JumpClear uses Fault Source Analysis to identify opportunities for horses & riders to improve their performance by showing the areas where they have a higher percentage of faults.
Recently, we've been expanding this analysis through comparing an individual member's performance to average or baseline fault distribution.
We use this approach as the basis for setting unique performance goals for horses: the logic is essentially finding fault metrics where the horse significantly differs from average performance and calculating how it could be performing if its faults were more like the average.
Here's how it works (this is a real example):
🠉We start with a horses faults for the past 12 months.
We compare that to the Average Fault Detail distribution. This is where we can identify Target Areas where a horse's faults differ significantly from the average. Here, we highlight Skinny jumps which are more than 5x average!
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Then we multiple the Average by the horse's Actual Total Faults for the past 12 months to get the expected number of faults for the jump detail in our Target Areas.
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Finally we calculate the difference between the Expected and Actual Faults. This tells us the change in faults possible if the horse improved its Target Areas to the Average.
Here, this horse could decrease its Total Faults by 15% if she improved this one fault area!



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