Developing Custom Horse Racing Figures and Market Narratives for Betting Edge

This conversation with professional horseplayer Sean Boarman offers a rare glimpse into the disciplined, often counter-intuitive world of high-stakes wagering. Beyond the immediate thrill of picking winners, Boarman reveals a strategic approach that prioritizes process, consequence analysis, and a willingness to embrace discomfort for long-term gain. The non-obvious implication? That true advantage in betting, much like in business, is forged not by chasing obvious trends or quick wins, but by deeply understanding the underlying systems and resisting the siren song of conventional wisdom. Those who can master this mindset--identifying false narratives, understanding delayed payoffs, and committing to rigorous analysis--will find themselves with a significant edge. This discussion is essential for serious handicappers, bettors, and anyone looking to apply a more strategic, systems-level thinking to their own competitive endeavors.

The Unseen Currents: Navigating the Systemic Dynamics of Horse Racing Wagers

Sean Boarman, in his "Pro Player Diary," doesn't just discuss betting; he dissects the very fabric of how professional handicapping operates. His insights peel back the layers of surface-level analysis to expose the deeper, often hidden, systemic forces at play. This isn't about gut feelings or chasing hot streaks; it's about a deliberate, often arduous, process of understanding how different elements interact over time, creating opportunities for those willing to look beyond the immediate.

One of the most compelling threads is Boarman's approach to data and figure-making. He dismisses readily available commercial data like Timeform US's late pace ratings as insufficient, not because they are inherently bad, but because they lack the granular detail and contextual understanding required for true edge.

"I don't think their late pace stuff is very good. I don't use the product all that much anymore, but from what I remember, they don't really give you a late pace figure for every race."

This highlights a critical systems-level insight: readily accessible data often represents a commoditized edge, meaning many players have it, thus diminishing its value. The true advantage lies in creating or deeply understanding data that others overlook or cannot easily access. Boarman's preference for Bris, or even the manual process of figure-making, points to a recognition that the effort and insight embedded in data creation are where the real value resides. This is a delayed payoff; the time spent building or intimately understanding figures doesn't yield immediate wins but builds a more robust predictive model over the long haul. Conventional wisdom might suggest using the most popular tools, but Boarman shows how extending that forward reveals its limitations.

His discussion on trip notes and race review further illustrates this. The idea that the process of analyzing races, rather than just the final figures, is more valuable, is a profound systems-thinking concept. It’s not just about the outcome of a single race, but about understanding the intricate dance of jockeys, trainers, track conditions, and pace dynamics. This deep dive creates a feedback loop: understanding these nuances improves future handicapping, which in turn refines the analysis, creating a virtuous cycle.

"What I realized going through the process was what I liked about it as much as anything, as much as valuable, if not more valuable than the figure, were the other things you noticed just by being so into the racing that I was making figures. Like the process was worth more than..."

This is where Boarman demonstrates a keen understanding of competitive advantage. While others might be satisfied with surface-level data or quick analyses, Boarman emphasizes the value of the painstaking process of reviewing races, understanding jockey tendencies, and recognizing trainer patterns. This requires significant time investment--a clear example of immediate discomfort (hours spent reviewing replays) yielding a lasting advantage (deeper, more accurate handicapping). The system responds to this meticulousness by revealing subtle clues that are missed by those who only skim the surface.

Boarman also touches on the allure and danger of narratives in betting. He points out how quickly public perception of quarterbacks like Matthew Stafford can shift, driven by recent results rather than a consistent understanding of performance.

"It's silly. The brain wants to find patterns even when there are none. And in this day and age where everybody has their own, you know, ability to get their opinion out there, you just hear a lot more nonsense."

This is a direct application of systems thinking: recognizing how external narratives--often driven by media or short-term results--can distort the underlying reality of performance. The successful player, Boarman suggests, must actively fight these narratives, looking for the "false narratives" to exploit. This requires a disciplined detachment from popular opinion, a willingness to be unpopular in one's picks, and a commitment to the data and process over the prevailing story. The advantage here comes from betting against the crowd, a strategy that often involves immediate social discomfort but can lead to significant financial rewards.

His reflections on his own career arc--leaving the structured environment of Keeneland to go solo, then returning--also speak to systemic pressures. Boarman recognized that Keeneland's evolving priorities might limit his ability to access the data and resources he needed for his handicapping process. This foresight, a recognition of how organizational shifts impact individual workflows, led him to make a difficult decision to strike out on his own, ensuring he could continue his work "the way I knew it had to be done." This proactive adaptation to systemic changes, even when it meant leaving a comfortable position, is key to long-term sustainability.

The Hidden Cost of "Easy" Data

The readily available, commercially packaged data sets--like Timeform US's late pace ratings--represent a seductive shortcut. They offer an immediate solution to a complex problem: understanding a horse's finishing speed. However, Boarman's critique highlights a critical downstream effect: these generalized figures often lack the nuance to account for race-specific variables. A rating, divorced from the context of the specific race dynamics (early pace, track condition, jockey tactics), can be misleading. The immediate benefit of having a number is overshadowed by the hidden cost of its potential inaccuracy, leading to suboptimal betting decisions.

The Process as the Ultimate Edge

Boarman's emphasis on the value of the process--figure-making, trip notes, race review--is a powerful illustration of how delayed payoffs create a competitive moat. The hours spent meticulously analyzing past performances, understanding subtle jockey maneuvers, or developing proprietary figures are not immediately rewarded with wins. Instead, this effort builds a deeper, more intuitive understanding of the sport. This foundation allows for more accurate predictions over time, especially in situations where conventional handicapping methods fail. The advantage is not in finding a magic formula, but in the cumulative effect of rigorous, sustained analysis.

"What I realized going through the process was what I liked about it as much as anything, as much as valuable, if not more valuable than the figure, were the other things you noticed just by being so into the racing that I was making figures. Like the process was worth more than..."

Narrative Bias: The Siren Song of Story

The tendency to bet based on compelling narratives--like a quarterback's perceived "clutch" status or a horse's "comeback story"--is a cognitive trap. Boarman identifies this as a significant pitfall, noting how quickly narratives can distort objective assessment. The immediate appeal of a story can override a sober analysis of data and past performance. The consequence of succumbing to narrative bias is betting on horses or outcomes that are overvalued by the public, leading to poor expected value. The true advantage lies in identifying and betting against these narratives, which requires a disciplined commitment to objective analysis, even when it means going against popular opinion.

Key Action Items

• Develop Proprietary Data Metrics: Invest time in creating or refining your own analytical tools, such as late pace figures or trip analysis metrics, rather than relying solely on commercially available data. (Immediate Action, Pays off in 6-12 months)
• Prioritize Rigorous Race Review: Dedicate specific time slots for in-depth review of past races, focusing on trip notes, jockey tendencies, and trainer patterns, not just the final results. (Immediate Action, Pays off in 3-6 months)
• Actively Identify and Fade False Narratives: Make a conscious effort to recognize popular betting narratives and systematically seek opportunities to bet against them, especially in high-profile events. (Immediate Action, Pays off in 3-6 months)
• Systematically Analyze Data Limitations: Regularly assess the shortcomings of the data sources you use and actively seek ways to compensate for their inherent biases or lack of granularity. (Ongoing, Pays off in 6-18 months)
• Embrace Process Over Immediate Results: Reframe your definition of success to prioritize the quality of your handicapping process, understanding that winning streaks are often a byproduct of consistent, disciplined analysis rather than luck. (Mindset Shift, Ongoing)
• Document and Learn from Every Bet: Beyond just wins and losses, meticulously document the reasoning behind each wager, particularly focusing on how narrative or data biases may have influenced your decision. (Immediate Action, Pays off in 6-12 months)
• Seek Diverse Data Sources for Context: When evaluating races, actively compare and contrast information from multiple sources (e.g., different figure makers, track biases) to build a more holistic understanding. (Immediate Action, Pays off in 3-6 months)