Sam Freedman, racehorse trainer in Melbourne, Australia, has been using the Equimetre for the past year. He grew up in the stable and had a great desire to work in the horse racing sector. He moved to England after finishing his secondary and tertiary degrees and worked as a training assistant for famous European trainer Roger Varian for two years during his time abroad.
He agreed to tell us more about his experience with Equimetre. Why did he decide to gather data? How do they use the Equimetre daily? What does he expect from it?
Can you introduce yourself?
My name is Sam Freedman. I am a racehorse trainer in Victoria, Melbourne, Australia. We’ve been using the Equimetre for the last twelve months or so, and our experience with it is improving all the time. We’re starting to get to know it all, and we use it across several different stables that we’ve got, and we’re enjoying our experiences so far.
“Ultimately, the main goal is to get the best out of every single horse and be able to judge a horse, to have some transparency with owners, and to be able to say to them – Look, this horse isn’t measuring up to where we expected it to – I think it helps.”
What was the driving force behind your decision to collect data on your horses?
A lot of why we ended up going for Equimetre was due to our training facilities. We can’t clock our horses; we can’t see a lot of the work as it is mainly behind trees, and we’re sort of shielded from being able to see it. So, we needed an accurate timing platform to be able to get the sectional times. We wanted to get their heart rate and recovery at the same time, to at least give us as much information as possible.
So that was initially where it started, and now we have sort of started to implement it across both of our stables. We’ve got two bases; one’s at Flemington and one is a private facility. The horses do similar work at different stables, but it’s interesting being able to compare the recovery of the same sort of work on different sorts of ground. And our private facility is largely uphill. It’s a rising track, and obviously Flemington is a very flat track and has tight turning tracks, so we’re still sort of learning about how we can compare what sort of work will marry up at each place.
So far, have you already seen some differences between your two tracks?
Not yet. We’re sort of starting to get the times that they run, just in terms of sectionals. Our farm is substantially slower than Flemington’s would be, and the recovery is a lot more consistent at the farm, only since we’ve got the same sort of walk back after their exercise. It’s a very controlled environment.
On the other hand, Flemington is a much more stressful environment. There’s a lot going on, so the recovery can sometimes be different as they sometimes must drop back in. Their recovery can be a little more delayed at Flemington, so we find that you’ve probably got to be a little more forgiving of the environment that they’re in. The use of Equimetre at the farm has been good because the horses have to do basically the same thing when they’re walking back in. We can measure them from the same standardized point, which is generally about five minutes after their exercise, and this will certainly give us good guidance on where their fitness is at.
What do you want to gain from the Equimetre? And what do you expect from this technology?
Well, I think we just like to keep learning about horses. I mean, times have gone by, everyone has looked at a stopwatch and they’ve guided their own training on what times they’re running. We now tend to ignore the sections that they’re running and largely look at the horse, see what’s in front of us. And I think, first and foremost, we will still use our eyes to train horses, but the data will hopefully back up what you see. And if we say that something is off, we’ll refer to the data, and then we can start to work from there. We can consult our vets and show them the data and suggest that perhaps there’s something going on that’s underlying. Ultimately, the main goal is to get the best out of every single horse and be able to judge a horse, to have some transparency with owners, and to be able to say to them, “Look, this horse isn’t measuring up to where we expected it to.” I think it helps. Certainly, the more information you’ve got, the more we can look to use it however we please. But if you don’t have the information, obviously you can’t use it.
How does the data collection play a role in your decision making?
My father and I are in a partnership but we’re both a little bit different. So, my father’s a little more old- school, but he’s been very open to change, which I think is important, being able to adapt. And I’ve largely been trying to lead with this new way of at least giving us some information. I think it’s still not going to be the be all and end all. We’re not just going to look at a computer screen and assess a horse on that, but it has its role in sort of directing where a horse might go to, where it’s at in its preparation, or if the work that it did is consistent with its recovery. I think, obviously, the more you’ve got it on a horse, the better it is. If you can compare the same work on the same sort of track to the same horse.
How do you use the solution daily?
We use it in the stable and we’ve got a couple of key staff members that put it on the horses. In terms of analyzing it, we’ve got Melissa, who’s in the office with us who’s basically in charge of downloading all the data and assessing it and just giving her insights into it. She’s still learning about it all as we all are. But I think, the more we’re having it on the same horses, the more we can start to at least compare it with each other and they go to the races and there’ll be examples of horses with poor recovery that come out and run very well, but that could just be the recovery from that specific horse.
Do you have an example where data may have helped you to make a decision?
Yes! A horse we have was running in a race on Monday. It had its final piece of work on the Tuesday, so six days prior, and its recovery was poor. It took a long time to get back to a near resting heart rate and it was blowing quite hard after its work, which was a little bit unusual. I had the horse scoped trotted up. Nothing really showed up. We decided to give it a little bit more work later in the week. We still had some time before the race. We put a tongue tie on, and the horse’s recovery was much better. It subsequently won on the Monday with the tongue tie on and I don’t think that we could have been certain that she may have performed a level that she did without the addition of that. But that was just a small example of sort of where you can start to pick up on little things.
Keywords: Sam Freedman, experience, data, Equimetre, user story, decision making, technology