An Irish National Hunt Trainers Analysis

November 5, 2025
Dave Renham

An exploration of Irish National Hunt trainers using the Geegeez Query Tool

Gold members of Geegeez have so many benefits and for the first part of this article I am going to discuss how I used one of these, the Query Tool, to obtain a wealth of trainer data, writes Dave Renham. The second part of the piece will crunch some of those numbers.

My focus was Irish racing and hence Irish trainers in National Hunt races. Data has been taken from 1^st January 2018 to 30^th September 2025 with profits and losses calculated to Betfair Starting Price (BSP) with a 2% commission applied on any winning bets.

Contents

Setting Up With Query Tool

So, the starting point for using the Query Tool was straightforward: by inputting the date range, then going to the RACE menu where, on the Country tab, I ticked ‘Ire’ and then, going to the Race Code tab, I ticked all of the NH code boxes. The screenshot below shows the filters used:

So, this gave me all the Irish data I was looking for so – over 11,000 races as can be seen from the 'Wins' column:

Next I went to the RUNNER menu and then clicked on the ‘Trainer’ radio button, which groups the criteria by the selected variable (in this case, trainer), and then I clicked 'Generate Report'. This gave me the records for every single Irish trainer who had had a runner during the period of study. The first few trainers in alphabetical order are shown below:

From here I wanted to focus only on the trainers who sent out the most runners in order to have big enough sample sizes to drill down into other areas. I ordered the trainers by runs in the Query Tool and decided on 800 runs or more as my cut off point. This gave me 29 trainers to review. By ticking the ‘+’ sign to the left of each of these 29 trainers' names (and, when doing this, the plus sign became a minus sign meaning the trainer had been selected), I added them to my shortlist. Once all were ticked, I generated a new report with only these 29 trainers shown:

I then went back to the SUMMARY tab (top of the main part of the page) and used the 'COPY' button to paste all of the trainer data into a Microsoft Excel file I had already opened. With the 29 trainers logged in the Query Tool, I then went about generating numerous reports by changing the Query Tool variables or options. Once generated, new reports were pasted into a worksheet and I added an additional column with the specific variable for that report. I created 30 different reports, all copied across to my Excel worksheet. This took no more than 20 minutes tops, and I now had all the data I needed to analyse and number crunch.

Irish NH Trainers, by Win Strike Rate

The rest of this article will take a more familiar format for regular readers, although I may discuss some Excel methods I used along the way, in case you want to do some digging for yourself!

First things first, let me share the results for each of the 29 trainers over the timeframe (trainers ordered by win strike rate):

One immediate point to share is that Irish racing has had bigger average field sizes when compared to the UK in recent years, and that helps to explain why the trainer strike rates are generally lower than we are be used to seeing when looking at UK trainer data. The maestro that is Willie Mullins was head and shoulders above the rest in terms of win strike rate having hit a touch more than one win in every four. His runners, if backed ‘blind’, made a very small profit to BSP. The second and third listed trainers, Henry de Bromhead and Joseph O’Brien, were also profitable to BSP. A handful of other trainers made a profit to BSP, but all of these had at least one massive BSP priced winner to skew their bottom line somewhat.

Irish NH Trainers, by 'Favourite' performance

One advantage of copying the 30 different reports into Excel meant I could create a Pivot Table to easily compare the data sets and see if there were any significant patterns or angles that were worth sharing. Pivot tables are an extremely useful way to number crunch data in Excel. For those interested in finding out more about them there are plenty of easy to follow YouTube videos around.

I started off by analysing some betting market stats beginning with trainer data for favourites. In order to have a big enough sample, I decided that a trainer must have saddled at least 100 or more favourites during the period of study. I wanted to start by comparing their overall win strike rate for 'All favs' with their strike rates for market leaders specifically in chases or hurdle races. The sample size for NH Flat favourites was too small for most trainers, so I have opted not to show that. The splits were thus:

Don’t be too put off by the huge variance in strike rates between, say, Mullins and Rothwell, because 88% of market leaders for Mullins were in non-handicaps, and 84% of Rothwell’s were in handicaps. Non-handicap favourites start at much shorter prices on average than handicap jollies, so Mullins was always going to have a much higher strike rate when comparing the two of them. Talking of handicaps and non-handicaps it makes sense for me to share and compare their win strike rates to help illustrate my previous point:

Most trainers conformed to the pattern of much better win rates in non-handicaps, although a few did buck this trend. Declan Queally, for example, had virtually the same strike rate in both race types and when we analyse his results in full, we see the following:

Favourites in handicaps produced excellent returns for Queally and anyone following his market leaders in these contests would have been counting their money. Philip Rothwell has fared far better in handicaps than non-handicaps with favourites, but the vast majority of his market leaders were in handicaps (only 18 in non-handicaps).

It's time to narrow down the research a little by looking at a handful of the most successful trainers.

Irish NH Trainers: Specific Handlers

Willie Mullins

I called him the ‘maestro’ earlier and he has been in a different league to his peer group in recent years. Clearly, he has the backing of some huge owners and gets many of the best horses, but one still needs to deliver. I have shared some of his market leader stats already, and below is a graph sharing his ROI percentages (BSP) in more specific race types – handicap chases, handicap hurdles, non-handicap chases, non-handicap hurdles and NH Flat races.

As can be seen, Mullins produced excellent returns when saddling the favourite in non-handicap chases. The full stats read 316 wins from 536 (SR 59%) for a profit of £116.47 (ROI +21.7%). He also showed a blind profit with market leaders in non-handicap hurdle races thanks to 540 wins from 1028 runners (SR 52.5%) for a profit of £75.68 (ROI +7.5%). He was less successful in handicaps, making a loss in both chase and hurdle race types. His worst record with favourites was in NH Flat races where losses were close to 9 pence in the £.

Switching to all runners rather than just favourites, Mullins had some powerful stats during the period of study when we analyse the run style of his runners in chase contests. Regular readers of my articles will know that chases tend to offer front runners a solid edge over all other run styles. Mullins conformed to this pattern in such races going back to the start of 2018 as the graph below, which shows his win strike rate across the different run styles, highlights:

Mullins’ horses that have taken the lead at the start of their chase races went onto win nearly 45% of their races. If we had known pre-race which of his horses would front run and backed them accordingly, we would have been in profit to the tune of £185.78 (ROI +36.1%). Compare this to the potential returns of midfield and held up runners, which would have lost 18p and 30p in the £ respectively.

Moving on to the very best contests, Class 1 events. Here, Mullins produced a blind profit and, considering he had 2536 runners in them, this was an impressive performance, even more so considering every Irish (and British) punter knows what this trainer has achieved. His record in Grade 3 races produced the best results: 117 wins from 457 (SR 25.6%) for a profit of £74.58 (ROI +16.3%).

Henry de Bromhead

Henry de Bromhead had some amazing wins in the UK during this timeframe, especially at the Cheltenham Festival, but here I will drill into his Irish record in more detail. His overall record showed a blind profit equating to over 6p in the £ and his yearly splits are shown in the graph below:

2021 was a poor year from a returns’ perspective, and 2020 showed a small loss, but the other six years all returned a profit. Hence, de Bromhead has been extremely consistent over this timeframe.

Like Mullins, de Bromhead has some interesting stats connected with run style but his most interesting numbers have been in hurdle races. His win strike rate splits have been as follows:

Horses that have led early have been the most successful by far and, if our crystal ball had been in tip top working order, backing these runners pre-race would have yielded a very healthy return of nearly 70p in the £.

From a personal perspective it will be sad that we will not see the iconic Rachael Blackmore riding for him in the future. They have been one of the best trainer/jockey combos of recent years and gave racing fans some great memories.

Gordon Elliott

For Gordon Elliott I would like to share his record with favourites in NH Flat races. Each year Elliott has had numerous runners in NH Flat races of which roughly 28% of them have started favourite. His record with these market leaders was as follows:

For favourites to return over 30p in the £ across a good number of bets is rare, so Elliott has performed well above the norm with this cohort of runners.

Elliott is another trainer who produced some very interesting run style stats during this time period. The stats for hurdle races were as follows:

As we know, the run style each Elliott horse employed was only known after the start of its race. Hence, the profit figures for leaders and prominent runners were not something we could have achieved in reality. However, what it does show once again is that for the majority of races the importance of being up with the pace rather than off the pace.

Geegeez Gold members interested in run style research can investigate further by using the Pace Analyser if wishing to dig into specific courses and/or distances. The example screenshot below shows some Carlisle data:

Parameters of race code, course, distance, going, number of runners, handicap/non-handicap and time frame can all be tweaked. Also we can check out both Irish and UK courses.

Members can also use the Query Tool for run style research like I have done for this article exploring other areas such as trainers, jockeys, etc.

Joseph O’Brien

Jospeh O’Brien, like Gordon Elliott, has produced positive stats when it comes to NH Flat races. The table below shows his overall record in these races, his record with favourites, and his record with horses that were in the top three of the betting:

O’Brien has clearly excelled in these races, and it will be interesting to see what happens over the coming season.

Like the other trainers discussed, O’Brien has worthwhile run style stats to share. Below is a graph showing the win percentages for each run style group in both chases and hurdle races:

Once again, we see front runners from his stable had a huge edge over prominent racers who in turn had a significant edge over horses that were held up or raced in midfield.

I hope this article has served two purposes. Firstly, I wanted to show that research can be undertaken very quickly to generate useful stats and across a variety of areas; and secondly, I have shared some data relating to the highest volume Irish trainers which we should be able to use to our advantage this coming winter and beyond.

Finally, I hope some members will be tempted to use the content here to inspire your own research using Query Tool, Pace Analyser and the other tools in the Geegeez Swiss Army Knife.

Until next time...

- DR

An Irish National Hunt Trainers Analysis