As we can see handicap races and chases do improve our predicting chances. Indeed if we combine those to focus on handicap chases LTO our figure improves to 60.5%. The figure for horses that ran in a novice chase LTO is only 35.8%, while horses that ran in a non handicap hurdle LTO sees the figure dropping to 23.1%, albeit from a smallish sample.

 

Sticking with horses that ran in a handicap chase LTO, it also seems to make a difference how many runners were in that contest. Clearly it is a logical argument to say the more runners in a race the harder it is to lead, and hence I would always take more note of a horse that led in a 15 runner race as compared to one who led in a 5 runner race. The stats for predicting the front runner show that the more runners LTO the better in terms of predicting the front runner next time out:

 

 

 

No. of runners in handicap chase LTO

% the horse was the early front runner

6 or less

57.5

7 to 11

59.9

12 or more

64.6

 

Class change

 

I had expected horses dropping in class to find it easier to lead next time, but the figures surprised me:

 

Class change from last run

% the horse was the early front runner

Down in class

52.4

Same Class

58.5

Up in Class

55.1

 

Horses running in the same class led more often, followed by horses upped in class, while horses dropped in class lead early the least.

 

As we can see there are several ways to improve this 55% front running figure. We have hit 70% on one occasion (focusing solely on favourites), but for the record, the highest figure I have found is 71.3% - this is achieved by combining the top 4 in the betting with the top 5 of the weights as well as the horse having run in a handicap chase LTO. One could argue this has been back-fitted, which of course it has. However, the three added filters are logical and hence, for me, I would not dismiss this front running prediction combination out of hand.

 

I hope you have found this article of interest andnext time I will conclude my series of articles on Pace in National Hunt Racing.

 

 

 

David Renham

www.racingtrends.co.uk

 

 








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