Continuing my race simulation analyses (see here for a recent example), I am this weekend looking at the Eclipse at Sandown. As I have with other races, I simulated 100,000 renewals by using recent (2018 on) RPR data from the runners as a means of predicting how likely they are to achieve a certain RPR (and win, or place, in each simulation).

Unfortunately, the Eclipse isn’t an ideal race to perform these simulations on, given that hot favourite Enable hasn’t been seen since last year (and thus has no 2019 RPR data to work with) and that Telecaster is hugely unexposed but very in and out. Thankfully the majority of the other runners have a relatively comprehensive back-history of running in Graded/Group/Listed company and a lot of RPR data to work with.

Data and Method

I used exactly the same base method as described previously (see the Queen Anne post for more detailed information). More briefly, I:

  • Recorded the RPR average (mean) and standard deviation (a measure of the variation around the mean) of all horses from turf Group/Graded/Listed races in 2018 and 2019
  • Computed 100,000 potential RPRs for each horse by using the analysis software, R, and a “truncated” normal distribution algorithm (with the lower limits set at a possible RPR of 0 and the upper at 5lb above most of the older horses’ highest recent RPR, and 7lb above the less exposed Telecaster and Regal Reality) — see figure below

The range of simulated RPRs for each horse in the Eclipse are shown above. Enable is highlighted by the green bars and curve.

  • Ranked horses from highest RPR to lowest in each of the 100,000 simulated renewals and then calculate the proportion of these that each horse won (highest RPR) and placed in (highest three RPRs)
  • Computed “fair” win and place odds for each horse based on these proportions


According to the simulations Enable should be an even shorter favourite at around 1.56 (8-15) than she is with the bookmakers and extremely short in the place market (around 1-20) —see Table below.





Fair Win Odds


Fair Place Odds

Danceteria 1408 17.7
Hunting Horn 342 8.9
Mustashry 26.9 2
Regal Reality 59.6 4.4
Zabeel Prince 50.2 6.4
Enable 1.56 1.05
Magical 7 1.6
Telecaster 7.2 2.7


There are a number of additional points of note. These include:

  • Magical and Regal Reality being a good bit bigger according to the simulations than with the bookmakers – although the strength in Enable is responsible for inflating these (see limitations below)
  • Each horse’s fair win odds only correlate relatively closely with their fair place odds R2 = 0.88, or 88%); the notable anomalies being Telecaster (who has the potential and ability to win race-winning RPRs but also the inconsistency to miss the frame more often than a more consistent performer of his ability would) and Mustashry (who rates an unlikely winner but who has around an Even-money chance of hitting the frame given he consistently runs RPRs that would see him pepper the places here)


RPRs are a relatively solid way of assessing a horse’s ability based on past performances, but there are examples when you should be less confident in their use than others. Of the analyses of this type I have recently conducted, I am not overly confident about this one given the make-up of the race.

We all know Enable has a massive chance if at her best but this represents her first run following a layoff after injury and it is not a given that she will return in A1 shape – especially over a trip that she hasn’t tackled for some time. Last season’s RPR data for her naturally inflates all the other runners’ prices, and it may lead to overconfidence.

Telecaster and Mustashry are arguably the most interesting runners from a potential punting perspective, because the former has lots of ability and has a better chance than the bookmakers believe if he is able to bring his A-game. That is a big if, however, as he blew his race before the start last time and backing him would be inevitably risky. Mustashry, meanwhile, is a solid and reliable performer who would need the higher-class horses to disappoint in order to win, but my simulations suggest he has a good (Even-money) chance of hitting the frame. Given that he is available at prices around 15/8 to do that with the bookmakers I am tempted to suggest him as a bet in the place market. However, his RPR data largely comes from races over 1m and while he gives the impression a bit further may even suit I am not convinced he really wants a stiff 10 furlongs in this company. If you think he will stay, I wouldn’t put you off a place bet, but for me, this is a rare no-bet race.

Future Directions

I will be using this technique to produce “fair odds” for Hong Kong racing beginning next season. HK fare is appealing for this type of analysis as there is a huge amount of ultra-reliable data available to work with.

I plan to produce my own sectional-enhanced speed ratings for all horses running in HK and use these instead of RPRs to model “fair odds” ahead of many of the meetings.

I may also look to trial it on the AW in the UK over the winter, as sectional times should be easy to calculate thanks to what is now available from certain tracks on the At The Races website.

Watch this space.