Developing Agile Athletes: Applying the Agility Development Framework in Practice

Agility actions—including side-steps, shuffle steps, crossover cuts, split-steps, spins, sharp turns, and decelerations—are critical manoeuvres in multidirectional sports, frequently determining match-winning moments (Dos’Santos et al., 2022; Martínez Hernández et al., 2022; Zahidi & Ismail, 2018). These actions serve to (1) evade opponents and create separation for attacking penetration, (2) close space, channel opponents, and execute defensive interventions, (3) generate high exit velocities, and / or (4) enable rapid redirection of the centre of mass (Dos’Santos et al., 2022; Young et al., 2022). Paradoxically, the same actions impose substantial mechanical loads that are implicated in lower-limb injuries, including ACL ruptures, hamstring and adductor strains, ankle sprains, and patellofemoral pain (Beaulieu et al., 2021; Dos’Santos et al., 2022; Kalkhoven et al., 2021). This blog examines the role of technique development in simultaneously enhancing agility performance and mitigating injury risk, reviews evidence-based instruction and feedback methods, and introduces the Agility Development Framework (ADF) as a structured approach to resolving the performance–injury conflict.

Numerous agility actions exist, each with distinct biomechanical characteristics and contextual applications (summarised in Table 1; see Dos’Santos et al., 2022 for detailed review). Given the chaotic and unpredictable nature of multidirectional sports, a unidimensional movement strategy is suboptimal. Instead, developing movement adaptability and a broad movement literacy — enabling athletes to select from multiple stable and unstable solutions — is essential for both performance and robustness (Dos’Santos, McBurnie, et al., 2019; McBurnie et al., 2022; Otte et al., 2019).

Table 1 | Agility actions including the advantages and considerations of each action, injury risk and considerations.

Table 2 | Agility actions including technique and mechanics, and scenarios of when each action is used.

The Importance of Technique in Agility Development

Agility is defined as rapid, whole-body movement involving changes in velocity or direction in response to a stimulus (Jones & Nimphius, 2018; Young & Farrow, 2006). As a perceptual–motor skill, it emerges from the interaction of technical, mechanical, physical, and perceptual-cognitive factors (DeWeese & Nimphius, 2016; Nimphius, 2017; Young et al., 2022). Technique—the relative positioning and sequencing of body segments to accomplish a task effectively (Lees, 2002)—is a foundational yet modifiable determinant of both performance and injury risk.

Optimal technique facilitates efficient braking, propulsion, and redirection of the centre of mass through features such as wide lateral foot placement, a firm base of support, rapid triple extension, and trunk control (Dos’Santos, Thomas, et al., 2021a; McBurnie, Dos’Santos, et al., 2021). Conversely, suboptimal technique (e.g., knee valgus, excessive lateral trunk flexion) amplifies hazardous joint loading and injury risk (Donelon et al., 2020; Fox, 2018). Importantly, targeted technique modification training lasting as little as six weeks has been shown to improve movement quality, reduce ground-contact time, increase exit velocity and propulsive forces, enhance kinematics, and attenuate knee joint loads during cutting and turning (Dempsey et al., 2009; Dos’Santos et al., 2019, 2021a,b; Jones et al., 2015). The optimal dosage and long-term retention of these adaptations, however, remain unclear and warrant further investigation, but these studies highlight the modifiable nature of agility actions.

No universal “optimal” technique exists, as execution is constrained by entry velocity, intended direction, contextual demands, and individual factors (anthropometrics, mobility, strength, training history) (Dos’Santos et al., 2018; McBurnie & Dos’Santos, 2022; Nimphius, 2017). Nevertheless, promoting within-skill (coordinative) and between-skill (movement selection) variability appears beneficial. Coordinative variability may distribute tissue loading more evenly, potentially reducing cumulative stress (Bartlett et al., 2007; Hamill et al., 2012), while a diverse movement selection enhances adaptability to unpredictable game constraints (Otte et al., 2019; Preatoni et al., 2013).

The overarching objective, and the Science of Multidirectional Speed philosophy, therefore, is to develop fast, robust 360° athletes who can rapidly and controllably change direction from either limb across a range of velocities, armed with a rich arsenal of contextually appropriate movement solutions (Dos’Santos et al., 2022; McBurnie & Dos’Santos, 2022). Although inter-individual technical differences are inevitable, fundamental biomechanical principles that optimise performance and minimise risk remain consistent (Jones et al., 2021; Lees, 2002). Technical models for key agility actions are presented in blog xxx and this article (Dos’Santos et al., 2022); thus, The subsequent section will outline how to design representative training environments using the ADF, incorporating evidence-informed instruction and feedback strategies to cultivate high-quality multidirectional speed technique.

Agility training philosophy and the agility development framework (ADF)

The overarching aim of the agility development framework (ADF) should be to create athletes who possess adaptable movement strategies and multiple movement solutions to solve the problems they encounter during the unpredictable and chaotic nature of multidirectional sports (Dos’Santos, McBurnie, et al., 2019; McBurnie & Dos’ Santos, 2022). Skill training is where athletes are able to “seek, explore, discover, assemble, and stabilise the coordination of movement patterns” (Davids et al., 2008). Thus, the ADF (Figure 1), to develop game-related movement skill, focuses on three phases (mesocycles) adapted from previous work (DeWeese & Nimphius, 2016; Dos’Santos, Thomas, et al., 2019b; Jones et al., 2015; Nimphius, 2017), and a similar approach to the Periodisation of Skill Training Framework (PoST) (Otte et al., 2019), Tabener’s et al. (2019) “control to chaos” continuum approach, and the Skill Acquisition Periodisation Framework (Farrow & Robertson, 2017): 1) technique acquisition; 2) technique retention and integrity; and 3) movement solutions. Initially, this approach (Phase 1) aims to develop pre-planned COD and deceleration technique and develop the athlete’s movement literacy (i.e., between-skill variability) in a controlled environment, before exposing the athletes to higher intensity, task complexity and mechanical loading, reinforcing optimal mechanics and exploring “repetition without repetition” and movement adaptability with the introduction of stimulus and information (low task complexity) (Phase 2). Finally, this leads to increases task complexity with multiple stimuli (and sports specific information), application in open, unanticipated and sports-specific activities with representative learning environments to improve the athlete’s ability to select appropriate movement solutions under differing task and constraints (perceptual-motor ability) for emergent behaviours and solutions to emerge (McCosker et al., 2019). Additionally, a critical feature within phase 2 and 3 is also developing the athletes’ movement capacity from compromised and sub-optimal positions to further develop movement solution and adaptability.

Figure 1 | Agility development framework

Pre-Implementation Requirements

Before applying the ADF, practitioners should conduct a comprehensive needs analysis that integrates:

Sport-specific movement profiling (typical angles, velocities, action sequences, offensive/defensive contexts)
Qualitative and quantitative assessment of COD, deceleration, and agility performance (e.g., Cutting Movement Assessment Score; Dos’Santos, Thomas, McBurnie, Donelon, et al., 2021);
Strength/power diagnostics and injury/training history;
Perceptual-cognitive demands and key informational cues (e.g., opponent hip orientation, relative positioning).

This athlete- and sport-specific profiling informs individualised entry points, prioritisation of technical targets, and cue selection within the framework (Nimphius, 2014, 2017).

Skill Practice Structure and Progression

The ADF employs a deliberate shift in practice organisation—from blocked to serial to randomised schedules—while progressively manipulating intensity, specificity, and contextual interference (Farrow & Robertson, 2017; Young & Farrow, 2013). This mirrors the “control–chaos” continuum (Taberner et al., 2019) and ensures conservative loading exposure, making it particularly suitable for developing athletes, those returning from injury, or during transitions from general preparation to in-season phases.

Key design principles (adapted from Otte et al., 2019) include:

High representativeness of perceptual and action constraints;
Strategic oscillation between stable and unstable movement conditions;
Graduated increases in informational complexity via constraint manipulation and scheduling.

These principles, detailed in the subsequent sections, provide the scaffolding for effective, evidence-informed agility development.

ADF: Phase 1

The primary goal of Phase 1 – technique acquisition, is to establish a broad, high-quality movement library by systematically introducing and refining the fundamental techniques of multidirectional speed and agility actions. This phase employs a highly controlled environment characterised by blocked practice (consecutive repetitions of the same task), low-to-moderate entry velocities, shallow change-of-direction angles, and sub-maximal intensity (Dos’Santos et al., 2018; Jones et al., 2015; Dempsey et al., 2009). Instruction is deliberately simple and externally focused, typically using one or two concise verbal cues derived from prior qualitative assessment (e.g., Cutting Movement Assessment Score; Dos’Santos, Thomas, McBurnie, Donelon, et al., 2021). An external focus of attention has consistently been shown to accelerate skill acquisition, enhance retention, improve performance outcomes, and promote safer biomechanical patterns compared with internal-focus cueing (Benjaminse et al., 2015; Benz et al., 2016; Porter et al., 2010; Winkelman, 2018).

Rather than pursuing early specialisation in a single “ideal” technique, Phase 1 prioritises movement diversification and between-skill variability. Athletes explore and stabilise a wide array of solutions, including:

Multiple deceleration strategies and end-body orientations (e.g., bilateral athletic stance, staggered split stance, single-leg pivot);
Varied propulsion directions from inside- or outside-leg push-offs;
Different cutting and reacceleration techniques (side-step, crossover cut, drop-step, split-step, spin, etc.).

This intentional breadth builds rich movement literacy, providing athletes with an extensive library of coordinative patterns that can later be selected and adapted under the perceptual and temporal pressures of competitive play. The overarching aim is to develop movement skill, developing the action capacity of the perceptual-action coupling associated with agility, and mechanical and technical ability to perform the movement, with deliberate practice a prominent feature of this phase. In essence, Phase 1 aligns with the stability and coordination stages of the Periodisation of Skill Training (PoST) framework (Otte et al., 2019). It emphasises deliberate practice to forge robust action capacity (underpin perception-action coupling), enhance mechanical efficiency, and create a versatile technical foundation from which more reactive and chaotic expressions of agility can safely emerge in subsequent phases. This approach is modelled on the movement stability and coordination training phases as suggested in the PoST framework (Otte, Millar, & Klatt, 2019). Example drills for Phase 1 are displayed in Videos 1 & 2.

ADF: Phase 2

With foundational movement stability and a diverse technical movement library established in Phase 1, Phase 2 systematically challenges the robustness of these patterns under progressively higher physical and perceptual demands (Dos’Santos, McBurnie, et al., 2019; Nimphius, 2017). The central objective is to preserve technical integrity and effective mechanics while exposing athletes to increased mechanical loading, thereby enhancing retention and stress-proofing the acquired skills.

Intensity is scaled through several evidence-informed factors:

Greater approach velocities and sharper change-of-direction angles (Bourgeois et al., 2017; Dos’Santos et al., 2018);
Longer acceleration distances prior to the directional change;
Serial combinations of actions (e.g., sprint → lateral shuffle → backpedal → drop-step → reacceleration);
Manoeuvrability activities that accumulate high volumes of high-intensity COD exposures (Jeffreys, 2010).

Practice structure transitions from predominantly blocked to serial and randomised practice structures, aligning with the principle of “repetition without repetition” (Myszka, 2018) and the skill adaptability stage of the PoST framework (Otte et al., 2019). This shift deliberately promotes within-skill variability and movement instability by encouraging subtle, self-organised adjustments in:

Braking strategy and stride adjustments;
Magnitude and direction of body lean;
Depth of hip, knee, and ankle flexion;
Foot placement relative to centre of mass;
Inclusion of transitional movements (e.g., rolling crossovers, jabs, shuffle) and initiation techniques (drop-step, split-step, inside/outside-leg push).

Additional constraint manipulations—varying run-up distances, starting postures, available space, or target zones—further amplify coordinative flexibility without sacrificing core mechanical principles (Spiteri et al., 2018). By repeatedly solving the same perceptual-motor problem in slightly different ways under varying intensity, athletes develop a resilient and adaptable technique that remains effective when fatigued or perturbed—qualities essential for transfer to the chaotic, reactive demands of Phase 3 and, ultimately, competitive performance.

Toward the latter stages of Phase 2, simple unanticipated elements can be introduced to elevate both cognitive and mechanical demand while remaining manageable (Farrow & Robertson, 2017; Otte et al., 2019; Young & Farrow, 2013). Examples include single-stimulus reactive drills triggered by visual cues (e.g., coach hand signal, flashing arrow, or light) or auditory commands. These impose a modest perceptual load—requiring the athlete to detect, process, and respond to one discrete piece of information—without fully replicating the rich, sport-specific informational landscape of open play.

Although such generic stimuli do not yet develop true sport-specific agility (Young & Farrow, 2013), lacking environmental and sport specific stimuli, they serve two valuable purposes:

They act as a robust stress test of technical integrity, as reduced decision time and restricted preparatory postural adjustments and muscle coordination and activation, typically provoke greater knee joint loading and momentary breakdowns in mechanics (Lee et al., 2013, 2017; Hughes & Dai, 2021).
They provide a controlled bridge toward the higher informational complexity of Phase 3, allowing practitioners to confirm that fundamental movement solutions remain stable under moderate reactive pressure before progressing.

Thus, successful negotiation of generic reactive tasks in Phase 2 signals readiness for the chaotic, multi-stimulus, and context-rich environments that characterise Phase 3 and competitive performance. Example drills for Phase 2 are displayed in Videos 3.

ADF: Phase 3

Phase 3 is the pinnacle of the ADF, where training becomes fully open, reactive, and ecologically valid. Drills are designed to mirror the chaotic, information-rich, and constraint-heavy nature of actual competition in multidirectional sports (Nimphius, 2017; Young & Farrow, 2013; Taberner et al., 2019). The environment progressively increases in perceptual-cognitive load by increasing the number, fidelity, and concurrency of stimuli (e.g., opponent body feints, relative positioning, ball trajectories, teammates’ runs, defensive structure) while simultaneously imposing tight temporal and spatial constraints. This forces athletes to continuously search for, detect, and exploit affordances in an ever-changing performance landscape (Gibson, 1979; Otte et al., 2019).

The overarching objectives are threefold of Phase 3:

Accelerate perceptual-cognitive expertise – faster and more accurate detection and utilisation of sport-specific informational cues (e.g., hip orientation, shoulder drop, weight shift);
Cultivate movement degeneracy – a rich, flexible repertoire of functionally equivalent solutions for identical performance problems (Seifert & Davids, 2017; Myszka, 2018);
Enhance transfer of training by preserving tight perception–action coupling under match-like pressure.

Small-sided games (SSGs), reactive 1v1, 2v1, 2v2, or overload scenarios, and constrained possession/retention games are the primary activities within this phase. These simultaneously develop agility expression, decision-making superiority, technical execution under pressure, tactical awareness, and physical conditioning in an integrated manner (Paul et al., 2016; Young et al., 2022). Practitioners should monitor both internal load (e.g., rating of perceived challenge; Hendricks et al., 2019) and external outcomes (successful evasions, tackles won, interceptions, defensive line breaks) to quantify agility performance and guide individual and session progression (Otte et al., 2020). An example of factors to manipulate drill / activity design are presented in Figure 2.

Figure 2 | Drill / activity construction: underlying components.

A constraint-led approach is central: task (rules, scoring zones, numerical advantage), environmental (pitch size, surface, boundaries), and organismic (fatigue state, limb restriction, equipment) constraints are continually manipulated to destabilise previously stable patterns and invite the emergence of new, creative solutions (McCosker et al., 2019). The coach’s role shifts from instructor to designer/facilitator, using questioning, silence, and bandwidth feedback to promote discovery learning rather than prescriptive cueing (Myszka, 2018; Otte et al., 2019).

Despite the emphasis on chaos, and potential use of SSGs, several practical challenges must be managed:

Precise dosing of high-intensity multidirectional actions is difficult in open play → supplement with GPS-derived COD counts and short pre-planned “top-up” exposures;
Athletes may default to preferred limb or movement patterns → use rule modifications, directional targets, or temporary limb restrictions to enforce between-skill variability;
Unequal stimulus distribution across players → rotate roles frequently, adjust area per player, and employ multiple simultaneous grids.

Finally, because the majority of match-play agility actions occur at sub-maximal intensities (Dos’Santos et al., 2022; Rayner et al., 2022), complete abandonment of pre-planned high-intensity work risks detraining of maximal braking/propulsive capacities and unilateral/bilateral mechanical robustness. Retaining a small, targeted dose of pre-planned, high-velocity COD and deceleration (ideally integrated into warm-ups or as short finishers) serves as a protective “maintenance stimulus” analogous to weekly high-speed running top-ups for hamstring health (Malone et al., 2017; McBurnie, Harper, et al., 2021).

In summary, Phase 3 fuses representative learning design, constraint-led methodology, and discovery-based coaching to forge perceptive, creative, and resilient athletes who thrive amid competition’s unpredictability. Close collaboration with skill-acquisition specialists and technical coaches is invaluable for maximising ecological validity and ensuring genuine transfer to match performance. Example drills for Phase 3 are displayed in Video 4

ADF: Programming and session plans

The three phases of the ADF are not rigid, mutually exclusive blocks; rather, each phase represents the primary emphasis—or largest proportion—of training volume during a given mesocycle (Nimphius, 2017). Most sessions will contain elements from all three phases, but with markedly different densities and intensities, following a classic emphasis model. The relative weighting of Phase 1, 2, and 3 content is individualised and dictated by factors such as training age, physical preparedness, movement competency gaps, results of qualitative/quantitative COD assessments, positional demands, injury history, and the current period of the season.

An example in-season agility session for a multidirectional invasion sport, illustrating the layered contribution of all three phases, is shown in Figure 3.

Although precise dosing guidelines for agility training remain an important research gap, existing technique-modification and COD speed studies suggest that two 15–30-minute focused sessions per week (≥48 h apart) are sufficient to drive meaningful improvements (Dempsey et al., 2009; Dos’Santos et al., 2019, 2021b; Falch et al., 2019). From a practical standpoint, we advocate a deliberately conservative progression profile for isolated agility sessions:

Total distance: 230–480 m per session
Change-of-direction actions: 20–40
Decelerations: 20–40
Perceived intensity: 50–100%

Week-to-week increases in these variables should generally stay within ~10% to respect tissue adaptation timelines and minimise spike-related injury risk (Gabbett, 2016; Kalkhoven et al., 2021; McBurnie et al., 2022). Quality of execution must always take precedence over volume as well. When scheduling or facility constraints prevent dedicated agility sessions, the same principles can be seamlessly embedded into daily field-based warm-ups (e.g., progressive technical circuits from Phase 1–2) or integrated into technical/tactical work in collaboration with the skills coach (Dos’Santos et al., 2019; McBurnie et al., 2022). Regardless of delivery method, agility content must be planned in the broader microcycle context, balancing intensive and extensive exposures with concurrent strength, conditioning, and sport-specific sessions.

Figure 3 | Drill examples of pre planned deceleration, change of direction, and agility.

ADF: practice structure, instruction and feedback, and learning activities

A defining feature of the ADF is the deliberate increase in contextual interference across phases. Phase 1 relies heavily on blocked practice (repeated execution of the same task) to accelerate early learning and stabilise coordination. Phase 2 transitions to serial and variance practice, introducing subtle perturbations and task switching. By Phase 3, sessions shift toward randomised and highly variable practice schedules. This progression has been consistently shown to enhance long-term retention and, most importantly, transfer to the unpredictable demands of match-play (Spiteri et al., 2018; Farrow & Robertson, 2017).

Instruction and Feedback Principles

Effective communication is critical for both performance enhancement and injury-risk reduction. Key evidence-based principles include:

External focus of attention via concise verbal cues and analogies outperforms internal-focus cueing for acquisition speed, retention, movement quality, and joint loading (Benjaminse et al., 2015; Benz et al., 2016; Winkelman, 2018).
Limit athletes to one or (at most) two cues per repetition to avoid cognitive overload and “paralysis by analysis” (Winkelman, 2018).
Provide frequent but targeted feedback early in learning; bandwidth or self-selected feedback becomes more appropriate as competency increases (Dempsey et al., 2009; Dos’Santos et al., 2021a,b).

Readers are strongly encouraged to consult the Skill Training Communication Model (Otte et al., 2020) for a comprehensive framework. Within the ADF, practitioners typically blend several complementary methods as illustrated in Table 3.

Table 3 | Overview of Instructional Methods Used in Agility Training

Our own applied research has successfully combined model learning, analogy-based cueing, and occasional video/self-modelling to significantly improve cutting and turning mechanics, reduce knee joint loads, and enhance performance in as little as six weeks (Dos’Santos et al., 2019, 2021a,b; Dos’Santos, Thomas, et al., 2021b).

Practical Recommendations

Prioritise positive, supportive, and descriptive feedback; emphasise what to do rather than what not to do (Otte et al., 2020).
Match the type and frequency of feedback to the athlete’s training age and the phase objective—more directive and frequent in Phase 1, sparser and athlete-led in Phase 3.
Use scenario-based, constraint-based, or object-based analogies (e.g., “Rip the paper under your foot,” “Be a rubber band snapping forward”) to maintain an external focus across all phases.

By aligning practice structure with progressively higher contextual interference and delivering clear, externally focused, individualised instruction and feedback, practitioners can maximise both technical mastery and ecological transfer within the ADF.

Summary

A wide variety of agility actions exist—side-steps, crossover cuts, drop-steps, spins, split-steps, and decelerations—each with unique biomechanical characteristics, advantages, and situational applications. Athletes deploy these actions for both attacking (evasion, line breaks, separation) and defensive (closing space, tackling, intercepting) purposes to achieve specific performance outcomes. Consequently, practitioners responsible for physical preparation must never underestimate the central role of technique in developing multidirectional-speed athletes. High-quality, adaptable technique is the primary modifiable factor that simultaneously enhances agility performance and mitigates lower-limb injury risk.

Virtually all multidirectional-sport athletes require the capacity to change direction rapidly and controllably within a full 360° spectrum, from either limb, across a range of velocities and contexts. Achieving this, demands more than isolated physical qualities—it requires athletes who possess rich movement literacy, functional variability, and multiple context-appropriate solutions for the unpredictable problems they will face in competition. The Agility Development Framework (ADF) we present provides a principled, periodised, and athlete-centred roadmap to achieve these attributes: robust, versatile, and agile movers who are fast, resilient, and capable of thriving amongst chaos of match-play.

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