The Double Helix
Skill-Metabolic Coupling and the Periodisation Problem in Cyclical Sport
The Ecological Dynamics Project
Ecological dynamics offers a fundamentally different account of how skilled movement develops. Traditional coaching treats technique as a template to be installed through instruction and repetition. Ecological dynamics treats coordination as emergent, arising from the interaction between performer, task, and environmental constraints rather than being prescribed by a coach.
This framework has been developed primarily in open play sports (football, basketball, rugby union) where the skill problem is perceptual-cognitive: reading play, anticipating opponents, selecting actions. In these contexts, physiological capability matters but operates somewhat independently from skill. A midfielder’s decision-making doesn’t fundamentally change shape based on fatigue; you can meaningfully separate “tactical training” from “conditioning.” In cyclical sports, skill and metabolic capacity are tightly coupled. The coordination solution is shaped by physiological state. This problem is where ecological dynamics can be extended.
Theoretical Foundations
The framework draws on three intellectual traditions.
Bernstein (1967) identified that the motor system has far more controllable degrees of freedom than can be consciously managed. A single arm movement involves coordinating dozens of muscles across multiple joints, each with its own range of motion, and explicit control of each dimension is computationally intractable. Bernstein’s solution is that coordination emerges through self-organisation, with the system coupling degrees of freedom in order to solve movement problems.
Gibson (1979) argued that perception is not passive reception followed by cognitive processing. Athletes perceive affordances directly from the environment. Perception and action are coupled in a continuous loop rather than operating as separate stages. The implication is that skill is not “knowing what to do” then “doing it,” but a unified perception-action system that detects and exploits affordances in real time.
Gibson arrived at this position by rejecting the dominant information-processing model, where sensory data enters through the eyes, gets transformed through successive stages of neural computation, and eventually produces a mental representation that guides action. Gibson observed that this model creates an explanatory gap: who or what reads the final representation? The problem is infinite regress. If a mental representation requires an interpreter, that interpreter needs its own representations, which need their own interpreter, and so on. This is the homunculus problem.
He proposed instead that the perceptual system evolved to detect invariants in the environment. Stable patterns in the optic flow directly specify relevant properties of the world. An affordance is what the environment offers the organism: a surface affords walking, a gap affords jumping, a ball affords catching. Instead of being computed from raw data, opportunities for action are perceived immediately because the perceptual system is attuned to them.
Affordance perception appears (according to subsequent neuroscience research) to involve distributed networks linking visual cortex, parietal regions (which integrate spatial and body-related information), and premotor areas (which prepare actions). Crucially, there is no central “perceiver” that reads a final representation. The perception-action system is coupled, in the sense that neural activity in motor planning regions occurs during observation of action-relevant objects, even without intention to act. The system perceives in terms of action possibilities.
The mathematical framework underpinning the theory is provided by dynamical systems. Movement systems are modelled as evolving through a state space, settling into stable regions (attractors) and transitioning between them when control parameters cross critical thresholds. Coordination patterns are not prescribed but emerge from the interaction of constraints. Small parameter changes can produce sudden reorganisation, and the system’s trajectory depends on its history. Because of this, behaviour is nonlinear. This means that movement solutions cannot be installed directly; they must be attracted through constraint manipulation.
If coordination emerges from constraint interaction rather than explicit control, then the coach’s job is to manipulate constraints rather than prescribe technique. Newell (1986) identified three constraint categories: organismic (the performer’s physical and psychological characteristics), environmental (the physical and social context), and task (the goals, rules, and equipment that define the activity). Task constraints are most directly manipulable. By changing the target, the equipment, the rules, coaches can design practice environments where movement solutions are attracted, not instructed.
The Critique of Traditional Coaching
Ecological dynamics proponents identify specific problems with traditional skill coaching as part of their offering.
Decontextualised practice separates skill execution from the perceptual environment. Drilling a pass without defenders, practicing a shot without game pressure, rehearsing technique without the informational context that would guide it in competition. This disrupts perception-action coupling, which ecological dynamics considers the fundamental unit of skilled behaviour. Athletes need to learn to detect the affordances that specify when and how to act in order for developed skills to transfer.
Linear progression assumptions contradict evidence that athletes show highly variable learning rates and trajectories. The expectation that athletes move predictably through stages doesn’t match the nonlinear, often discontinuous nature of actual skill development.
Prescriptive technique models fail to develop what researchers call “degeneracy”, or the ability to achieve the same goal through structurally varying motor solutions. An athlete trained to execute one “correct” technique lacks the adaptive flexibility to solve the coordination problem when constraints change. A corollary of the idea that tasks are coupled to environment is that athletes need a repertoire of functional solutions to deploy across circumstances.
John Kiely’s foundational critique (Sports Medicine, 2018) extends beyond skill coaching to periodisation itself. He challenges the field’s reliance on Hans Selye’s General Adaptation Syndrome, arguing that modern allostasis theory demonstrates adaptation is modulated by psycho-emotional factors, context, and individual history, not merely biological responses to physical stress. “There seems no optimised pre-determinable planning path. There is only the informed exploration of a dynamically changing landscape.”
The Research Base
The approach has generated substantial research, primarily in invasion sports like football, basketball, and rugby. Empirical comparisons between linear and nonlinear pedagogical approaches show mixed but generally favourable results for ecological methods. A systematic review of team-invasion sports found nonlinear approaches produce greater effects for tactical skills, with stronger transfer to game performance.
A practical implementation challenge persists. There is “little guidance to help ecological designers decide what type of constraint to design-in, how long to leave a constraint in for, and when to manipulate, change or add-in extra constraints.” Practitioners are largely encouraged to develop expertise through “exploratory trial-and-error learning”, a recommendation that critics note lacks the research-informed specificity coaches need.
The Periodisation Question
Traditional periodisation was developed primarily for physiological adaptation. Matveyev’s foundational work, Bompa’s block periodisation, Issurin’s conjugate sequencing are frameworks that tell you how to sequence volume and intensity to develop strength, power, and endurance. They say relatively little about skill development, implicitly treating technique as something maintained or refined alongside the “real” work of conditioning.
Ecological dynamics demanded a different question: if coordination emerges from constraint interaction rather than being installed through instruction, how should skill training be structured across a season? It’s not clear if a macrocycle is necessary, if the training target is perceptual-motor development rather than physiological adaptation.
Two frameworks now explicitly address this: the Skill Acquisition Periodisation (SAP) framework and the Periodization of Skill Training (PoST) framework. These represent the field’s attempt to provide structured planning tools while preserving ecological principles.
SAP (Farrow & Robertson, 2017) reconceptualises traditional periodisation principles for skill contexts:
- Specificity becomes maintaining perception-action coupling and representativeness
- Progression becomes managing information complexity through constraint manipulation
- Overload becomes increasing cognitive effort through variability and interference
- Reversibility addresses skill retention and transfer between contexts
The framework preserves periodisation vocabulary while changing what the terms refer to. The coach or planner is periodising constraint configurations and information load.
PoST (Otte, Millar & Klatt, 2019) provides more operational detail. Built on Newell’s model of motor learning (itself derived from Bernstein’s degrees of freedom problem), PoST proposes three training stages:
Coordination Training is the initial stage: low environmental variability and task complexity. Athletes typically “freeze” degrees of freedom to simplify the coordination problem. The framework emphasises task simplification (reducing complexity while maintaining perception-action coupling) rather than task decomposition (breaking skills into isolated parts). Progression is based on observed movement consistency, not predetermined timelines.
Skill Adaptability Training comprises three nested sub-stages. Movement Variability Training involves 1-2 athletes working on within-skill variability with modified equipment. Complex Training expands to 3-4 athletes practicing between-skill variability across multiple tasks. Team-based Training introduces phase-of-play situations and small-sided games with maximum representativeness. The progression systematically increases “information complexity”, or the perceptual-cognitive challenge of the learning environment.
Performance Training shifts toward competition preparation, where skill development may no longer be the primary objective. The framework explicitly acknowledges this stage may re-emphasise movement stability for confidence.
What distinguishes PoST from traditional periodisation is its accommodation of non-linear progression. The authors state that “movement back and forth between skill training stages should be considered” as normal development, not regression. This is a genuine departure from linear models.
The framework offers concrete planning tools: macro-cycle calendars, weekly micro-cycle templates, and single-session planning forms with fields for constraint manipulation. A published case study applied the framework to professional goalkeeper training over a 2018/2019 season, revealing that typical GK coaches spent only around 30% of training time in complex, representative activities, with 50-70% devoted to isolated technical work that fails to maintain perception-action coupling. The framework provides structure for shifting that balance.
What Gets Periodised
The key insight from both frameworks: the debate isn’t whether to plan skill training, but what should be periodised. The answer is constraints and learning environments, not prescribed techniques. The coach plans sequences of practice configurations characterised by different constraint setups. The athlete’s movement solutions within those environments remain emergent.
This preserves self-organisation at the movement execution level while providing structure at the practice design level, an elegant resolution that works well for contexts where skill and conditioning are loosely coupled.
Theoretical Tensions
The field hasn’t reached complete consensus. Collins et al. (2024) note that “whether reading one article or several from an ecological dynamics perspective, the narrative to date has been inconsistent, confusing and contradictory”, with some papers dismissing mental representations entirely while others acknowledge intentions and attention as meaningful factors. The relationship between emergence and planning, between self-organisation and coaching intervention, remains actively debated.
But the direction of travel is clear: periodise constraints, not techniques; expect nonlinear progression; respond to observed athlete behaviour rather than following predetermined timelines.
Extending to Different Contexts
Both PoST and SAP were developed in open-skill, invasion sport contexts. Football. Basketball. Team games where the skill problem is primarily perceptual-cognitive: reading play, anticipating opponents, selecting from a repertoire of actions. The metabolic demands exist but operate somewhat independently. A midfielder’s decision-making quality doesn’t fundamentally change shape based on whether they’re at minute 20 or minute 80. Fatigue degrades performance, but the perceptual-cognitive apparatus remains structurally similar.
This creates a loose coupling between skill and metabolic capacity. You can meaningfully separate “tactical training” from “conditioning.” The skill development question (how do I improve decision-making under pressure?) and the physiological question (how do I build the aerobic base to sustain 90 minutes?) are related but distinguishable problems with distinguishable solutions.
The PoST framework’s structure reflects this context. When it describes Performance Training as a phase where “skill development may no longer be the primary objective,” it’s treating skill as something that can be deprioritised while you attend to other concerns. The framework periodises information complexity because that’s where the perceptual-cognitive problem lives in invasion sports.
Cyclical sports present a different constraint landscape. In rowing, kayaking, running, cycling, and swimming, performance is a skill acquisition task with high metabolic demand. What does the evidence show about skill and metabolic capacity in these contexts?
Skill and Metabolic Capacity in Cyclical Sports
1. Fatigue systematically reshapes coordination, not just performance
The movement pattern that solves the coordination problem when fresh is not the same pattern that solves it when fatigued. This isn’t degradation—it’s a different problem requiring a different solution.
Meta-analytic evidence from running documents consistent kinematic changes as metabolic fatigue accumulates: contact time increases, cadence decreases, knee flexion at initial contact increases, vertical stiffness decreases (Apte et al., 2021). But the key finding is that athletes continuously recalibrate. Hunter and Smith (2007) found that during a 1-hour high-intensity run, runners’ preferred stride frequency tracked their energetically optimal frequency throughout, declining from 1.45 to 1.43 Hz as oxygen uptake rose.
A similar pattern is found in swimming. Stroke frequency initially increases to compensate for declining stroke length, until a mechanical failure threshold is reached, after which both decline together (Puce et al., 2023).
The neuromuscular system is actively re-solving the coordination problem as metabolic constraints shift, emphasising how the metabolic constraints of a task require different movement solutions.
2. Economy cannot be partitioned into technique versus physiology
Biomechanics alone explains only 4–12% of between-individual variation in running economy (Van Hooren et al., 2024). Physiology alone fares no better. Economy varies by up to 30% among trained runners with similar VO2max values. The gap is substantial, enough to determine race outcomes more than maximal oxygen uptake.
Training studies deepen the puzzle. Motor learning can improve economy without detectable physiological change. Moore, Jones, and Dixon (2012) found beginner runners became 8.4% more economical over 10 weeks while VO2max remained stable. Conversely, strength training improves economy through enhanced musculotendinous stiffness without observable technique modifications (Blagrove et al., 2018). Economy improves through both pathways, but neither is visible in the measures we’d expect.
Paula Radcliffe’s career illustrates the impossibility of clean separation. Over 15 years, her running economy improved 15% (from 205 to 175 mL·kg⁻¹·km⁻¹ at 16 km/h) while her VO2max remained stable at ~70 mL·kg⁻¹·min⁻¹. Her physiologist Andrew Jones acknowledged he cannot identify which single factor drove this improvement.
The question itself may be malformed. The improvement wasn’t in “technique” or “physiology” but in the coupled system that produces economical running.
3. Metabolic capacity is bound to coordination context
Capacity measured through one movement pattern doesn’t fully transfer to another. VO2max tested on a treadmill versus a cycle ergometer differs depending on training history. Untrained subjects show 10–22% higher VO2max running than cycling. But trained cyclists achieve similar or higher values on the bike than the treadmill (Basset & Boulay, 2000).
The pattern is consistent. Runners showed 10.5% higher VO2max on treadmill versus cycle, triathletes 6.1% higher, cyclists only 2.8% different. Economy shows even stronger specificity. Runners had 21% better running economy than cyclists, yet cycling economy showed no difference between groups.
The mechanism is peripheral adaptation. Saltin’s one-leg training studies demonstrated 20–30% increased capillarisation and 20–40% increased oxidative enzyme activity in trained legs, while untrained legs showed no peripheral adaptations despite central cardiovascular improvements. As Hughes et al. (2018) summarised: “the vast majority of training-induced adaptations occur only in those muscle fibres that have been recruited during the exercise regimen.”
For competitive athletes, peripheral adaptations become the limiting factor. Metabolic capacity is developed and expressed within particular coordination contexts, and the coordination solution chosen determines which fibres are recruited.
4. Pacing develops through metabolic experience, not cognitive instruction
Pacing is a self-regulatory skill that develops over years and cannot change easily (Menting et al., 2022). Good pacing strategies are maintained and inappropriate ones discarded through experience. These are the same processes that generally govern skill acquisition.
Developmental studies reveal a clear trajectory. Children ages 5–8 show “positive pacing” (continuous slowdown), indicating inability to anticipate metabolic demands. By age 10, U-shaped velocity distributions emerge. Major shifts toward adult-like pacing appear around ages 15–16. Lambrick et al. (2013) demonstrated that inexperienced children required repeated metabolic exposure to develop appropriate 800m pacing, improving from 250.1 to 242.4 seconds across three trials.
Pacing depends on physiological feedback. Amann’s studies blocked Group III/IV muscle afferent feedback via fentanyl during 5km cycling time trials. Athletes overestimated their capacity, chose excessive power outputs, and experienced “severe ambulatory problems on completion.” The afferent blockade released what Amann described as a “centrally mediated brake on central motor drive.” Pacing cannot be purely cognitive.
Pacing also breaks down in novel metabolic conditions. Racinais et al. (2015) found cyclists completing their first heat-exposed time trial took 77 ± 6 minutes versus 66 ± 3 minutes in cool conditions, despite initiating the first 20% at similar power output. After 14 days of heat acclimatisation, performance returned to 66 ± 4 minutes. Without metabolic reference points for heat stress, they could not pace appropriately.
This is different from invasion sport skills, where perceptual-cognitive patterns can be trained through video, small-sided games, and varied practice. Pacing requires the physiology to be present.
5. Elite-novice differences emerge under metabolic load
Maas et al. (2018) compared 15 novice runners (<10 km/week) with 15 competitive long-distance runners during treadmill runs to exhaustion. While both groups showed increased pelvic tilt and rotation, only novices displayed significant increases in forward trunk lean (a change associated with injury risk and reduced efficiency).
Mo and Chow (2018) found experienced runners displayed more coordination variability (flexibility in inter-joint couplings) while maintaining less outcome variability than novices. A larger repertoire of motor solutions enables adaptive responses to fatigue while preserving performance stability.
Elite and novice performers have different coordination solutions, and the difference becomes most pronounced under metabolic stress. This appears to be a distinguishing factor in cyclical sports.
The Double Helix Thesis
The evidence points to manifestations of the same underlying phenomenon. Fatigue reshapes coordination rather than simply degrading it. Economy cannot be partitioned into technique versus physiology. Pacing requires metabolic experience to develop. Capacity is bound to coordination context. Elite-novice differences emerge under metabolic load. The expression of metabolic capacity requires motor coordination, and vice versa.
We call this the Double Helix thesis. Metabolic capacity and coordination skill are not loosely coupled variables that occasionally interact. They are better understood as complementary strands where information is encoded in the relationship between them rather than in either strand alone.
DNA’s two strands are chemically distinct but structurally inseparable. Each strand defines the shape of the other through base pairing. The genetic information emerges from their complementary relationship, rather than being stored in either strand alone. Similarly, the coordination solution is shaped by the metabolic context in which it operates, and metabolic capacity is only ever expressed through a coordination solution.
This mirrors a statistical reality explored in my previous post on periodisation modelling: Hellard et al. found that the fitness and fatigue time constants in the FFM correlate at r = 0.99. These parameters cannot be independently identified from performance data. The Double Helix thesis suggests this is a reflection of how these systems actually work.
Extending Ecological Dynamics to Cyclical Sports
The Double Helix thesis seeks to extend the core concepts of ecological dynamics to a domain the existing frameworks haven’t yet adequately addressed.
Principles That Transfer
Periodise constraints, not techniques. The coach’s job is to configure constraints that allow functional coordination solutions to emerge. In cyclical sports, the relevant constraints include pace targets, segment focus, entry state (the metabolic and kinematic context the athlete enters the effort from), duration and rest, and equipment and environment. The constraints define the coordination problem so that the solution can be found by the athlete.
Responsive over predetermined planning. Progression should be guided by observed athlete response: movement consistency, output relative to expectation, signs of coordination breakdown or consolidation. Calendar-based phase transitions make little sense when athlete trajectories are highly variable. Observe how the joint product is evolving and adjust constraints accordingly.
Non-linear progression as normal. An athlete might return to earlier segment work after a block focused on a different segment, because the changed metabolic profile creates new coordination problems in previously-trained segments. Skill and metabolic development must constantly track a moving target.
The coach as constraint manipulator. The coach cannot directly install a coordination solution or manipulate metabolic pathways. They can only configure constraints and let the system self-organise in response. Understanding what’s happening inside provides hypotheses and guides constraint selection, but it removes dependence on mechanistic knowledge to act.
What Changes for Cyclical Sports
Block logic reconsidered. Traditional periodisation prioritises the development of physiology (you can build the aerobic base first, add glycolytic capacity, then sharpen for racing). But the coupling thesis implies you cannot develop aerobic capacity separately from the coordination pattern you’ll use to express it. An “aerobic base block” consisting entirely of steady-state work develops a coordination solution for steady-state movement. Not only will this not transfer to race-pace coordination, it may degrade the race-pace movement solution.
This suggests block boundaries must blur. Some race-pace or segment-specific work is needed even in phases emphasising development of other characteristics, because the coordination solution must be practiced at the intensity where it will be expressed. The sequencing question changes from “when do I develop each energy system” to “how do I configure constraints so the coordination-metabolic pairing develops together.”
Blocks might still have coherence as periods of shifting emphasis but not as discrete phases where physiology is developed first and skill treated as independent.
Race segments as periodisation targets. PoST periodises “information complexity”, or the perceptual-cognitive challenge of the learning environment. For cyclical sports, the Double Helix framework proposes periodising by race segment. A race has metabolically grounded phase transitions that create distinct challenges, with trainable coordination solutions.
Start segments (for shorter races) present a coordination problem of aggressive force application with high accuracy. Finishing segments require maintaining functional output as degrees of freedom collapse under severe metabolic constraint. Longer events involve reading internal state against external progress.
The co-evolution problem. Skill adaptation occurs faster than physiological adaptation. As the metabolic profile shifts across a block, the coordination solution that was optimal last week may no longer be optimal. Physiological adaptations have timescales of weeks; coordination can update within days.
During a phase of training, the metabolic substrate shifts continuously. The coordination solution must repeatedly re-adapt to exploit the expanding capacity; it is never “solved” because the substrate keeps changing.
Open Questions
The framework provides conceptual structure but not validated protocols.
Segment targeting. How do we determine which race segments act as the target for a given phase of training?
Diagnostic development. What triangulation of measures identifies limiters across segment types and phases?
Coordination stability. What markers indicate the coordination solution needs updating versus being appropriately stable?
Physiological considerations. How do we address the physiological demands that underpin typical periodisation models—recovery, fatigue management, taper—within a framework that denies clean separation?
Transfer and integration. Does segment-specific training transfer to integrated race performance, or does the integration itself require practice?
Measurement. If skill and metabolic capacity can’t be separately assessed, what should we actually measure?
Conclusion
Ecological dynamics has transformed skill periodisation: periodise constraints rather than techniques, expect non-linear progression, respond to athlete observations rather than calendar phases. But these frameworks were built for invasion sports where skill and metabolic capacity are loosely coupled.
The Double Helix framework proposes extending ecological dynamics to cyclical sports, where the coupling is tight. It preserves constraint manipulation as the coaching method and responsive planning as the macro-structure. It proposes that race segments provide actionable periodisation targets, and that the co-evolution of skill and metabolism is the central problem rather than a complication.
Much of this remains hypothetical. What the framework offers is a conceptual structure that may actually match the problem: cyclical sport performance is a joint product of coordination and metabolic capacity, and training is the configuration of constraints under which that joint product co-evolves.
Torri Callan is a data scientist with a PhD in statistics and a background in elite sport. Read more about the author.
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