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Impact Factors In Horse Racing


American writer Fred Davis is somebody that serious punters should be aware of. In 1974 he wrote a book called "Percentages and Probabilities" where he discussed a new way of analyzing horse racing information via the statistical approach of “Impact Values”. Since then, especially in America, Impact Values are used by private handicappers and many serious punters in an attempt to gain an edge.
 
The use of Impact Values seems less common in the UK – the whole statistical approach is still not “in vogue” as the die hard traditions of form study reigns supreme. Things are changing slowly, but a statistical approach is still frowned upon by many.
 
However, I believe it is a very important method in terms of appreciating how strong a statistic actually is. Essentially the operation is a fairly simple mathematical division sum, but it may be easier to give an example:
 
Example – looking at draw bias at Chester. In 10 runner plus 5f handicaps over a recent 7 year period, we find that the 3 lowest drawn horses won 24 of the 47 races – in percentages terms that equates to 51.1%. The highest 3 drawn horses won just once equating to a success rate of 2.1%. Hence, if we want to work out the Impact Value we divide 51.1% by 2.1% which gives us a figure of 24.3. Hence, the Impact Value is 24.3, and what it means is that horses drawn in the bottom 3 stalls are 24.3 times more likely to win than those drawn in the top 3 stalls. Quite a strong statistical indicator that one!
 
Not all Impact Values are this big / potent. However, working out Impact Values gives you a clearer picture than simply looking at say a wins to runs ratio (strike rate). Let us look at one of the top flat trainer’s record with older horses in all age handicaps – again over a recent 7 year period:
 
Wins
Runs
Strike Rate
46
274
16.8%
 
On first glance, what is your first impression? Essentially, you should be thinking that this is a fairly good record – a 1 win in 6 strike rate in handicaps suggests it is more a positive record than negative one. However, how good is this performance in reality? Well one thing we need to do is compare this trainer’s individual record with the record of all trainers in the same race type. Now the average strike rate of all trainers in all age handicaps is around 7.5%. Hence to calculate the Impact Value we need to divide 16.8% by 7.5% - this gives us an Impact Value of 2.2. Hence, this trainer outperforms the average trainer by over 2 to 1 in all age handicaps. Hence, knowing this Impact Value means that this trainer requires further investigation and research on his performances in all age handicaps.
 
However, despite an Impact Value being extremely useful, it is important that you not only consider the Impact Value, but also the Return on Investment (ROI). ROI is calculated by dividing profits or losses by the number of runs. Hence if 100 bets produced a profit of £24.00, then the ROI is +24%; if 100 bets produced a loss of £15.00, then the ROI would be -15%.
 
If the trainer in the above example had an ROI of +30% then it indicates that not only are these trainer’s horses winning more than they should, they are also winning at prices that are bigger than perhaps they should be. A combination of positive Impact Values and positive ROIs is the ideal scenario and those horses should offer us, the punter, a good chance of making profits. A positive Impact Value coupled with a negative ROI gives us a dilemma. Clearly the horses are winning more than they should, but unfortunately the prices on the winning horses have not big enough to produce profits.
 
Sounds easy then – find a positive Impact Value coupled with a positive ROI and we have the way to the Holy Grail of successful betting. Unfortunately again, just having those two figures is not enough to have full confidence in our statistics. Let me explain further. Below is a list of hypothetical trainers and their imaginary performances in maiden races focusing on Impact Values and ROIs.
 
Trainer
Impact Value
ROI
Smith
5.2
+200%
Jones
2.9
+71.4%
Johnson
1.4
+27.8%
 
Looking at the above list, which trainer or trainers would you choose to follow? Clearly Smith looks the best one to follow – a success rate of over 5 times the norm and percentage profits (ROI) of 200%. Jones looks very good also with a success rate roughly 3 times the norm and percentage profits (ROI) of over 70%. However, if we add some other key stats to the table then it becomes very clear that we need to rethink:
 
Trainer
Wins/Runs
Strike Rate
Profit to £1 level stakes
ROI
Impact Value
Smith
1/2
50%
+£4.00
+200%
5.2
Jones
2/7
28.6%
+£5.00
+71.4%
2.9
Johnson
32/234
13.7%
+£65.00
+27.8%
1.4
 
Smith and Jones (not the comedy duo I hasten to add!) have had such a small number of races that their Impact Values and ROIs are both falsely inflated, whereas Johnson now looks the trainer to be most interested in considering that his two “positives” have been generated by a significant sample size. An Impact Value of 1.4 is not that high, but still indicates that he is 1.4 times more likely to win maiden races than the average trainer. Also profits of nearly 30% are very acceptable over a good number of runs / bets.
 
What people do next will vary – however, it may not be prudent to simply back all Johnson’s runners in maidens without any further thought. There is a fair chance that you might make a profit thanks to the combination of the past positive stats, but even at this point, further research and analysis should be a priority. You have arrived at what looks like a profitable trainer/race type combination, however there is more work to do. What happens next is entirely up to the individual, but if it was me, I would do at least two things: firstly I would examine the winning prices of the 32 winners. This would help determine whether there are any further patterns – we have already seen that stats can be misleading. Despite all this information we have now about Johnson’s runners, if one of the winners had been priced at 66/1, then all the profits generated from the 234 runners would have essentially come from this one horse. That would immediately create a re-think and make you wonder whether this area needed further exploration. Assuming the prices of the horses fitted into a fairly standard pattern, then the second thing I would do is break the results down into years, or perhaps blocks of 25 races. This would be an attempt to see if the results followed a fairly consistent pattern over the time period. The results of this secondary research might indicate that results have tailed off in the past couple of years – again this would set the alarm bells ringing. Whatever the outcome of this further analysis, be it statistical or more form based, at least you would be giving yourself the best opportunity to profit from your research. A combination of a positive Impact Value, a positive ROI, and consistent results are a powerful combination. A little hard work perhaps, but the chances are it would be worth it. Now if only I could create an Impact Value for hard work and profit making – now that would be something!
 
 







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