Technology & Horse Racing – Good or Bad?
In the past couple of years horse racing punters have been turning to new technological race reading innovations like stride length data and lengths gained jumping in their quest to find more winners. In this piece Dave Stevos is going to look at the credentials of some of the most popular race reading tools that have emerged in recent years and give his verdict on their usefulness to horse racing bettors.
Lengths Gained Jumping
As is stated by RaceIQ, this metric is basically used to determine how well a horse has jumped throughout a race in comparison to their fellow competitors and how much influence their jumping has had on the final result.
Measurable data, such as speed on approach to the obstacle and speed after jumping the fence, is used to come up with a figure that accurately defines how many lengths a horse has gained or lost at each hurdle or fence.
The question is, do we need ‘lengths gained jumping’ data to tell us that Majborough jumped like a stag at the DRF or that Final Demand jumped like a bag of hammers? Probably not.
Jump Index
This is a similar metric to lengths gained jumping but it is more of an overview of how a horse has jumped throughout its career and not in comparison to its rivals. Each horse is given a jump index rating based on efficiency, speed and fluency of jumping with 10 being the highest achievable rating.
Stride Length Data
This is a measurement of how many strides a horse takes during a race and how much ground it covers with each stride. RaceIQ provides punters with average stride length and frequency through an entire race, and also how many strides are taken during each furlong. This metric can indicate whether a horse will be suited by a wide, galloping track or a sharp, turning track. Horses with long striding patterns will enjoy racing on the former, but more nimble, smaller horses with shorter stride patterns will be suited by tight and turning tracks like Chester, for example.
Par Times & Sectionals
RaceIQ use sectionals and times to gauge the strength of performance of a horse. GPS tracking is deployed to time how long it takes each horse to cover every furlong, thus giving an overview of how the race was run and whether a horse was suited by the fractions. The sectionals outline whether a race has been run at slow pace, an even pace or a
strong pace. They also indicate how strongly a horse finishes the race in the final furlong. Par times collate the times of races over the past ten years and when used in conjunction with sectionals, this gives an understanding of the quality of a race win time. Par times can also be used to gauge ground conditions as race times will be slower when underfoot conditions are softer and quicker when the ground is good or good to firm.
One Fatal Flaw
All this new-fangled data seems great on the surface but there is one fatal flaw… It is based on the premise that all horses are trying their hardest to win. In Group 1 and Grade 1 races at the top level most (but not all) horses will be there to do their best but in lower grade races like maidens and handicaps, that is simply not the case.
Over jumps, especially in Ireland, the vast majority of top-class horses have one meeting in mind – Cheltenham in March. Their whole seasons are geared towards turning up at Prestbury Park in tip top form for one race, so data they have produced in their prep races can be very misleading. A prime example of this would be the late Langer Dan, a two-time winner of the Coral Cup at Cheltenham in 2023 and 2024. In his three runs prior to winning in 2023 he was beaten 8.25l, 11l and 35l. In 2024 he had four prep runs and was beaten 49l, pulled up, beaten 27l and beaten 31l, yet he won the Coral Cup by 3.5l. In his case, RaceIQ data would have been about as useful as an underwater
hairdryer.
The Verdict
So, is this data worth looking at? Well, it all depends on how keen of a ‘racing eye’ a punter has. Seasoned horse racing bettors don’t need data to tell them whether a horse is gaining or losing ground when they jump an obstacle, nor sectional times to tell them whether a race has been run at a slow or a strong pace and they certainly don’t need stride data to tell them whether a horse is suited (or not) by certain tracks. The best punters train their ‘racing eye’ over years and years of watching horse racing and there is no substitute for experience. Barney Curley, for example, is arguably the greatest punter of all time and he managed to repeatedly beat the bookmakers without having access to data like this. With all that being said, I suppose tools like this can be useful for newcomers to the sport who don’t really understand what they are watching. It also enables trainers to create glossy power-point displays with flashy graphics to explain to owners why their horses ran poorly. However, I would warn against being overly reliant on this type of information. When horses are not trying, they are going to produce inaccurate figures and basing your betting on poor data will only end one way… in tears.
