ERQI Ratings

Yesterday USEA rolled out a brand new feature to their membership: ERQI ratings. What the heck is ERQI? In USEA’s words:

The ERQI (EquiRatings Quality Index) is a risk management tool that assigns a value to each USEA competing horse. The ERQI is calculated as a probability, a number between 0 and 1, with horses closer to 1 showing statistically higher levels of positive performance in the cross-country phase. ERQIs are displayed on each horse’s profile in a color code representing the level of risk the horse carries on cross-country. The ERQI is built on the ‘data footprint,’ (the past results) of each horse, and applies a marginal gains approach to improving fall rates.

Basically, layman’s terms, Equiratings takes the horse’s record and uses that to decide how likely you are to die on XC at each level. The more you progress up the levels, and the more clear rounds you accumulate at each level, the more boxes turn green and yellow.

HenryERQI
Henry’s ERQI
  • Green/Light Green: Horse at this level is competing with the normal amount of risk.
  • Yellow: Horse at this level is competing with a slightly higher level of risk than normal.
  • Orange/Amber: Horse at this level is competing with a much higher level of risk than normal.
  • Red: Horse at this level is competing with the highest level of risk.

They started a program like this in Ireland a couple years ago and saw a decrease in falls on XC at the higher levels. This year the US is trying it out, and Britain and Australia are supposed to be the next ones up on the docket for some kind of implementation.

The ratings are attached to each horse, not each rider. As a risk-assessment tool, I think it’s pretty neat. In this sport I feel like the more information we have, the better our decisions will be. You can only view the ratings attached to horses that you have shown or own, so they aren’t public.

Image result for equiratings
these handsome Irish chaps are hardcore judging you right now

But what does this really mean? Not much. At this point the ERQI ratings are purely informational and don’t determine qualification for anything. We still have the same qualification criteria for Prelim and above that we had before. So far (the verbiage USEA uses makes it seem like this may change in the future) they’re really just meant to be another data point that riders can use to help them make better decisions on what to enter or where a horse is at development-wise.

Granted, for most of us low level people, it’s a bit inconsequential. There’s also a lot that these ratings can’t take into consideration. It’s looking for clean rounds, and we all know that at the lower levels it’s possible to have a clean round but still be kinda scary. It can also only use results from USEA-recognized shows, obviously, so any results at schooling shows (or shows in Canada, for those near the border) aren’t included. There are definitely holes here, but there are some things that just can’t be measured in data points and probably never will be.

PHPWagon
such as “did the rider crap their pants over any particular fence?”

Is the ERQI a be-all, end-all tool that should be used as THE deciding factor for what a horse and rider are capable of? Probably not. Like this thing is pretty convinced that Henry and I would not die if we ran Prelim, whereas I’m over here like “I dunno, I’m like 50% sure that we might.”. So there’s that.

Interested in learning more about ERQI? There’s a handy dandy FAQ page already on the USEA website here.

What do you guys think of these new ERQI ratings? Will it have any influence on your competition schedule? Do you think it’s a useful tool? And, maybe more interestingly, do you think this kind of assessment tool has the potential to spread to other sports in the future (ie jumpers with a “clear round” rating)?

 

12 thoughts on “ERQI Ratings

  1. It sounds like a good idea. It will be refined as peopel use it.
    I think it may be helpful. I remember well, a well-known professional eventer riding a horse, that had a few falls on 3* starts X-C. Until finally that horse broke its neck and the rider its collarbone on a 4 *star event. I was suprised that combination could go on 4* stars X-C as they had fall on 3*stars event? Perhaps this tool will help to avoid this type of accident.
    I kept the gender of horse and rider neutral, for keeping anonymity. I don’t like naming and shaming. But Perhaps because that rider had connections, it was left to compete. It was in Europe.
    So hopefully this system will avoid this leniency.

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  2. I think it can be a handy tool, for the middle to upper levels especially…
    But only if people heed the warning. I hope it will help keeping more horses and riders safe…

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  3. so in my professional (non-horse) world, my job is basically creating ERQI ratings (ie, probability index scores) assessing the relative likelihoods that any given constituent will exhibit a certain behavior, predicted based on past behaviors and known attributes. this is an extremely applicable field in all aspects of business analytics and has been in heavy use by the private sector for…. ages (hi, Amazon recommended products! hi, baseball’s “Money Ball”!!). the non profit sector started picking it up over the last decade or so, and that’s where i focus my efforts.

    at it’s heart, this type of analysis is intended to leverage available data to better understand where and how to allocate resources more effectively so that the entities employing the ratings can reach the outcome they want with less margin of error and greater ROI. when applied specifically to horse sports, the idea is that competitors and owners can use a tool like this to focus efforts on advancing the horses that appear likeliest to succeed, and diverting less successful (ie, safe) horses either into programs to help them improve, or make choices to not continue investing in a horse’s potential upper level career when it does not appear to have a high likelihood of success (ie, safety). and eventually, these same scores can be used in conjunction with other qualifications criteria to ensure that each horse advancing in the upper levels has demonstrated a solid record and foundation of safety.

    there are limitations tho, like you say. the models can only know the data you feed them. a horse with a very limited data history will be harder to rate than a horse who has a very complete history. plus, there are all those intangibles and external environmental factors that become very difficult to control for. so… you end up in this whole “art and science of competing horses” scenario. the science offers us so much in better understanding our horse’s performance and progress, but we ignore the “art” of horses at our own peril.

    ultimately i expect this system to be successful, honestly, if it’s implemented and communicated in a way that makes sense – so users understand what it *does* and *does not* mean. not sure it’ll make much of a difference at the lowest levels (starter/bn/n) but i see it as being extremely helpful in fleshing out the already existing set of anecdotal “best practices” when it comes to moving horses up the highest levels.

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    1. I do very similar type things and I know Olivia does some of this too. Data nerds for lifeeeee. I love me some business analytics. You also explained all my comments better than I would have so I’m not even bothering to write my own. So long as we remember junk data = junk model/results, limitations of things that can’t be measured and correlation ≠ causation (I seriously might say that 100 times a week to people), it’s useful data. I think the idea of some objectivity measurement is always helpful in reducing bias we may already have (confirmation bias anyone?) and can hopefully provide yet another piece of information for consideration in making decisions.

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    2. Another potential use I would see this would be in sales- sure, someone is advertising their horse as a Prelim packer, but what does their rating say about their real ability to navigate that level? It provides more transparency there. Like you say though, this can backfire if they just had one run at that level and it went poorly- they may have plenty of ability and just need some schooling, but their perceived value could drop in a sales situation.

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      1. They’re not publicly viewable at this time, so the rider or owner of the horse would have to release that information for the buyer to know it. I can see both good and bad sides to making them public. Of course, we already have very very public, very complete show records that anyone can view just by looking a horse up, so I don’t know that the ERQI would really add much value beyond that from a buyer’s perspective. It’s still really interesting though, I’ve enjoyed looking at my friends’ horses’ ratings as they’ve shared them, just to see how they’re all stacking up. Gives you insight into how the ERQI works.

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  4. I think it’s really quite interesting. I would love to see where they think me and Moose could go. Although with the only USEA event that is in our record where we had a stop, I doubt it will be incredibly favourable or (I hope) accurate!

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    1. It doesn’t really calculate “potential”, it’s more of a “how much risk are you going to be in if you enter that level RIGHT NOW”. Which is kind of moot if you aren’t qualified for said levels, but definitely interesting anyway. So as you move up the levels, and as you do more horse shows, your ERQI will change. And yeah, the more data points it has, the better it is.

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  5. I definitely foresee this really helping. There isn’t much I can say that others haven’t already (and 10x more coherently than me) but I can say that I agree with you. I can see it helping a lot, but I can also see it’s limitations and also that it really is only as helpful as those who may take it into consideration. I think it’s a great tool to start out with right now though, and I think we will find ways to refine it and help it come along 🙂

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  6. Man I really hope this doesn’t spread to SJ hahaha. I definitely see this as hugely helpful in assessing safety over solid obstacles, but I’m not sure it’s as applicable in the colorful sticks realm. For example, Frankie and I had way more rails in the 1m classes than we do at 1.10-1.15m. Part of that was just building his education, but a big part of that is that the bigger sticks get his attention and encourage a cleaner effort from him. I know we’re just one data point, but I know of plenty of horses that are lazy at the lower heights, but are more interested and careful once you pose a challenge.

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  7. I actually really love the idea of this.

    I think it would be really useful further down the track when it is a bit more established to help determine if a combination is ready to move up a level.

    I have seen some downright scary people who think that despite never having a clear 95 run around XC they want to step up to 105 regardless.

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