Winning Systems: Jump Racing Drifters

    In this second part on horses who drift in the betting market, Dr Peter May takes a look at the trends behind such runners in jump races.

In the earlier Flat racing article we defined a “drifter”, specifically that is was a horse with an exchange price that was longer than its associated mid-morning price after adjustments were made for subsequently withdrawn runners. We also examined 100,000 flat race performances (turf and all weather) and established that drifters win at a much lower rate than other runners, and for handicaps return less to the punter when backed at off time.

A few key form attributes were analysed and some very basic trends were established that have shown positive returns in the past, but it was concluded that the most efficient way to make a profit from these runners would be to identify them in advance, though clearly that is not an easy task and would depend upon a very accurate odds line.

The focus now turns to jumps racing with analyses undertaken to determine whether the same trends exist for this code as for flat racing.

A sample of 75,000 race performances was taken from jumps races run in recent seasons for which a range of prices were available. Using the same definition of a “drifter” as for the Flat, the proportion of horses deemed to drift was 60% - identical to the flat.

Also similar to previous findings was the division between handicaps and non-handicaps. For jumps races 57% of handicappers drifted whilst 63% of non-handicappers started at longer odds than their adjusted mid-morning price.

In terms of win rate, Table 1 shows the chance of success for the four main jumps race categories. In similar fashion to the flat, drifters win much less often with win percentages ranging from 8% to 12%, whereas the other runners in the sample produced a strike rate of between 13% and 21%. Interestingly if the drift is greater than half the original price (6.0 to 9.0 for instance), then the win rates drop much further as low as 2% for non-handicap races and between 4% and 5% for handicaps.

Table 1: Analysis Of Win Rates

Race Classification

Drifted

Others

All

Handicap Hurdle

8%

13%

10%

Handicap Chase

10%

16%

13%

Non-Handicap Hurdle

8%

18%

11%

Non-Handicap Chase

12%

21%

15%

Based on the data presented in Table 1 it would be difficult to recommend backing a drifter in a non-handicap hurdle race with a success rate of just 8% compared to 18% for the other horses, but in terms of profit these lose less at 6p/£ compared to 12p/£ for those which have shortened (see Table 2).  The profile for non-handicap chases is the same, but for the handicap contests it is better to side with those runners that have not drifted.

Table 2: Analysis Of Profit/£

Race Classification

Drifted

Others

All

Handicap Hurdle

-0.04

0.00

-0.02

Handicap Chase

-0.04

0.00

-0.02

Non-Handicap Hurdle

-0.06

-0.12

-0.11

Non-Handicap Chase

-0.02

-0.08

-0.04

For handicappers which have drifted significantly, at least by more than half the original price, the profit figures are much poorer at around -0.10/£. Those handicap chasers which halved in price returned a decent profit of 9p/£, but the same horses made a huge loss in handicap hurdle races suggesting that the value had been missed and was somewhere between the early price and the off time price.

So perhaps following gambles in these races, where the price has already dropped markedly, is not the way to make a profit. Of course knowing about the gamble in advance is very advantageous with these handicap hurdlers showing a profit £1.50/£ at the early price!

The fact that handicappers that have not drifted break even (Table 2) implies that we should be able to profit from these by adding a few filters. However it’s not as easy as it would appear. Applying the usual filters does not particularly help, for instance quick returners (up to five days) show a loss. Finishing position is a little more encouraging with horses filling the positions 7th, 8th and 9th producing a profit of 25p/£ from 907 runs, but this is hardly the basis for a robust system.

For handicap hurdlers there appears to be a better chance of finding a successful system. Quick returners that shortened made 9p/£ from 259 qualifiers in the sample, and last time out winners produced a similar level of profit from 1283 bets.

As with the flat data, the best approach to making a profit is to model the data and generate techniques for identifying those runners which will shorten. These models could incorporate the use of either an odds line or a rule-based method. Creating such a system would not be easy but it could be worth the effort given that, within the sample, handicap chasers which do not drift made 25p/£ at the early price.

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