Jake Gillies - Data-Driven Decision Making in Rehab
Jan 20, 2026
Episode 208: In this episode, Andy McDonald is joined by Jake Gillies, Lead Sports Scientist at Bristol Bears Rugby, working at the sharp end of performance data integration within English Premiership rugby.
Jake’s role centres on quantifying the physical demands of match play and translating performance technology outputs into actionable training decisions. Prior to joining the Bears, he worked as a Sports Scientist at Harlequins Rugby, alongside experience as a Strength & Conditioning coach in the British Basketball League (BBL) — giving him a broad, cross-sport perspective on how data should (and shouldn’t) be used.
Across the conversation, Jake breaks down what it really means to turn data into action. He explores how practitioners can move beyond numbers for numbers’ sake, contextualise information within rehab and performance environments, and ensure that data serves decision-making rather than complicating it. The discussion highlights the importance of athlete intent, flexible testing frameworks, and clear visualisation when bridging the gap between rehabilitation and match performance.
Topics Discussed:
• Turning data into action
• Contextualising data in rehabilitation
• Managing complexity in rehab objectives
• Insights vs. information in sports science
• The importance of good data in rehab settings
• Athlete intent & performance metrics
• Flexibility in testing protocols
• Effective data visualisation & dashboards
• Bridging the gap between rehab and match performance
Key Points
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The Shift from Descriptive to Insight-Driven Science: Sports science has transitioned from a purely descriptive role to an insight-driven performance tool that focuses on unlocking specific physiological adaptations rather than just monitoring fatigue. Modern practitioners must move beyond "data dumping" into spreadsheets and instead focus on creating actionable insights that drive program development for young athletes while retaining capabilities in veteran players. This evolution involves shifting away from a reductionist mindset where practitioners simply look to reduce training loads based on "red flags" on an iPad, moving toward a more holistic science of adaptation that prioritizes physical preparation over mere load management.
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The Hierarchical Model of Data Actionability: The process of turning raw numbers into clinical action involves a hierarchical four-step model: data, information, insight, and action. Raw data points, such as individual velocity band distances from GPS, are first summarized into information, like total high-speed running volume. However, information without context is merely a snapshot in time; true insight only occurs when that data is married with the specific context of the training drill, such as whether a player’s running was anticipated or a response to an external stimulus. Only once this insight is established can a practitioner take a meaningful, evidence-based action in the training environment.
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Moving Beyond Simple Pass-Fail RTP Metrics: In the return-to-play (RTP) process, utilizing simple pass-fail markers, such as reaching 90% of maximum velocity, can be dangerous if the practitioner fails to consider the "stylistic execution" of the movement. While hitting a speed target is a necessary precursor, the rehab must eventually account for the density and intensity of the efforts to match the specific positional demands of the sport. Relying solely on a single number without understanding how that volume was achieved—such as the number of entries into high-speed zones or the acceleration profiles—can lead to re-injury once the player returns to the chaotic environment of full-intensity training.
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Foundational Importance of Data Hygiene: Data quality is fundamentally dependent on strict testing protocols and the environmental conditions present during collection. Good data starts before the technology is even switched on, requiring valid and reliable tools and a standardized environment to minimize error rates. For example, GPS accuracy can be significantly compromised by stadium roof overhangs or high-walled training environments, which lower satellite counts and signal quality. This "environmental noise" can lead to misleading performance reports that do not accurately reflect the athlete's true physical output or physiological strain during a session.
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Standardization in Neuromuscular Testing: Maintaining high levels of "data hygiene" includes ensuring athletes use the same GPS unit every session and that testing protocols are executed by the same practitioner consistently. Minor inconsistencies, such as an athlete wearing different shoes for an isometric test or grabbing a frame for leverage during a shoulder assessment, can completely invalidate the results. If the testing environment is compromised—such as external noise or vibrations during a force plate jump—it is often better to skip the test entirely rather than collect flawed information that could lead to an incorrect clinical intervention.
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Combating Goodhart’s Law in Performance Testing: The "Goodhart’s Law" principle is a common pitfall in high-performance sport, where a measure ceases to be useful once it becomes a target for the athlete to "game." Athletes may manipulate tests, like lifting their knees higher during a counter-movement jump to increase flight time, to artificially meet a return-to-play standard. To combat this, practitioners should look beyond simple outcome markers and investigate deeper metrics, such as eccentric braking impulse or duration, to ensure the underlying movement quality supports the reported number. This ensures the athlete is truly ready rather than just proficient at passing the test.
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Filtering through Information Overkill: Practitioners often face "information overkill," where the abundance of available metrics—such as the hundreds of variables generated by modern force plates—can lead to decision paralysis. The goal of a specialist generalist is to filter through this "muddy middle" to identify the two or three metrics that truly drive meaningful clinical decisions. Chasing too many rungs on the rehab ladder doesn't necessarily extend the timeline, but it does significantly increase the confidence level of the staff when a player finally returns to full competition, ensuring that the metrics chosen are those most sensitive to the specific injury.
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Contextualizing Movement Density and Cognitive Load: Understanding the cognitive and physiological differences between planned and unanticipated movements is critical for late-stage rehab. An athlete may achieve identical physical outputs during a planned rehab run compared to a match, but the match environment imposes a much higher cognitive stimulus and differential RPE (Rate of Perceived Exertion). Insights into how a player is achieving their volume—whether through steady-state running or reactive, high-density efforts—determines if they are truly physiologically prepared for the demands of the head coach’s style of play, which often requires rapid transitions and reactive decision-making.
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Statistical Significance vs. Observational Change: Statistical assessments like the "smallest worthwhile change" (SWC) are more effective than simply observing if one number is larger than another. This approach allows practitioners to determine if a change in a performance marker, such as a Nordic score or a jump height, is statistically significant rather than just a result of standard error or daily fluctuation. Utilizing these statistical filters helps bridge the gap between information and action, ensuring that interventions are based on real physiological shifts and that practitioners don't overreact to "noise" inherent in high-frequency monitoring.
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Interdisciplinary Integration of Sports Science: The role of the sports scientist is increasingly becoming a collaborative one that supports various departments beyond just medical and S&C, including recruitment and performance analysis. By providing a structured process for data analysis, the sports scientist can offer objective insights that help the entire organization move away from opinion-based decision-making. This cross-departmental integration ensures that the "data plus context" philosophy is applied to all areas of athlete management, allowing for better alignment between the medical department's rehab goals and the coaching staff's tactical requirements.
Where you can find Jake:
Sponsors
VALD Performance, makers of the Nordbord, Forceframe, ForeDecks and HumanTrak. VALD Performance systems are built with the high-performance practitioner in mind, translating traditionally lab-based technologies into engaging, quick, easy-to-use tools for daily testing, monitoring and training
Hytro: The world’s leading Blood Flow Restriction (BFR) wearable, designed to accelerate recovery and maximise athletic potential using Hytro BFR for Professional Sport.
Gameplan Performance, Gameplan Performance is a rehab Project Management & Data Analytics Platform that improves operational & communication efficiency during rehab. Gameplan provides a centralised tool for MDT’s to work collaboratively inside a data rich environment.
