A Performance Framework for the 100 m

Context of this Article

This article originated from a university assessment that required critical reflection on how different sport-performance frameworks conceptualise performance.We were asked to compare models featuring the elements Performance, Physical, Technical, and Tactical—each arranged differently—and to justify which best suited our sporting context and why. The task also required labelling and refining these models, proposing additional components where appropriate.

The subject, taught by Dr. Franco Impellizzeri, aims to develop critical thinking skills that allow practitioners or coaches to identify logical fallacies in scientific evidence and evaluate its real-world implications for high-performance sport. It has been an exceptional subject, and learning from Franco has been a privilege.

As a sprint coach, this exercise echoed the same questions I pose in the mentorship program I ran last year. In that mentorship, I asked coaches to first define their philosophy - a confronting task that requires clarity about their understanding of the sport, their framework for athlete preparation, and their ability to evaluate the current state of the athletes they work with.Once a philosophy was articulated, coaches were then asked to construct a system - one that aligns philosophy with the pragmatic realities of sport: competition schedules, facility access, budgets, and available training time. A performance framework sits beneath both philosophy and system. It is a simple, interpretive tool that helps coaches and athletes understand results and identify where improvements in performance may be found.

The Value of Performance Frameworks

Performance frameworks:

• Organise complexity – Performance is multifactorial; frameworks simplify it into digestible domains.

• Guide decision-making – They clarify what matters most, and in what order.

• Provide shared language – They align coaches, athletes, and support staff around a common understanding.

• Support measurement and evaluation – They translate abstract ideas into measurable components.

• Bridge theory and practice – They make thinking visible, testable, and open to refinement.

In short, frameworks are not truths; they are guiding heuristics that help us reason more effectively about sport.

My Framework: The Causal Chain Model

Among the models proposed, I gravitated toward one that positioned the components linearly. I labelled it the Causal Chain Model, as it offered the clearest logic for a closed-skill event like the 100 m sprint. My interpretation is that each component exerts a causal influence on the next, reflecting how performance unfolds in practice. This aligns with my philosophy and the systems I use to prepare athletes for the 100 m.

Sequence: Physical → Technical → Tactical → Performance

• Physical capacities set the ceiling for what is technically possible.

• Technical potential emerges from those physical capacities.

• Tactical choices (the race model) arise from the available technical model.

• Performance is the outcome of executing that model under competition conditions.

This hierarchy fits sprinting because biomechanics and physiology constrain technique, which in turn shapes tactical expression. It provides a logical order for programming and analysis—develop physical capacity first, refine technical execution, then polish tactical decision-making.

Operational Definitions

Each determinant of performance was defined and, where possible, linked to measurable proxies.

Physical Subcategories

• Anthropometry & body composition – DEXA, limb ratios.

• Strength & power – IMTP, CMJ, RSI, Nordic, groin squeeze.

• Speed capacities – 0–30 m acceleration, flying 10 m max velocity, 60–100 m speed endurance.

• Mobility & coordination – ROM, rhythm, stability screens.

Each measure is a proxy—valuable only when interpreted through the lens of the athlete’s context and the coach’s system.

Expanded Definitions

• Performance: Most often evaluated by race time; however, competition placing may sometimes outweigh time-based outcomes—the classic “world record vs Olympic gold” dilemma.

• Technical: Essentially the athlete’s movement solution for expressing speed.

• Tactical: A race model co-designed by athlete and coach. Evaluation is best framed thematically rather than rigidly strict split-by-split adherence risks penalising athletes for “breaking” a race model during breakthrough performances.

• Physical: This component can become endlessly complex. Coaches must avoid analysis paralysis by identifying which qualities truly underpin sprinting: strength, power, elasticity, flexibility, endurance, body composition, and anthropometry. Testing should remain simple, systematic, and linked to the athlete’s performance expression.

Model Refinements: Mediators and Moderators

While the Causal Chain Model is deliberately simple, two additional realities influence performance:

• Psychology acts as a mediator—it explains how or why physical qualities are expressed technically or tactically.

• Environment acts as a moderator—it alters when or how strongly these relationships hold (e.g., wind, heat, or rounds).

Attempting to operationalise these fully would complicate the model unnecessarily. Recognising them as mediating and moderating influences preserves simplicity while capturing the complexity of real performance.

This perspective reflects my realist–pragmatist lens: physical qualities are real (realism), but our measurements are proxies chosen for their practical usefulness (pragmatism).

Practical Application

The model supports two key coaching processes:

1. Periodisation

GPP → SPP → Competition Phase

Physical work builds the foundation, technical refinement develops efficiency, and tactical sharpness emerges closer to competition.

2. Problem-Solving

When performance stagnates, reverse-engineer:

1. What time do we want to run?

2. What race model aligns with that outcome?

3. What technical model supports that plan?

4. Do the physical qualities exist to express it?

This sequence shifts focus from symptom (e.g., slow max velocity) to cause (e.g., insufficient stiffness, technical breakdown, exposure to high-speed running, etc.).

Limitations and Failure Modes of the Causal Chain Model

• Risk of under-valuing expression (tech/tac):

  
  

  Treating Physical → Technical → Tactical as strictly linear can underplay the need to develop technical skill and race execution. Strong physical qualities won’t convert to speed if they aren’t expressed efficiently.

• Mis-weighting physical qualities:

  The model doesn’t tell you which physical qualities to prioritise. Coaches can over-index maximal strength while neglecting power/RFD, stiffness/reactivity, or max-velocity exposures, creating a strong “ceiling” that isn’t sprint-specific. If we're looking at the physical component as the foundational piece to this framework, you need to ensure your understand of this component is extremely solid.

• Over-simplicity in complex contexts:

  Works best for the 100 m; less explanatory in events/sports where cognition, pacing, and opponent interactions are central (200/400 m, team sports). It can flatten nuance in those settings.

• Insufficient feedback loops:

  The neat left-to-right flow can hide bidirectional effects (e.g., improved technique revealing physical limitations; tactical rehearsal refining technical robustness). Without explicit loops, you might miss iterative adjustments.

• Proxy dependence & measurement error:

  The model stands on proxies (IMTP, CMJ, RSI, splits). Poor test selection, inconsistent protocols, or over-interpreting single metrics can misdiagnose the limiting factor.

• Psychology & environment sidelined:

  Positioning psychology as a mediator and environment as a moderator preserves parsimony but de-emphasises their operational detail. In some athletes/contexts these influences can be decisive.

• Individual variability vs. fixed sequence:

  Some sprinters thrive with atypical sequences (e.g., earlier transition to upright). A rigid chain can bias coaching toward the model rather than the athlete.

• Coach dependency:

  The model’s usefulness hinges on the coach’s ability to synthesise data into action. Without that integration, it becomes a tidy diagram with no practical leverage.

Closing Reflection

The 100 m sprint is a relatively simple, deterministic event. A simple, causal framework best reflects its nature. Adding endless sub-domains or psychometric variables rarely adds clarity; it often creates noise.

The value of any framework lies not in its complexity but in its utility - its ability to guide reasoning, inform practice, and help the coach synthesise multiple dimensions of performance into coherent action.

This is not ‘THE’ performance framework for the 100m – it is just something that I have created as it aligns with my coaching context, philosophy, system and scientific lens. It is a pragmatic, realist, meatheaded view on coaching - which is just the way I like it.

How do you view performance of the 100m sprint?

Thanks for reading.

Jack