Member Statistics June 2022

 

JumpClear members averaged a 54% Clear Round Average in June.  While this is lower than we saw in May, it's in line with the rolling 12 month average.

Only one horse achieved a perfect 100% average.  Interestingly, he came from the FEI division!

Members were highly active across multiple competitions and a range of divisions.  Active members averaged 5.9 rounds over the month.  

Looking at Fault Source metrics, the most faulted course elements was an Other Oxer (28% of Faults). This is a consistent theme!  The next most faulted were Other Vertical (12%), Combination-Out Vertical (11%) and Liverpool Vertical (11%).  

In total, 35% of faults came from combinations, which is close to average.  

Looking at a few other metrics of note:

• 68% of faults came from a Related Technicality.  This is 10pp higher than the 12 month baseline.  Moreover, if we drill into this number, it isn't solely driven by Combination Faults (where Combination Mid and Combination Out are, by definition, "Related"; excluding Mid and Out, 60% of faults were at Related jumps.

• Other Oxer was the most faulted element for both Classes Over and Under 1.40.  However, there was a significant gap: it represented 38% of Faults over 1.40 and 29% under.  This is atypical - normally Other faults occur more heavily at the lower heights.
• Combination Faults did occur along their normal pattern - including all Combination Elements, Combinations made up 47% of Faults above 1.40 and 27% under 1.40.

Upperville Grand Prix Analysis by JumpClear

The CSI 4* Grand Prix at Upperville Horse Show was designed by Marina Azevedo and featured a 16 obstacle track.  5 of the 21 entries jumped clear (24%).

We saw a total of 29 faults in Round 1 (1.38 faults per entry).  

The single most faulted jump came at 11, the Liverpool Vertical on a related distance (21% of faults).  

Jump 8B, the Oxer Combination-Mid element of the Vertical-Oxer-Vertical combination was the second most faulted (17% of faults). Interestingly, neither the In nor Out element of the Triple were ever faulted! 

The only other jump on course not to be faulted was the Triple Bar single at jump 3.

In total, Combinations accounted for 28% of faults which is 10pp below average for a High Performance class.  If we count both Liverpools on course (jump 6 was a Single Liverpool Oxer), Liverpools accounted for 28% of Faults which is more than double average!  

The class was won by Schuyler Riley on Robin De Ponthual!

JumpClear Member Statistics May

 

JumpClear members excelled in May with one of the highest overall Clear Round Averages to date, boosted by performances from 6 horses with perfect 100% CRA.

Members averaged a 67% Clear Round Average.  This is about 10pp above the rolling 12 month average. 

Members were highly active across multiple competitions and a range of divisions.  The six horses with perfect averages were similar diverse and included horses from Medium Amateur to Open 1.45+.

Looking at Fault Source metrics, the most faulted course elements was an Other Oxer (23% of Faults).  The next most faulted were Combination-In Vertical and Combination-In Oxer (both 12%).  Other Vertical was fourth at 9% of faults (the least we’ve seen in several months). 

In total, 39% of faults came from combinations (slightly higher than the 12 month average of 31%).  

Looking at a few other metrics of note:

• 61% of faults came from a Related Technicality
• 56% of faults came at an Oxer, and of these, 71% were the front rail
• in Round 1, faults were split evenly by Front and Hind leg.  For the Jumpoff, faults were 85% with the Front Leg

Devon Horse Show Grand Prix Analysis by JumpClear

The Devon Horse Show's feature event is the Thursday night $250,000 Sapphire Grand Prix of Devon CSI 4*.  This year's class was designed by Olaf Petersen and featured a 16 obstacle track, contested by 30 horse and rider combinations.   

We saw a total of 24 faults in Round 1 (1.20 faults per entry).  7 entries (23%) of the class jumped clear.   

The final line of the course - repeatedly referred to as "heartbreak alley" on the live commentary - accounted for 46% of Round 1 faults! The single most faulted jump came at 12A, the vertical Combination-In element of the Vertical-Oxer Double set off the short turn (21% of faults).  Jumps 12B and 13 (a Liverpool Oxer set as the last jump off a related technicality) each accounted for 13% of faults.

The jump immediately preceding this line - a Liverpool Vertical set towards the ingate - also accounted for 13% of faults. 

5 jumps on course were never faulted.

In total, Combinations accounted for 50% of faults which is significantly above average for a High Performance class but this was driven by the final double, noted above; the triple combination at 5ABC drove just 17% of faults.

The class was won by Mclain Ward on Contagious for his 12th win in this grand prix!

Analysis of the Major League Show Jumping Grand Prix at Thunderbird - May 2022

 

The Major League Show Jumping Series kicked off for 2022 at Thunderbird Park with a 5* Grand Prix designed by Peter Grant.   

We saw a total of 36 faults (meaning a rail or refusal) in Round 1.  10 entries (33%) of the class jumped clear.   

The most faulted obstacle was a Plank (17% of faults in Round 1).  The Plank was set off a related distance following a Wall and constructed from a thin black panel.  

Three Jumps were equal for the next most faulted: the Oxer A element of the triple combination (Oxer-Oxer-Vertical); the related Liverpool Oxer; and the Oxer B element of the double combination (Vertical-Oxer).  Each was responsible for 11% of faults.  

Only two jumps on course were never faulted: Jump 4, a related Other vertical and the Last Jump Vertical.

In total, Combinations accounted for 39% of faults which is about average for a High Performance class.

The class was won by Jordan Coyle on Ariso  

Continuous Improvement and Showjumping: Getting 1% Better at Jumping Clear Rounds

 

JumpClear analysis enables approaching showjumping training through the lens of continuous improvement, aka, the 1% Improvement Rule. Under this approach, we would use JumpClear Fault Source Analysis to set measurable, achievable goals for progress based on incrementally reducing our most common faults.

I first read about 1% Growth in a biography by Valorie Kondos Field, the former coach of the amazing UCLA gymnastics team who compared the philosophy of getting 1% better day after day favorably to one of striving for - and falling short - of a standard of 100% perfection. She writes:

"The philosophy I do embrace is getting 1 percent better...Imagine an athlete one day getting 1 percent better in technique, form and mental discipline. Then getting 1 percent better in technique, form and mental discipline the next day. And the next day. Wow! The compounding effect of such incremental improvement would reach near super-hero status, but it is also absolutely achievable."  

Takeaway 1:  set measurable, achievable goals

Takeaway 2: such goals add up to big results 

James Clear explains this theory further (and adds some math) in his book, Atomic Habits, Tiny Changes, Remarkable Results. Clear cites the effects of simply improving 1 percent every day and calculates, if you were to improve at an activity 1%, you would improve results by 37 times in one year! 

How does this relate to showjumping?  

It's actually kind of hard to align showjumping with a 1% growth approach.  

While the outcome of a round itself is clear - we have a score and placing - what we often understand as the drivers of success and failure - the things that we chip away at daily - aren't measurable.  (Am I 1% better at shortening my reins?).  As a consequence, regardless of level - and especially if we've been in the sport for a long time - progress towards goals can feel really amorphous.  

JumpClear was designed to add a layer of quantifiability to some of the things which go into jumping a clear round - and while we can't measure improvement in rein length, Fault Source Analysis delivers a data-driven understanding of a horse & rider's most common faults.  In doing so, we aim to give riders a tool to see the goal of jumping more clear rounds through the lens of measurable, achievable components, i.e, focusing on and reducing specific fault areas.    

Old Salem Farm Spring Grand Prix Week 2

The Grand Prix during the second week of the Old Salem Farm Spring series, like Week 1, was designed by Alan Wade and held during the day on the new sand international arena at the OSF Venue. It was a CSI4* versus the CSI3* held Week 1. We'll provide some analysis of this week's class and some overall thoughts comparing the two weeks.  

We saw a total of 45 faults (meaning a rail or refusal) in Round 1.  There were 31 competitors so each entry averaged 1.42 faults.  13% of the class jumped Clear in Round 1.   

Interestingly, while the average faults per entry is similar to last week where the 33 competitors averaged 1.42 faults, the percent clear last week was twice as high (27%).  (Simply, many more horses had just a single rail this week.)  A likely factor: the time allowed played a significantly greater role this week; more than half the class incurred at least one time fault (just 3 entries did last week).      

The most faulted obstacle Week 2 was a Combination-Out Oxer, (Vertical-Oxer combination).  This jump was responsible for 18% of faults in Round 1.  

The next most faulted jumps were the A element of the same combination (16%) and the related liverpool vertical immediately following this combination (13%).  

In total, the Double Combination at 10AB was responsible for a third of Round 1 Faults.  In comparison, the Triple Combination caused relatively little trouble - accounting for just 11% of faults.

If we compare both Grand Prixs, both classes utilized a Triple Combination and one Double and Combinations were clearly a key driver of faults!  A combination element was the most faulted jump both weeks.  All combination elements combined accounted for 57% of Faults Week 1 and 44% Week 2.   (Both are significantly higher than the average for Combination Faults in a High Performance Class which we are seeing around 37%.)

The class was won by Mclain Ward on HH Azur.  

Old Salem Farm Grand Prix Analysis (Spring 1. May 15, 2022)

 

The Grand Prix during the first week of the Old Salem Farm Spring series was a CSI3*, designed by Alan Wade.  It was held during the day on the new sand international arena at the OSF Venue. 

We saw a total of 47 faults in Round 1.  The most faulted obstacle was a Combination-Mid Oxer, (Vertical-Oxer-Vertical combination).  This jump was responsible for 17% of faults in Round 1.  

The next most faulted jumps were the A element of the same combination and a single other oxer (the jungle themed oxer with green rails immediately preceding this combination).  Each respectively caused 13% of faults.

In total, the Triple Combination was responsible for 38% of Round 1 Faults; moreover, if we also include faults from the Double Combination at 10AB, Total Combination Faults = 57% of Round 1 faults!  (This is significantly higher than the average for Combination Faults in a High Performance Class which we are seeing around 37%.)

All jumps except 2, an Other Related Oxer, were faulted at least once. 7 other jumps were each faulted only once.  All in, of the 16 course elements, half were responsible for 85% of the faults in Round 1!

The class was won by Jordan Coyle on Centriko Volo.  

JumpClear Member Statistics April

 

Overall, we saw significantly less activity from JumpClear members during April, as might be expected during what many use as a transition month between the winter and summer season.  

Only 1 in 4 members were active.  For those who did compete, Average Rounds per Month were lower than usual - 3.5 versus an average just under 5.0.  75% of horses competed in just one competition.  

Members who showed averaged a 38% Clear Round Average.  This is significantly below the baseline.  

Looking at Fault Source metrics, the most faulted course elements continue to come from the "other" Jump Detail with Other Vertical driving 28% of Faults and Other Oxer 17%.  The next most faulted were Combination-In Vertical (14%) and Liverpool Vertical (14%).  

Keeping in mind we are considering a fairly small number of faults, a few more detailed points of note:

• 70% faults were at Related jumps (versus 53% in the baseline)
• 72% of faults were at Vertical jumps (versus 49% in the baseline)
• for classes 1.40 and above, 47% of faults were at Other; 41% were at a combination element. For classes below 1.40, 42% of faults were at Other.  Just 8% were at a combination element.  (Note: this is an exaggeration of a trend previously discussed that Combinations comprise a higher percentage of faults as jump height increases).  

Performance Goals Part 2: Using Data to Make a Plan

JumpClear is a great tool for identifying your best opportunities to improve your results and setting measurable goals.

Yesterday we gave an example of using JumpClear data to identify an opportunity for improvement and set a goal.  But now what?  What do you do with all these numbers?  

(To be clear, JumpClear data isn't going to be a silver bullet.  The goal is to give a rider & trainer information to identify a challenge and be part of their overall tool kit for horse management and training). 

Fault Source Analysis encompasses 6 metrics.  We only used Jump Detail to set our goal but the data around the other metrics tells us a lot more about this particular challenge.

Using the same example - which full disclosure, is one of my horses - this is what happens when you zoom in on just Skinny jumps:

100% of faults are off the left lead

100% of faults are with a front leg

60% are at a single technicality

Hmmm...We now have a pretty consistent defined situation to problem solve and maybe come up with some mental cues. 

We also have a really concrete and bite-sized goal.  Recalling the "Model" course jump distribution, Skinny Jumps were calculated to be 4.7% of total jumps over 12 months.  If we use some other data around the average number of classes JumpClear members contest, that comes out to 24.8 Skinny Jumps.  If we assume they are evenly spread across leads, we're down to 12.4 Skinny Jumps to make a particular focus.  

Over a year of jumps, that feels like we've narrowed it down to a pretty achievable goal!

Using JumpClear to Set Performance Goals

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):

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We start with a horses faults for the past 12 months.

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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!

Comparing Faults Types Between Different Horses

In the last post, we analyzed the baseline distribution of the Jump Detail fault metric and compared it to a hypothetical modeled course.  Our conclusion was on average, faults aligned well with the frequency different types of jumps occurred.

However, there are significant differences between individual horses.  These different fault distributions reflect the behavioral asymmetries of horses & riders and are the basis of JumpClear's Fault Source Analysis methodology.  

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Standard Deviation measures the variance within a range of numbers. Here, it is used to capture the difference between the fault patterns of the individual JumpClear member horses.  We see the SDs are all large compared to the absolute values for the Baseline values.

Likewise, when we calculate a Fault Range of + or - one Standard Deviation, there is huge variance in possible outcomes.  There are 7 metrics alone where horses could vary from no faults (a negative value is calculated) to up to 10%! 

Going forward, JumpClear will use this approach of comparing a horse's fault distribution to the Baseline and Standard Deviation Range as part of identifying each horse's unique opportunities for improvement.   

Are Some Jumps Faulted More Frequently? Analyzing Fault Distribution for Showjumping

 Are some jumps faulted more than others?  Is it because they're "harder" or just used more frequently?  We looked at the data to find out.

The Approach:

We designed a model course to arrive at an approximate distribution of jump types.  The Course was based on an average of 10 different jump configurations to capture different Combination Types, and use of elements like Liverpools, Skinny Jumps, Planks, Walls and Water.  

We calculated the percent each element comprised within the model course and compared that to Baseline Data for JumpClear members for their Fault Distribution for Average Round 1 Faults over a 12 month period.  

Findings

Overall, the Model Course aligns very well with Average Faults.  This data suggests that faults - viewed as an average across multiple horses and rounds - occur roughly in proportion to the frequency of the type of course element.  Otherwise said, no particular jump is a bogey causing a hugely disproportionate amount of faults.

We know, however, that faults vary significantly between individual horses.  We'll look more closely at this in the next post.

Showjumping Course Analysis Combination Elements

As the JumpClear database grows, it's exciting to deliver more insights based on total member data.  Here we take a deeper look at Combination Faults...

Starting with the basics, Combinations - across all elements - made up 34% of Round 1 Faults for JumpClear members over the past 12 months.  They were a much smaller percent of faults in the jumpoff - just 15%.  

There numbers are interesting because they suggest that combination faults come down to simple math.  Combinations are faulted roughly in proportion to the percent they make up of total jumps on the course*; they are not - in fact - horrible bogey obstacles that stand in the way of every horse & rider's clear round.

(If you want to check that math: the average first round has between 12 - 14 numbered jumps with somewhere around two doubles and a triple or two doubles, so 19 to 21 obstacles of which combinations comprise 6 or 7.  The average jumpoff has about 7 - 9 numbered jumps with one double, so about 9 to 11 obstacles of which combination elements make up two).  

However, we see that combination faults differ quite significantly by division.

As a general rule, the lower heights have fewer combination faults.  This is largely - but not entirely - driven by the impact of the "mid" element and likely reflective of the limited use of triple combination in the 1.30 and 1.20 national classes.

By a slight margin, the most rails come from the Combination In Element.  Across all elements, faults are split nearly evenly between oxers and verticals.

WEF 2022 Grand Prix Analysis

 

Each week of WEF, JumpClear analyzed the Grand Prix to provide stats on the most faulted course element.  We also tracked overall faults across the 13 weeks.  Here's what we learned!

There were 551 First Rounds throughout the Season (data includes the highest level grand prix each week).  119 (22%) were clear.  The highest clear round average came in Week 6, a 3* where Catalina Cruz was the course designer.

There were 772 unique Round 1 Faults.  

• The most frequently faulted course elements were an Other Oxer (13%) and Other Vertical (10%)
• The least faulted were a wall, a triple bar, the first jump (all jump types) and a Last Jump Vertical.  All were 1% or less of total faults.  (Interestingly, last jump oxer was much more heavily faulted (7%)
• Combinations made up 37% of faults in total: the most faulted combination element was a Combination-in Vertical
• The most faulted Combination Type by a significant margin was an Oxer-Vertical (27%).  Vertical-Oxer (18%) and Vertical-Oxer-Vertical (15%) followed.  

Industry Insights Based on JumpClear Member Statistics (March 2022)

 

JumpClear members averaged a 53% clear round average in March.  This is in line with the 12 month average.  

This is the first month where no horse achieved a perfect 100% clear round average.  The highest average was 80%

Average Rounds/Month was 6.9 which is the highest we've seen.  

Looking at Fault Source metrics, the most faulted course elements continue to come from the "other" Jump Detail with Other Oxer driving 28% of Faults and Other Vertical 22%.  The next most faulted were three Combination elements: Combination-In Oxer, Combination Out-Vertical (both 11%) and Combination-In Vertical (10%). 

Lovsta Future Challenge Final

 

Lovsta Future Challenge - Jumping

The Lovsta Future Challenge is a tour for 7 year old showjumpers in Wellington.  The vision is to give young jumpers the best conditions to develop towards top international sports.   

49 horses qualified for the final by jumping at least 2 clear rounds in the 7 qualifiers held over the course of the winter.  On average, we saw a 55% clear round average during the qualifers.  

The top qualifers are shown below.  Note the eventual winner, Cinderella and Beat Mandli, was tied for the top performance going into the final!    

 

Looking by breed, Dutch Warmbloods (KWPN) made up over 1/4 the qualifiers.  Belgian Sporthorses and Selle Francais were the next most represented.  The most popular stallions were Balou du Rouet and Emerald.

JumpClear conducted fault source analysis throughout the qualifiers.  In general, we see a very similar pattern in young horses to the baseline with Other Vertical and Oxer emerging as the most faulted, followed by the combination elements.  

Member Statistics February 2022

 

JumpClear members averaged a 51% clear round average in February.  This is a significant decline from January but more in line with the 12 month average (54%).  

Their Round 1 Clear Round Average was nearly 20 points below the Jumpoff Average (45% vs. 65%); this is a slightly larger gap than usual.

Two horses achieved a perfect 100% Clear Round Average.

Members averaged 4.6 Rounds/Month and 2.7 Faults (# of Faulted Jumps).  Both are higher than January but more in line with the volume we saw late last Fall, suggesting Members may have been just gearing up for the season in January.  

Looking at Fault Source metrics, the most faulted course elements continue to come from the "other" Jump Detail with Other Oxer driving 23% of Faults and Other Vertical 15%.  The next most faulted was a Combination-In Vertical (10%).  

If we drill into more detail, Other Singles Oxer resulted in 13% of Faults; Other Related Oxers resulted in 10%.  

Lovsta Future Championships - Qualifier 6

Lovsta Future Challenge - Jumping

JumpClear is excited to partner with the Lovsta Future Challenge to provide analytics supporting its US Jumping and Dressage Future Challenge!

The Lovsta Future Challenge is a tour for 7 year old showjumpers in Wellington.  The vision is to give young jumpers the best conditions to develop towards top international sports. 

Each week, JumpClear will provide topline statistics on Qualifying horses.  As the tour progresses, we will dive deeper into overall series metrics including Fault Source metrics.  Analysis will also cover the breeding and development of top qualifiers.  Stay tuned!

WEF Grand Prix Analysis (Fault Source)

 

We've studied all WEF Grand Prix classes from 2020 and 2021.  Here's what we learned about the most typical faults across all classes and by course designer!

Across all classes and CDs, the most faulted jump based on a combination of JUMP TYPE and JUMP DETAIL metrics was an Other Oxer (15%) followed by an Other Vertical (11%) ("other" means there was no special detail associated with it).  In total, combinations represented 40% of all faults, with the most by a small margin delivered by a Vertical Combination-In.

Faults by Jump Detail by Course Designer

When we look by Course Designer, differences start to emerge in the CD's respective use of combinations, how significant the last jump is, whether special jumps like the wall or water were used and so forth.  

WEF Grand Prix Analysis (Percent Clear)

 

Heading into the 2022 Grand Prix season, we though it would be interesting to share some analysis of prior WEF circuits.  We've studied all Grand Prix classes from 2020 and 2021 - that's nearly 2000 rounds, 350 unique riders and 730 unique horses!

Here's what we learned!

All classes combined resulted in a 28% Clear Round Average.  Riders were twice as likely to jump clear in the jumpoff than in Round 1.  These statistics were consistent between 2020 and 2021.

  Interestingly, if we consider Clear Rounds by Level, the lowest percent clear occur in 5* and National classes.  2* classes saw the highest percent Clear Rounds.  

  Night classes saw significantly fewer clear rounds than classes during the day.

  Classes held on grass had the most clear rounds.  However, we need to consider that these classes were also all 100% held during the DAY; NIGHT classes brought down the clear down average in classes held in Large Sand (the International Arena).

Clear Rounds by Course Designer

If we look at the fault distribution by Course Designer, Anderson Lima, Alan Wade and Eric Hasbrouck had the most clear rounds; the lowest were in classes designed by Nick Granat, Mauricio Garcia and Andy Christiansen.  

2021 Member Statistics: Fault Source

 

The most frequently faulted course elements for members during the 2021 competition year were an Other Oxer (25%) followed by an Other Vertical (15%).

If we drill down a third metric, a Front Rail Other Oxer contributed 15% of Faults.

Combination-In Oxer (9%) and Combination-In Vertical (7%) were the next most faulted.

In general, we consistently see the "Other" Jump Detail represent the most faulted course element by a wide margin.  Often, as we see here 2 or 3 metrics can be added to the analysis (for example, JUMP TYPE and RAIL) before any other Jump Detail reaches the same percentage of faults.  

2021 Member Statistics: Clear Round Average

 

JumpClear members averaged a 52% Clear Round Average during the 2021 competition year.  Their Clear Round Average in the Jumpoff was over 20pp higher than in Round 1.  

Members averaged 42 Rounds per Year, 31 in Round 1 and 11 in the Jumpoff.

If we look by division, the Clear Round Average was highest in the 1.20, followed by the 1.25, 1.30 and 1.25 Open Divisions.  The lowest Clear Round Average was in the High AO/JRs and the Grand Prix.

By Rider Status, we see a sizable gap between Pros and JR/AOs with Pros achieving almost a 10pp higher Clear Round Average.