583 – Applying Dynamical Systems Theory in Coaching, New Course Announcement

today on the perception and action podcast a look at a couple of articles that emphasize the value of applying dynamical systems theory and coaching and an exciting announcement about a new course i'm offering in which i will teach you how to apply it in your particular sport so it's time for a call to action hi this is rob gray from arizona state university i've been on a now over 25 year journey as a researcher professor and high performance consultant to understand how we acquire and adapt our perceptual motor skills welcome to the perception and action podcast where i discuss how psychological research can be applied to improving performance accelerating skill acquisition and designing technologies now on to the show in today's episode i want to start a series focused on applying dynamical systems theory in coaching and introduce an exciting course i'm going to be offering in which i will teach you how to apply dynamical systems theory offering to not bury the lead i think we've reached a point where applying the tools of non-linear dynamics is something that is feasible for a coach to start doing themselves collecting their own time series data doing analysis of variability via vibe coding and identifying things like attractors and invariants in this course which i'm going to be offering for the first time starting in february 2027 my goal is to work with coaches in developing their skill in how to do this we'll look at how to collect time series data using both iphone cameras and cheap wearable accelerometers from there we'll go through the basics of filtering and cleaning the data then finally we'll get to different dynamical systems theory measures things like entropy relative phase fractals uncontrolled manifold analysis the lyapuna exponent to name a few so it will be a mix of learning concepts and learning how to apply them the course will involve online recorded materials students can work throughout their own practice and learn how to apply them to their own course so i'm going to go through the basics of filtering and cleaning their own space group meetings where students will share some of their work and questions with the rest of the cohort and one-on-one meetings with me where we'll talk about applying dynamical systems theory in your specific sporting context and achieving your specific goals i'm keeping these courses small so we have lots of time for interaction you can find out more about this course and the other ones i'm offering by going to perceptionaction.com for slash courses a quote from one of the papers i will talk about later in the episode dynamical system theory is a tool that can be used to apply dynamical systems theory to advanced complex system understanding by analyzing spatial temporal characteristics of coordination patterns and tasks requiring the use of multiple biomechanical degrees of freedom within the broader principles of complex systems dynamical systems theory explores how movement patterns emerge through a process of self-organization and where movement variability is viewed as an essential motor behavior rather than a movement error quantifying coordination variability using these methods may be the only true method in which a practitioner may fully experience the impact of this approach and consider the emergence of new coordination patterns despite a dynamical systems theory approach becoming more prevalent within sport research translating this knowledge to the practitioner on the ground remains a challenge in this course i want to try to meet that challenge on that page i just mentioned you will also find information about my cla design course which is already filled up for the first two sessions starting december 2026 at april 27 but i will be offering more in the future for the rest of today's episode i want to look at a how dynamical systems theory can be applied in coaching trying to motivate you in seeing its value the first is a recent proof of concept study i conducted with college baseball pitchers this study builds on the ideas of nick steragoo director of the center for research in human movement variability at the university of naraska omaha for example in his great article published in 2009 he presents how non-linear dynamic can be applied to pt and understanding sports injury he presents evidence that healthy movement can be applied to pt and understanding sports injury involves variability and complexity rather than perfect repeatability and predictability which of course i've talked about many times on the podcast before to quote the article thus we propose that optimal movement variability lies between too much variability and complete repeatability dynamical systems theory introduced the notions of stability and non-linearity to explain variability the structure of variability as opposed to just the amount can be described using non-linear tools these non-linear tools best capture variation in how a motor behavior emerges in time for which the temporal organization and the distribution of values is of interest end quote so the basic idea is that there's more to variability than just the magnitude whether it's high or low its structure how it evolves over time gives us much more information about coordination is the system perfectly repeatable or does it have some complexity by which we mean somewhere in between not going to completely random locations over time but rather being drawn back to some the same locations but never via the same exact path in other words an attractor or a variant as i mentioned in my last book i've started to apply non-linear dynamics to use as an early warning signal for detecting potential injury the goal of this study was to conduct a proof of concept test to evaluate the possibility of using critical fluctuations i.e destabilization in the coordination variable as early warning signals for arm injuries and basal injury and non-linear dynamics as early warning signals for arm injuries and basal injury baseball pitchers for this study three college baseball players with a history of arm injuries and two pitchers with no injury history were tracked across the course of the 2024 season markerless motion capture data from each game started a minimum of 70 pitches and during bullpen sessions between starts were used to calculate the hearst exponent sample entropy and the index of synergy pitch flight data for example velocity spin and pitch movement and subjective ratings of pain and perceived exertion were also collected the results were as follows three of the five participating pitchers two with previous injury history and one without were placed on the injury list with arm issues during the course of the season for these three pitchers there were significant changes in the three coordination measures on average 3.6 games before being placed on the il consistent with previous research significant changes in the pitch parameters for example a decrease in fast ball play for the first time in the two pitchers who did not go on the il there were no significant changes in any of the variables for the two pitchers who did not go on the il overall the pattern results is consistent with a dynamical systems model of sports injury which changes in coordination for example muscles playing different roles in a motor synergy precede both declines in performance and major injury the next step i'm working on is of course understanding what we can do about it once we can detect these changes in coordination in my new course i'm going to show you how to get measures like this and how you might apply it in your sport the second paper i want to look at is a recent one by hicks at all on applying dynamical systems theory to understanding coordination in sprinting traditionally sprinting has been coached from a reductionistic or cognitive perspective decomposing performance to individual component parts these approaches often identify average group-oriented sprints coordination strategies or patterns to improve efficiency of movement and achieve quote-unquote optimal sprint technique the authors propose using a dynamical systems framework instead quote sprint coordination within a dynamical systems theory framework emphasizing how sprint performance emerges from constantly varying internal or external constraints that regulate patterns of coordination by controlling mechanical metabolic and neurophysiological degrees of freedom within the limits of the system therefore movement variability is viewed as an essential component of coordination rather than simply noise end quote a key property of complex systems the authors emphasize is their non-linearity highlighting how little causes can contribute to large effects these non-linear cause and effect relationships have previously been observed during running and sprinting for example when a runner begins to get fatigued subtle changes in velocity often lead to spontaneous shifts in coordination patterns and muscle activation synergies in an attempt to maintain performance i discuss this idea in my book at advanced ecological approach when discussing effort-based training sometimes a change in one variable can lead to a completely reorganized pattern rather than just a linear scaling from a dynamical systems perspective how can we shape coordination as a coach by manipulating constraints of course to quote the authors sprint athletes constantly navigate constraints via their own intrinsic dynamics such as preferred mode of coordination or previous movement experiences for example a sprinter with long limb segments may leverage a greater step length at maximal velocity but must therefore coordinate larger inertial demands at the hip as a trade-off end quote one of the reasons usain bolt is the fastest man ever is that he could coordinate a large step length with still managing step frequency this allowed bolt to take almost four fewer steps across the course of a race obviously most tall athletes do not achieve this level of sprinting success along with step length there are many other constraints involved quote across sprint phases horizontal force production can be classified as a short-term boundary condition fluctuates with neuromuscular readiness or fatigue it strongly influences the ability to maximize forward propulsion when accelerating in contrast developing the capacity to produce greater levels of force directed horizontally a key to acceleration occurs over longer time scales through training adaptations by manipulating and guiding constraints participants can shape each athlete's learning environment to allow individualized coordination and control patterns to emerge within the system's boundary conditions. end quote. The next talk about how sprinting can be understood in terms of Bernstein's, see also Newell, concepts of coordination and control, quote, in sprinting, coordination can therefore be seen in the relative timing and sequences of limb movements during the stride cycle. That results from the control that pertains to the magnitude and velocity of joint rotations and force application, end quote. Think of limb segment sequencing as coordination and force application at different phases of the sprint as control. Dynamical systems theory can be used to understand coordination with reference to phase transitions. For example, a spontaneous reorganization of movement pattern due to changes in a control parameter, such as velocity, stability and flexibility of movement and movement variability, all of which underpin athlete-specific movement, end quote. The body of evidence suggests while specific patterns, for example, increased antiphase thigh-thigh coordination, appear more consistently at higher speeds. The variability across conditions and individuals highlights there's no single fixed technique. In turn, this supports a dynamical systems theory perspective that maximal velocity sprinting is not defined by universal movement templates, but by context-dependent coordination strategies that self-organize to meet individual performance needs, end quote. This paper also does a great job discussing how a coach must balance self-organization at multiple timescales, both short-term to find a solution to the constraint you've put in front of the athlete, now and longer-term to change their sprint coordination, end quote. Most importantly, there are two different forms of self-organization on different timescales that must be distinguished. Self-organization within a task and self-organization across training. In the first case, the athlete spontaneously fixes the available degrees of freedom in a stable pattern in order to solve a single movement requirement under the current system. End quote. Coupling, relative phase and synergies arise spontaneously and stabilize or reconfigure the pattern, for example, freezing, releasing degrees of freedom, without any external specification of how the movement is to be performed. In the second case, exploration across many different tasks or exercises reshapes the solution landscape, resulting in a new, more effective coordination pattern. Here, the athlete organizes both each exercise and cumulatively, the repertoire itself. Variability drives reorganization rather than simply optimizing a fixed solution. End quote. This is something I actually want to dig into a bit more in the future, what I'm calling long-term athlete development within the CLA. Quote, from this perspective, coaching cues can be viewed as one type of constraint that interacts not only with the athlete, task, and environment, but also situative conditions, shaping but not determining a coordination solution. In addition, the focus shifts from cueing athletes to cueing athletes towards a single model of sprint technique to designing environments and instructions that facilitate individualized yet functional movement solutions. They discuss how this, again, could be understood within dynamical systems theory, in particular, in terms of phase transitions. Quote, recognizing when targeted coaching interventions should either reinforce or challenge existing coordination patterns is therefore essential knowledge. Modifications to sprint coordination patterns must align with the intervention and skill acquisition approach to either reinforce an attractor or induce a transition to a new coordination pattern, for example, a new attractor. Mini hurdles or wickets are an example of how a coach can manipulate task constraints to shape sprint-specific movement solutions. By adjusting the spacing, the coach can emphasize different aspects of sprinting. Placing the hurdles closer together, for example, encourages a higher step frequency, while placing them further apart promotes an increased step length. In this way, mini hurdles act as a task constraint where the hurdle distances are adjusted to the subjective information in terms of the individual needs, guiding the athlete toward externally focused movement adjustments. Rather than instructing the athlete with internal cues like pick up your knees or hit the ground with more force, which may disrupt self-organization, the mini hurdles create an environment where the athlete implicitly adapts their mechanics. This may indirectly lead to picking up the knees, shorter hurdle distance, or hitting the ground with more force, longer hurdle distance. End quote. Approaches that draw on dynamical systems theory to explain performance see the role of coach shift from a person who gives direct feedback on technique, for example, the coach giving the answer to a solution, to a facilitator who creates an interactive learning environment for athletes to solve movement problems. Key to this approach is for practitioners to explore a dynamical systems perspective, including conceptions as constraints, degrees of freedom, the necessity of differences for learning and self-organization, and the role in sprint coordination and performance. Furthermore, we challenge practitioners to consider drawing on skill acquisition approaches embedded in dynamical systems theory, for example, the CLA, highlighting the individual nature of how patterns of sprint coordination and performance emerge. End quote. Okay, that's it for today's episode. If my little sales pitch for applying dynamical systems theory and coaching was convincing, you can find out more information about my new course. Please contact me. Remember, you can contact me at robgray at asu.com. Or follow me on Twitter at shaky weights. To find out more about the podcast, please check out perceptionaction.com. Finally, to support the podcast and receive bonus materials, including a monthly coaches meetup, please head over to patreon.com forward slash perception action. This is Rob Gray from ASU. Cheers for now, and keep them couple.