Distance and Going Winners

The focus this time is on distance and going winners with the aim of establishing whether these attributes impact on the chance of success and, more importantly, the profit and loss figures.

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Elsewhere in this section I have examined course winners and established that, with the exception of a couple of race types, course winners did not perform significantly better than other runners. 

The focus this time is on distance and going winners with the aim of establishing whether these attributes impact on the chance of success and, more importantly, the profit and loss figures.

A previous success on similar ground, or a win over the same race distance, is considered to be such a key factor that indicators are printed on most racecards drawing attention to these form attributes of the runners. I must admit that when I am covering the Speed Page for attheraces.com, and trying to find six good bets for the following day, I am often swayed by these factors and will be influenced by them when determining the more likely winner of two closely rated runners. 

Although such actions do seem to be eminently sensible, without an examination of the raw data it is not possible to be sure that using these attributes in the race analysis process actually improves the accuracy of the assessment.

The table below shows the win rates, in percentages, plus the average profit and loss to a level £1 staked at Bookmakers’ starting price for six race categories and compares the figures for all runners, distance winners and going winners for a five year period of flat racing on turf.

Table1: Win Rates and Profit Figures for Turf Races Staged over Five Years

All RunnersDistance WinnersGoing Winners
2yo Hcaps11-0.1613-0.1413-0.20
2yo Non Hcaps12-0.2415-0.2214-0.22
3yo Hcaps11-0.1913-0.1513-0.17
3yo Non Hcaps13-0.2115-0.3016-0.25
All Age Hcaps9-0.2110-0.2110-0.20
All Age Non Hcaps12-0.2314-0.2014-0.19

It is noticeable that the win rates are slightly higher for the going and distance winners than for all runners which would be expected since these are supposed to be positive indicators.

However, the differences are not particularly significant suggesting that the factors are not adding a great deal which is disappointing, but worse still are the profit and loss figures. The losses are no better than those achieved by a random selection process which demonstrates that these factors are fully accounted for in the price estimation by Bookmakers.

Breaking down the analysis of the distance winners by specific race distances showed almost uniform distribution of loss figures across the full range from sprinting to staying with one small exception. 

Three-year-old races run over a mile produced slightly better returns but this was most likely due to randomness rather than some significant trend. Results for the going winners were similarly uniform across the different states of ground with only three-year-old handicaps run on soft or heavy ground showing any deviation and even that was only minor.

One of the reasons for the similarity between the win rates and profit data for the various categories is that a high proportion of the runners will be either distance or going winners. Consider an all age handicap run over five furlongs, it would be a surprise if fewer than half of the runners had not won over a similar distance in the past, and for races on good ground the same will apply to the going winners. 

As a result we get a regression to the mean, in other words the overall results for these factors will tend towards those for all runners as the ratio of qualifiers to runners approaches one. Therefore, in order to get more informative analyses it is necessary to reduce this proportion and remove this effect. To do this we can isolate a single runner in each race, then test to determine whether the distance winner, or going winner, factors add any value.

There are many different ways we can isolate fewer runners for analysis, one would be to set a maximum price limit, say 10/1, another would be to restrict the analysis to the top weights or to the runner for which the trainer’s win rate is highest. For this analysis, though, I have decided to use the BHA rating; for non-handicap races the analysis will be applied to those horses which are clear top-rated by the BHA. Again this data is normally displayed within the racecards and therefore is easy to obtain and use.

Table 2: Win Rates and Profit Figures for BHA Top-Rated Runners

All RunnersDistance WinnersGoing Winners
2yo Non Hcaps27-0.1530-0.0224-0.08
3yo Non Hcaps26-0.0633+0.0835+0.17
All Age Non Hcaps27-0.0830-0.0929-0.16

From Table 2 it is easy to see the impact the additional factors have on the win rate for the BHA top-rated runners. In Juvenile non-handicaps, for example, distance winners have enjoyed a 30% win rate compared to a figure of just 27% for all horses. This positive effect is also reflected, with one exception, in the profit and loss figures. 

As for the course winners, the most interesting race classification is three-year-olds only. Over the five years, distance winners that were also top-rated by the BHA in this race category returned a profit of 8p/£ to Bookmakers’ starting price (13p/£ at exchange prices) and going winners made a 17p/£ profit (25p/£ on the exchanges). 

For handicap races using the BHA ratings is not helpful since, due to the normalisation by weight carried, there are no top-rated runners. So in order to focus the analysis on fewer horses per race an alternative is required. The top weight could be used, or best drawn runner, or horse from the stable with the best record in handicaps, but for this investigation I have chosen to keep the process as simple as possible and use the market leader (based on Bookmaker SP). Table 3 presents the results for the five-year analysis for handicap favourites.

Table 3: Win Rates and Profit Figures for Favourites

All RunnersDistance WinnersGoing Winners
2yo Hcaps29-0.0832-0.0336+0.04
3yo Hcaps31-0.0332-0.0532-0.03
All Age Hcaps26-0.0926-0.1126-0.08

The loss figures are all under 10% which is a direct reflection of the over-round associated with these horses. Bookmakers tend to under-price the outsiders more dramatically than those at the front of the market so the average loss for these runners is not as great.

However this doesn’t mean that profits are more easily made; only one of the nine categories is in the black. Switching to exchange prices does improve the situation though. Distance winners running in juvenile handicaps have made 6p/£ profit over the last five years, and the 4p/£ profit shown in Table 3 for going winners improves to 17p/£. 

The equivalent figures for three-year-old handicaps are 4p/£ and 5p/£;  but for all age handicap distance winners the profit is still negative and going winners only made 3p/£. 

Whilst these results are far from earth shattering, there may be other factors which combine better with going and distance winners than the favourite. For instance, using an independent set of ratings, such as the ATR Speed Figures, may increase profits to a manageable level, or by adopting an approach based on race profiles or recent form may produce a profitable system. So there remain possibilities for this angle which I may return to in a future article.

As with the course winners, the profits for going and distance winners are found in the age restricted races, possibly for the same reasons given in the last article. But perhaps most interesting is that whilst a previous win over the race distance or on the same going is usually considered to be an important factor for race analysts, it is maybe not as significant as we believe.

Distance and Going Winners
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