Updated: Mar 29
Spending one's life analysing horse racing data has its positives and negatives.
Without a doubt, the positive is that you become immune to the highs and lows that traditional gamblers encounter every year and focus on long term profits. Data is data and, no matter how much you may enjoy cheering a 33/1 winner after a few decades, nothing really floats your boat in the short run. Not cheering your 33/1 winner over the line may be deemed a negative by many, but the long losing run that often follows makes it not such a bad thing.
The one thing that does get the pulse racing, though, is finding a large sample size of data that shows a consistent profit over a long and sustained period of time that can be used in conjunction with current race modelling to improve an overall ROI (return on investment).
Yet anyone can do it and, strangely, it is actually the 'non racing' fraternity who often come up with some of the best angles that are underbet. I could list countless examples, but one that may surprise you more than most is the opinions of equine vets. They understand the mechanics of a horse better than anyone and can make perfect sense to a set of results that would make little, if any, sense to most 'punters'. So much can be gained by simply listening to them on issues like wind operations, skeletal make up, conformation, etc., that it really should be part of todays modern gamblers armoury.
Other 'trades' who have been very beneficial over the years to listen to and offer valuable points are mathematicians, especially those who understand racing but have limited interest in gambling. They have no interest whatsoever in 'sexy' news or social media trends. For example, it was pointed out to me by one such type that, in non-handicap chases leading up to Cheltenham, the favourites do disproportionally well as the uncompetitive nature of the racing due to the festival approaching led to small fields and underbet favourites. After pondering on the theory for way too long, we went about a long discussion to make sure this was a theory that could be substantiated before we went data trawling (data trawling is whereby you dig through data and find a trend in the data, although this can be a flawed concept without a practical and logical theory to back it up, hence the theory must be in existence first).
Sure enough he was right, in simple numbers, qualifiers from February favourites have shown a profit since 1998 to 2019 in 15 months and a loss in only 7 months to SP (starting price, *not used BSP as not going that long) and an overall profit to SP of 5.5% with an A/E 1.1.
Incredible, really, on a massive sample size of 1600 qualifiers on short prices at SP.
Herein lies the problem with gamblers. Tell them you are backing favourites in non-handicap chasers in the weeks leading up to Cheltenham (this just as one example) and they will simply look at you like you are the simplest and most uneducated gambler they have ever met. Yet they have no substance to discredit the theory, just a firm belief that their brain can calculate in a split second that you will lose. Sadly, this is the reason they are highly likely not to win 'long term' by gambling.
We get lots of messages and emails from people who'd like to know more about this style of gambling but are intimidated by the sheer volume of variables available. Hopefully, the examples above show you that anybody can think outside the box and make long term profit, but it helps if you are somebody who is analytical rather than somebody who just likes to gamble.
In the words of the Austrian writer Marie Von Ebner-Eschenbach: "nobody knows enough but many know too much".