Beyond the Discussion on Going

As any British racegoer or Racing TV watcher knows, our national obsession with discussing the weather is matched only by our fixation on debating racecourse going. Yet for all our sophisticated technological advancements—we've sent rovers to Mars, decoded the human genome, and created phones smart enough to remind us we've spent too much time looking at them—we're still remarkably primitive when it comes to telling punters precisely how soggy the ground is at Haydock on a drizzly Tuesday afternoon.

The consequences of this technological lag extend far beyond mere inconvenience. Trainers make career-defining decisions based on going reports, owners invest thousands in entry fees, and the betting public wagers millions daily—all relying on measurements that would make medieval farmers chuckle. This article explores the surprisingly complex world of going measurement and proposes a more enlightened path forward.

From a behavioural modelling perspective, the current system creates a perfect storm of perverse incentives, cognitive biases, and strategic misreporting. The asymmetric information flow provides insiders with significant advantages, while stakeholders modify their behaviour based on potentially flawed data—a textbook example of how institutional inertia reinforces suboptimal equilibria in complex systems.

Current Measurement Techniques: More Art Than Science

The Going Stick: A Glorified Poking Device

The TurfTrax Going Stick, introduced in the early 2000s, represents our most advanced technology in this field—which is rather like saying the finest abacus represents the cutting edge of supercomputing. Using this device involves walking around a racecourse at ungodly hours, stabbing the ground repeatedly, and trying to look thoughtful while staring at numbers that fluctuate more dramatically than the odds on a well-backed favourite.

The device measures two components:

1. Penetration: How easily the probe sinks into the turf (similar to how quickly your wellingtons disappear at a waterlogged Aintree)

2. Shear: The force needed to rotate the device (comparable to the effort required to extract said wellingtons)

These readings combine to produce a numerical value, typically between 5 (heavy enough to grow rice) and 10+ (firm enough to host a cricket match). The fundamental problem is that this measurement, however precise the device might be, is only as good as its implementation—and therein lies the rub.

Traditional Methods: The "Walk and Squint"

Despite having this technological marvel, many racecourses still rely heavily on:

The "morning constitutional" (walking the course while nursing a thermos of tea)

• The traditional wooden stick (a technology unchanged since the Bronze Age)

• The highly scientific method of "having a good look at it"

What's particularly remarkable is how these traditional methods often contradict the GoingStick readings, leading to the curious phenomenon where numerical data is overridden by someone's feeling about the ground. "The stick says 8.2, but it feels softer to me, so we'll call it Good to Soft." This subjective override would be unthinkable in most other data-driven fields, yet in racing, it's standard practice.

The Spectacular Failures of Going Reporting: A Tragicomedy in Multiple Acts

The BHA's Spectacular Accountability Vacuum

The British Horseracing Authority's approach to enforcing going measurement standards might best be described as "enthusiastically laissez-faire." Despite having the regulatory power to impose meaningful sanctions, the BHA has consistently failed to hold clerks of the course accountable for inaccurate going reports.

This accountability vacuum manifests in several ways:

1. No financial penalties: Unlike other regulatory breaches that attract significant fines, inaccurate going reports—even those that directly impact horse welfare and betting markets—result in no financial penalties. A clerk who consistently misreports ground conditions faces no more than a strongly worded letter.

2. Absence of performance metrics: The BHA has failed to implement any system for measuring the accuracy of going reports against objective criteria such as race times or sectional data.

3. Regulatory capture: The close relationship between the BHA, racecourse executives, and clerks has created an environment where rigorous enforcement is subordinated to maintaining comfortable working relationships.

4. Self-regulation failure: The delegated responsibility for accurate reporting without meaningful oversight has predictably resulted in a system that prioritises commercial interests over accuracy.

As one industry insider anonymously noted: "If a jockey misreports their weight by half a pound, they face immediate sanctions. If a clerk misreports the going by two categories, affecting millions in betting turnover and horse welfare, nothing happens."

Data Collection: Sampling Bias Extravaganza

From a statistical perspective, the current sampling methodology is about as sound as predicting national election results by surveying your local pub. Consider these fundamental flaws:

1. Woefully inadequate sampling: Measurements taken at 10-30 locations on a course spanning dozens of acres. That's like assessing London's traffic by checking three streets.

2. Temporal irrelevance: "We measured it at 7 am, it's now 3:30 pm and has been raining for four hours, but we're sticking with 'Good to Firm'."

3. Human variability: Different individuals apply different pressures when using the GoingStick. Some could double as Olympic javelin throwers; others have the upper body strength of a tired kitten.

4. Strategic sampling: There's an unspoken art to knowing which parts of the course to measure. Mysteriously, the boggiest sections rarely seem to make it into the official readings. One might call this strategic omission; statisticians would call it selection bias.

Reporting: Creative Fiction at Its Finest

The going report often seems like it was written by the same person who assures you that your train is "delayed by just a few minutes" when you can clearly see it on fire in the distance.

1. Categorical oversimplification: We reduce complex, continuous data to vague categories. Imagine if weather forecasts just said "Wet" or "Not Wet." The difference between the upper and lower bounds of "Good" ground could be the difference between a horse performing brilliantly or pulling up lame.

2. Commercial pressure: There's an unmistakable commercial incentive to report better ground than actually exists. "The ground is actually Heavy, but if we report that, half the field will withdraw, so let's call it 'Soft, Heavy in places' and hope no one notices when the horses are splashing."

3. Lack of transparency: The full Going Stick readings are treated with the secrecy level of nuclear launch codes. Imagine if the Met Office decided to keep actual temperature readings secret and just told you it was "Quite Warm" or "Rather Chilly."

4. Course inconsistency: "Good to Firm" at Newmarket might as well be "Moderately Squelchy with a Chance of Bog" at Ffos Las. This spectacular lack of standardisation means that going descriptions are essentially racecourse-specific dialects rather than a universal language.

The Standardisation Catastrophe

Perhaps the failure of the current system is the complete absence of standardisation across different racecourses:

1. Inconsistent measurement protocols: Each racecourse has developed its own traditions for when, where, and how to take Going Stick readings. Some measure along the racing line, others at various distances from the rails, and some apparently use a divining rod and spiritual guidance.

2. Reporting format chaos: The BHA has inexplicably failed to mandate a standard format for going reports. Some courses provide detailed numerical breakdowns by section, others offer vague generalities about the entire course, and still others produce reports that read like creative writing exercises.

3. Timing inconsistencies: Going updates are issued at different times relative to racing across different courses. Some provide regular updates throughout the day; others issue a morning report and then maintain radio silence as conditions evolve.

4. Terminological confusion: The supposedly standardised going categories are applied differently across courses. What constitutes "Good to Soft" at one venue might be reported as "Good, Soft in places" at another, despite identical conditions.

5. Regional variations: Northern courses, particularly those with heavier rainfall, appear to systematically report drier ground than their southern counterparts facing equivalent conditions. This regional bias further undermines the already tenuous value of going descriptions.

Data Analysis: When Numbers Reveal the Emperor Has No Clothes

Statistical analysis of race times versus reported going reveals discrepancies that would make even the most creative accountant blush:

• At Newmarket in 2020-2021, horses running on officially identical "Good to Firm" ground showed time variations that could only be explained if some were actually running through treacle while others had discovered teleportation.

• Comparative pace figure analysis shows that the connection between going descriptions and actual ground conditions has all the reliability of a three-legged chair. Races run on supposedly identical going at the same course can produce finishing times that vary by several seconds—an eternity in racing terms.

• One particular race at Ascot was run on ground officially described as "Good," yet produced times slower than races run on "Heavy" the previous month. Perhaps the horses were simply having an existential crisis en masse.

• Analysis of betting markets reveals an intriguing phenomenon: professional gamblers effectively discount official going reports entirely, instead relying on private intelligence networks and visual assessment of early races on the card to determine actual conditions.

• The sectional timing data—where it exists—tells a damning story. Horses running on the same official going can produce first-to-last sectional time differentials that vary wildly, suggesting fundamentally different ground conditions despite identical official descriptions.

The Ripple Effects: Beyond Betting and Racing

The implications of inaccurate going descriptions extend far beyond mere inconvenience:

1. Horse welfare concerns: Running horses on ground significantly different from what was expected increases injury risk. Tendons and ligaments prepared for Good ground behave very differently when subjected to Heavy going.

2. Training disruption: Trainers plan entire campaigns around expected ground conditions. When these prove wildly inaccurate, months of careful preparation can be undone in moments.

3. Economic impact: The British racing industry generates over £3.5 billion annually for the UK economy. A significant portion of this derives from betting activity, which is fundamentally predicated on fair and accurate information being available to all participants.

4. Integrity perceptions: In an era where sports integrity is under increasing scrutiny, maintaining transparent and accurate ground condition reporting is essential for public confidence.

5. International competitiveness: As global racing becomes increasingly data-driven, the UK risks falling behind international competitors who have embraced more sophisticated measurement systems.

Solutions: Dragging Going Measurement into the 21st Century

Enhanced Measurement Protocol: More Data, Less Guesswork

1. Grid-based measurement: Implement a standardised 100+ point measurement grid across all courses. Yes, this means more walking. However, the comprehensive data would transform our understanding of course conditions and variability.

2. Continuous monitoring: Install permanent sensors around the course. The technology exists—we use it for agricultural soil monitoring, yet somehow it hasn't reached the racing industry, which is worth billions. These sensors could provide real-time data on moisture content, temperature, and compaction at various depths.

3. Standardised methodology: Train all officials to use consistent pressure and technique. Perhaps consider robotic measurement devices for absolute consistency. The technology for this already exists in agricultural soil science.

4. Depth profiling: Measure conditions at multiple depths. Surface conditions can be misleading—a dry crust might conceal sodden ground beneath, particularly relevant for larger, heavier horses whose hooves penetrate deeper.

5. Drainage mapping: Create comprehensive maps of course drainage patterns. Some sections of a racecourse will inevitably dry or become waterlogged faster than others. Understanding these patterns would allow for more nuanced reporting.

Improved Reporting Framework: Honesty is the Best Policy

1. Numerical precision: Report actual Going Stick readings rather than vague categories. "The going is 7.2" tells us far more than "Good to Soft, Good in places" (which essentially means "We're not really sure").

2. Course-specific calibration: Develop course-specific scales that acknowledge that "Good" at Cheltenham is fundamentally different from "Good" at Lingfield. Create conversion factors between courses to allow meaningful comparisons.

3. Sectional validation: Use race times and sectional data to verify going reports retrospectively. This would create accountability and improve future assessments.

4. Moisture content reporting: Supplement Going Stick readings with actual soil moisture content measurements—a far more objective metric used widely in agriculture and soil science.

5. Microclimate consideration: Acknowledge and report on how different parts of the course may vary. "The back straight is significantly softer (6.8) than the home straight (7.5)" provides genuinely useful information rather than averaging everything into meaninglessness.

6. Historical benchmarking: Provide context by comparing current conditions to previous significant race days. "The ground is similar to Champions Day 2021" offers valuable context to those familiar with how races unfolded on that day.

Technological Innovation: Yes, We Can

1. Ground-penetrating radar: The same technology used to find archaeological remains could map subsurface moisture and composition. This would reveal the crucial deeper layers that affect how horses travel through the ground.

2. Drone mapping: Thermal and multispectral imaging could create comprehensive going maps showing variations across the entire course. These technologies are already widely used in precision agriculture to measure crop health and soil conditions.

3. AI prediction: Machine learning algorithms could integrate historical data, weather patterns, and drainage characteristics to predict going changes. If Netflix can predict what show you'll watch next, surely we can predict how wet a field will be.

4. Mobile monitoring: Develop apps that allow trainers, jockeys, and punters to receive real-time updates on ground conditions, including visual heat maps showing variations across the course.

5. Biomechanical integration: Correlate going measurements with actual biomechanical data from horses. Stride length, ground reaction forces, and hoof penetration depth would provide direct evidence of how horses interact with different ground conditions.

6. Weather integration systems: Automatically update going predictions based on hyperlocal weather forecasts and real-time rainfall data. "Based on current rainfall patterns, we predict the going will change from Good to Soft by 3:30 pm" would be transformative for race-day decision-making.

Implementation: Making Change Happen

Short-term Actions: Transparency and Consistency

1. Publish all raw Going Stick readings and measurement locations. Yes, this means admitting when you've only taken readings from the driest parts of the course.

2. Take measurements immediately before racing and between races. This revolutionary concept would involve telling people what the ground is actually like when horses are about to run on it.

3. Standardise protocols across all racecourses. Clear guidelines should specify sampling locations, measurement techniques, and reporting standards.

4. Create a centralized database of going measurements, accessible to all stakeholders. Transparency builds trust, and trust is the foundation of racing's integrity.

5. Introduce independent verification of going reports. This could be managed by the BHA or an independent body to ensure consistency and accuracy.

Medium-term Developments: Building a Data Foundation

1. A comprehensive database linking going measurements to race performance. This would allow historical analysis of how accurate going reports have been and how different horses perform under various conditions.

2. Course-specific calibration that acknowledges the unique characteristics of each venue. Uttoxeter in December is not the same as Goodwood in August, despite what the current system might suggest.

3. Integration of going data with existing race analysis platforms. This would allow punters and professionals to see the relationship between ground conditions and performance metrics.

4. Development of going-adjusted performance ratings. These would account for how a horse's ability might vary across different ground conditions based on historical data.

5. Regular auditing and review of going measurement practices. Continuous improvement should be built into the system rather than reactive response to criticism.

Long-term Vision: The Smart Racecourse

1. Real-time going updates accessible via mobile app. Punters could receive notifications: "The going at Newbury has changed from Good to Soft following that downpour during Race 3."

2. Integrated platforms combining going data with weather forecasts and historical performance. Imagine having all this information at your fingertips when making selections.

3. Predictive modelling that forecasts going changes based on weather patterns. "Based on current rainfall and drainage patterns, we predict the going will change to Soft by the feature race at 3:30 pm."

4. Automated measurement systems requiring minimal human intervention. Robotic or drone-based systems could take hundreds of measurements in minutes, creating comprehensive going maps.

5. International standardisation of going measurements. This would allow meaningful comparisons between performances at Ascot and Flemington, enhancing global racing.

6. Integration with training systems to match horse preparation precisely to expected race conditions. The sophistication of training could finally match the sophistication of going measurement.

The Economics of Improvement: Why Change Makes Financial Sense

Implementing these changes would require investment, but the return would be substantial:

1. Increased field sizes: More accurate going reports would give trainers greater confidence in entering their horses, potentially increasing average field sizes by 10-15% according to industry analysis.

2. Enhanced betting turnover: Better information leads to more confident betting. Conservative estimates suggest a 5-7% increase in betting turnover from improved ground condition reporting.

3. Reduced wastage: Fewer horses would run on unsuitable ground, potentially reducing injury rates by 12-18% according to veterinary studies. The welfare and economic benefits are substantial.

4. International competitiveness: As a global leader in racing, the UK has an opportunity to set the standard for going measurement, enhancing its reputation and potentially increasing international participation.

5. Technology transfer: Innovations in going measurement could have applications in agriculture, sports turf management, and environmental monitoring, creating additional revenue streams.

BHA Enforcement: Putting Teeth in the Rules

For meaningful change to occur, the BHA must develop an enforcement framework with genuine consequences:

1. Financial penalties: Implement a graduated system of fines for racecourses found to have significantly misreported going. These penalties should be substantial enough to incentivise accuracy over commercial considerations.

2. Going accuracy ratings: Publish league tables of racecourses ranked by the accuracy of their going reports when compared to objective measures like race times and sectional data.

3. Licensing requirements: Make accurate going reporting a condition of racecourse licensing, with persistent offenders facing licence review.

4. Independent oversight: Establish an independent panel of experts to review going reports and provide oversight of measurement practices.

5. Mandated standardisation: Enforce a single, standardised reporting format that all racecourses must use, eliminating the current hodgepodge of inconsistent approaches.

6. Automatic review triggers: Implement automatic investigations when race times deviate significantly from what would be expected based on the reported going.

7. Whistleblower protection: Create secure channels for industry participants to report suspected going misreporting without fear of reprisal.

Conclusion: A Call for Revolution (or at Least Evolution)

The current system for measuring and reporting going is like trying to perform delicate surgery while wearing oven mitts—technically possible but needlessly difficult and prone to error.

In an era where we can measure the chemical composition of distant planets, track individual honeybees across vast landscapes, and monitor the minute-by-minute glucose levels in diabetic patients, surely we can develop more sophisticated methods for determining whether a racecourse is a bit on the soft side.

Accurate going information would transform decision-making, potentially saving millions in misplaced entries and protecting horse welfare. Standardised, precise measurements would open new frontiers in performance prediction and understanding how different horses handle various conditions. For the everyday punter trying to solve the impossible puzzle of picking winners, it might just mean the difference between backing a horse suited to the actual conditions rather than the imaginary ones described in the racing post.

After all, in a sport where margins of victory are measured in fractions of a second, shouldn't we be measuring the surface they run on with at least the same precision we use to monitor our morning coffee temperature?

The technology exists. The need is clear. The economic benefits are substantial. The only question is whether the racing industry can overcome its historical inertia and embrace the muddy, data-driven future.

As the old racing adage goes, "Horses for courses." Perhaps it's time we knew exactly what those courses were really like.