Basketball, Goalies, and Perception–Action Asymmetries

Why might basketball be a useful complementary sport for hockey goaltenders?

In this episode, I explore that question through the lens of perception, not conditioning or skill transfer in the traditional sense. The discussion starts with multi-sport participation and why transfer appears more likely when sports share similar perceptual problems, even if the movements themselves are different.

Using an older, Russian psychology paper as a starting point, I look at how athletes’ perception of space may become directionally tuned based on the demands of their sport. The study compared young basketball and hockey players and found that spatial representation differed depending on whether the sport primarily operated in the vertical plane (basketball) or the horizontal plane (hockey).

The authors described this pattern using the term reverse perspective—a label that feels clunky and unintuitive today, but which helped surface an important idea: perception does not develop evenly. Instead, it adapts around the actions and spatial problems athletes are repeatedly asked to solve.

From there, the episode reframes the findings using a more modern concept: perception–action asymmetries. Rather than viewing these patterns as perceptual errors or distortions, they can be understood as functional adaptations—certain dimensions of space are weighted more heavily because they matter more for successful action.

The episode then brings this idea back to goaltending, examining how hockey heavily emphasizes horizontal information while still requiring accurate reads in the vertical plane through screens, tips, release height, and rebounds. Basketball is discussed not as a solution or fix, but as a different perceptual environment that may expose goalies to vertical spatial problems in ways hockey does not consistently provide.

Importantly, this episode does not argue that playing basketball will improve shot-height recognition or replace hockey-specific training. Instead, it offers a conceptual framework for thinking about athlete development: what perceptual problems are athletes actually being asked to solve, and which ones might they rarely encounter?

The goal is not prescription, but perspective.

Quiet Eye Isn’t Quiet | How Elite Athletes Actually See

We tend to think of vision as clear, continuous, and camera-like.
In reality, it’s fragmented, selective, and heavily constructed by the brain.

In this episode, I explore how elite athletes use their eyes under pressure — and why traditional “Quiet Eye” explanations fall short when applied to fast, open sports like hockey.

Using a landmark on-ice eye-tracking study by Martell & Vickers (2004), we break down how expert defenders don’t simply hold their gaze longer, but instead use a rapid-to-stable cascade of visual attention: quick sampling early, followed by a final stabilizing fixation before action.

This episode reframes Quiet Eye not as a single moment, but as the final phase of a much more dynamic perceptual process.

• Why most of your visual field is blurry — and why you never notice

• How the brain fills in blind spots and missing information

• What “Quiet Eye” really means in closed vs open sports

• Why team-sport gaze research produced conflicting coaching advice

• How this study used live, on-ice eye tracking instead of video simulations

• Key differences between elite and near-elite visual behavior

• Why elite athletes succeed with shorter fixations, not longer ones

• The idea of a “quick-then-quiet” gaze cascade

• Implications for hockey, goaltending, and skill development

• Why training vision requires humility, not simple prescriptions

Elite vision isn’t calm from the start — it’s efficient.

Experts sample information rapidly, recognize patterns early, and only settle into a longer, stabilizing gaze once the situation collapses and action is inevitable.

Quiet Eye still matters — but it’s earned, not forced.

Martell, S. G., & Vickers, J. N. (2004).
Gaze characteristics of elite and near-elite athletes in ice hockey defensive tactics.
Human Movement Science, 22, 689–712.

The Coretex Athletic Review explores sport science, perception, and performance through the lens of real research — with a bias toward practical relevance for coaches, athletes, and practitioners.

In this episode, I examine how athletes learn skills by watching others—and why perfect demonstrations may not always be the most effective teaching tool.

I review a research study that explores whether learners benefit more from observing a flawless expert, or from watching someone make mistakes and correct them in real time. The findings have important implications for coaching, teaching, and skill development—particularly in early learning stages.

This episode reviews a study by Anastasia Kitsantas, Barry J. Zimmerman, and Tim Cleary, published in the Journal of Educational Psychology titled The Role of Observation and Emulation in the Development of Athletic Self-Regulation.

• Participants:
  60 ninth-grade students with little to no prior experience in the task

• Task:
  Learning a dart-throwing skill broken down into specific technical components

• Purpose:
  To examine how different types of demonstrations and feedback influence skill learning, confidence, motivation, and self-regulation

Participants were assigned to one of three modeling conditions:

• No model: verbal instruction only

• Mastery model: a demonstrator performing the skill flawlessly

• Coping model: a demonstrator who initially makes errors, then gradually corrects them

Each group was further split based on whether they received simple verbal feedback during practice.

• Learners who observed a coping model:

  • Performed the skill more accurately

  • Reported higher confidence (self-efficacy)

  • Showed greater satisfaction and intrinsic interest

• Learners who observed a mastery model performed better than those with no model—but consistently worse than those who observed coping models.

• Social feedback during practice improved outcomes overall, but did not eliminate the advantage of coping models.

• Most notably, learners who observed coping models were more likely to attribute mistakes to strategy, rather than ability or effort—a pattern strongly associated with better learning and motivation.

The study suggests that:

• Early learning benefits from seeing how mistakes are corrected, not just what “perfect” execution looks like

• Demonstrations shape not only movement patterns, but how athletes interpret success and failure

• Intentional error-and-correction demonstrations may help athletes develop better self-regulation skills

This episode explores how these findings map onto real-world coaching environments, particularly in group settings and early skill acquisition.

Perfect demonstrations can establish standards—but learning how to adjust, correct, and adapt may require seeing imperfection first.

In this episode, host Evan Kurylo revisits The Mundanity of Excellence (1989) by sociologist Daniel F. Chambliss — an ethnographic study of Olympic-level swimmers that challenges how we think about talent, hard work, and athlete development.

Rather than framing excellence as the result of dramatic breakthroughs, rare talent, or cutting-edge methods, Chambliss shows that elite performance emerges from mundane, highly structured daily behaviours embedded within different competitive cultures. Excellence, he argues, is not flashy — it is boring, consistent, and normalized.

The episode opens with the idea that facts have a “half-life,” drawing on examples from medical science to show how some knowledge decays quickly while broader behavioural patterns tend to persist. From there, we explore Chambliss’s key concept of stratification — the idea that competitive levels are not just different in quantity, but in quality, culture, and expectations.

The discussion also introduces an interpretive distinction between improvement within a level and advancement between levels, arguing that while performance can scale empirically within a stable framework, moving between levels often requires a conceptual shift in how training is structured. This idea is stress-tested with counter-examples and caveats, including early-stage learning, physiological adaptation, and late specialization.

This episode is not about dismissing hard work or data, but about understanding when effort helps — and when it simply reinforces a ceiling.

• The “half-life” of facts and why some ideas age better than others

• Stratification in sport as culture, not just selection

• Quantitative vs qualitative differences in athlete development

• Why “more training” often fails to produce elite performance

• The Mission Viejo Swimming Club example

• Excellence as normalized, mundane discipline

• Conceptual vs empirical problems in development

• Counter-examples and limitations of Chambliss’s framework

• Connections to nonlinear pedagogy and skill acquisition

Chambliss, D. F. (1989). The Mundanity of Excellence: An Ethnographic Report on Stratification and Olympic Swimmers. Sociological Theory, 7(1), 70–86.

Within a level, performance often scales with effort.
Between levels, advancement usually requires a change in structure.
Excellence is rarely dramatic — it is built through boring, high-fidelity execution over time.

This episode presents an interpretation of Chambliss’s work alongside modern perspectives from coaching and skill acquisition. Where applicable, limitations and counter-examples are discussed to avoid oversimplifying athlete development.

This episode explores how athletes make sense of fast, chaotic game environments using internal models, priors, and pattern recognition. Through the lens of Bayesian reasoning and Piaget’s concepts of assimilation and accommodation, we break down why anticipation is a skill, why young athletes often lag in perceptual processing, and why predictable drills don’t transfer well into games. A practical, clear look at the cognitive side of skill development.

These aren’t quoted directly in the episode, but they underlie the explanations:

• Simply Psychology: Schemas, Assimilation & Accommodation⁠⁠https://www.simplypsychology.org/piaget-assimilation-accommodation.html⁠⁠

• Verywell Mind: Piaget’s Stages of Cognitive Development

• Stanford Encyclopedia of Philosophy: Jean Piaget

• Piaget, J. (1952). The Origins of Intelligence in Children.

• Kahneman & Tversky – Judgment Under Uncertainty (base rate fallacy)

• Gigerenzer, G. – Risk Savvy (intuition vs statistics)

• Griffiths & Tenenbaum – Bayesian models of cognition

• Abernethy, B. – Perceptual expertise in sport

• Vickers, J. – Decision Training

• Davids, K. – Dynamics of Skill Acquisition

Dan Morris book Bayes Theorem: A Visual Introduction for Beginners: https://a.co/d/eRmMNC3

Article: https://pubmed.ncbi.nlm.nih.gov/30024211/

Episode 1 — The Birthplace Effect: Population Size, Relative Age, and the Hidden Ecology of Talent

This episode reviews the landmark 2006 study by Côté et al. examining how birthplace population and birthdate influence elite athlete emergence across the NHL, MLB, NBA, and PGA.

Topics covered:

• Why the strongest athlete representation comes from cities of 50,000–100,000

• Effect size comparisons: birthplace (3.51) vs. relative age (0.44)

• Why large metropolitan areas and rural towns under-produce pros

• Environmental and psychosocial explanations for the “Goldilocks Zone”

• Updated caveats from recent (2021–2024) research

• Practical implications for parents, coaches, and development pathways

Link to the original article: https://pubmed.ncbi.nlm.nih.gov/17115521/

Hosted by: Evan Kurylo
Presented by: Coretex Athletics