Part 3: The Biases That Shape (and Undermine) Athlete Preparation Behaviours
Applied Behavioural Sports Science Series
If Part 2 established that automatic cognitive processes (System 1) govern much of an athlete’s preparatory behaviour, Part 3 turns to the predictable distortions that arise from those processes. Cognitive biases are not arbitrary flaws; they are systematic, reproducible tendencies that shape decisions under uncertainty, effort, fatigue, and pressure. In high-performance sport, where training and recovery behaviours accumulate over months and seasons, these biases exert a profound influence on athlete development.
This post examines several cognitive biases particularly relevant to athlete preparation (present bias, loss aversion, the planning fallacy, the availability heuristic, and default bias) and considers their implications within a complex systems framework. Importantly, we do not treat these biases as individual “failures,” but as emergent properties of the athlete–environment interaction. By understanding these forces, we as practitioners can design environments that counteract them, thereby supporting more stable and adaptive behaviours.
Cognitive Biases as Constraints on Behaviour
Cognitive biases function as individual constraints in the ecological dynamics sense. These biases are consistent, person-specific tendencies that shape perception, decision-making, and action. However, unlike anthropometric or physiological constraints, cognitive biases are not fixed; they are plastic and context-dependent. They can be amplified or attenuated by environmental design, social influence, and behavioural architecture.
This makes them highly relevant to performance environments. If biases influence preparatory behaviours, and if those biases are malleable, then high-performance systems can be designed to regulate them.
Kahneman and Tversky’s research (1979, 1984) forms the empirical foundation for much of what follows, but contemporary behavioural design (Wendel, 2013; Thaler & Sunstein, 2008) provides practical mechanisms for influencing bias-driven decision patterns.
Present Bias: The Preference for Immediate Rewards
Present bias refers to the systematic overvaluation of immediate rewards relative to future benefits. In the context of athlete preparation, present bias manifests in behaviours such as:
choosing indulgent foods over nutritionally appropriate ones
skipping recovery to leave earlier
avoiding uncomfortable gym sets
delaying sleep for short-term entertainment
deferring conditioning intensity because of transient fatigue
The behaviour is predictable and not irrational. Evidence consistently shows that we as humans discount future benefits when faced with immediate alternatives (Laibson, 1997; Frederick et al., 2002). For athletes, the utility of future outcomes such improved body composition, enhanced aerobic capacity, reduced injury risk, is often too abstract to outweigh the immediacy of comfort or convenience.
From a complex systems perspective, present bias acts as an attractor where athletes reliably gravitate toward low-effort, high-immediacy behaviours unless the environment is structured to counteract this pull. Behavioural design therefore aims to reduce the temporal distance between action and reinforcement.
Examples of reducing the present–future gap:
immediate feedback in velocity-based training
fast-acting reinforcement around recovery (e.g., gamified check-ins)
transparent progress dashboards visible to athletes
simplified routines that generate small, rapid wins
These strategies shift the reward structure so that System 1 perceives value now, not later.
Loss Aversion: Avoiding Discomfort at the Cost of Progress
Loss aversion describes the psychological phenomenon where losses loom larger than equivalent gains. Kahneman and Tversky (1979) estimated that losses have approximately twice the psychological impact of gains.
In athlete preparation, loss aversion is often misinterpreted as a lack of resilience or discipline. Yet many behaviours can be explained more parsimoniously as an aversion to the perceived “loss” of comfort, effort, or emotional safety. Examples include:
athletes choosing submaximal loads to avoid the “loss” of comfort
reluctance to tighten nutrition to avoid perceived deprivation
avoidance of conditioning sessions perceived as punishing
resistance to recovery modalities that feel unpleasant (cold water immersion)
hesitance to engage in prehabilitation due to boredom or discomfort
Loss aversion can also appear in identity-preserving behaviours. An athlete might avoid adopting new habits because doing so threatens an existing identity (“I’m not the type who meal preps,” “I’ve always relied on my natural fitness”). Here, the “loss” is symbolic rather than physical.
Behavioural design counteracts loss aversion by reframing choices, minimizing friction, and increasing the perceived gain from desired actions.
Examples:
making the desired behaviour the path of least resistance
using social norms to convert loss-avoidance into belonging-avoidance
reducing the discomfort of complex tasks through simplification
presenting progress as avoiding a negative outcome (e.g., “maintaining speed advantage”)
Loss aversion cannot be removed, but it can be strategically redirected.
The Planning Fallacy: Overestimating What One Will Do
The planning fallacy describes the human tendency to underestimate the effort required to complete future tasks and overestimate one’s likelihood of doing them well (Kahneman & Tversky, 1979). Athletes routinely fall victim to this:
“I’ll clean up my diet next week.”
“I’ll go harder in conditioning tomorrow.”
“I’ll get to bed earlier once things settle down.”
“I’ll do my recovery when I get home.”
These intentions are sincere, but they are generated by System 2 in a moment free from immediate constraints. Once System 1 resumes control in real time, such as when fatigue, emotion, or convenience dominate, the behaviour collapses.
The literature on implementation intentions (Gollwitzer, 1999) suggests that behaviour becomes more reliable when abstract intentions are replaced with specific, context-bound cues (“If situation X occurs, I will perform behaviour Y”). In sport, this suggests a move away from general verbal commitment and toward structured, environmental action prompts.
Examples:
pre-specified gym loads visible on racks
recovery checklists placed in the locker rooms
designated post-training nutrition items waiting in a central location
When behaviour becomes “if–then” rather than “I intend to,” adherence improves.
The Availability Heuristic: Salience Over Importance
The availability heuristic refers to the tendency to judge the significance of information based on how easily it comes to mind. In sport, this bias explains why:
athletes often prioritise highly visible modalities (compression boots, ice baths)
recovery strategies that feel tangible are overrated relative to sleep or nutrition
Irregular intense efforts overshadow consistent submaximal effort
rare but dramatic performance moments distort self-perception
novel interventions are pursued more eagerly than proven fundamentals
Athletes, like all humans, overvalue what is vivid and undervalue what is systemic. Sleep is the clearest example where its invisibility makes it cognitively distant despite its overwhelming scientific importance (Fullagar et al., 2015).
From a systems perspective, the availability heuristic creates skewed attractors where athletes orient toward salient (most noticeable) interventions rather than effective ones. Behavioural design therefore seeks to make important behaviours visible.
Examples:
sleep dashboards displayed to athletes
nutritional targets presented in simple, daily indicators
visible progress markers for aerobic conditioning
“behaviour leaderboards” focusing on input metrics
Visibility becomes a constraint and an attractor for System-1 behaviour.
Default Bias: The Power of the Path of Least Resistance
Default bias refers to the human tendency to adopt the option that requires the least effort or energy. In high-performance environments, this bias is magnified by the constant presence of fatigue.
Athletes typically:
take the shortest route out of the facility
choose foods placed closest to them
engage in minimal recovery unless prompted
rely on habitual lifting patterns
adopt the routines of their immediate social group
What appears as “laziness” is in fact a predictable cognitive tendency interacting with the athlete’s energetic state. Remarkably, numerous field and laboratory studies show that altering defaults yields profound behavioural changes across diverse populations (Johnson & Goldstein, 2003). In sport, this principle is perhaps the most powerful behavioural design tool available.
Examples:
placing recovery equipment on the exit path
making healthier foods the default buffet options
structuring training groups to foster desired lifting intent
using pre-set gym loads as the default rather than optional
automating post-training nutrition distribution
Behaviour becomes the default rather than the exception.
Biases as Systemic Properties, Not Athlete Weaknesses
The key argument of this chapter is that these biases are not individual deficiencies. They are systematic tendencies of human cognition that become amplified in high-performance contexts due to fatigue, emotional stress, workload, and environmental complexity.
From a complex systems perspective:
biases act as constraints
constraints shape behavioural emergence
behavioural emergence shapes adaptation
Thus, the goal is not to eliminate bias (which is an impossible task) but to design preparation environments that anticipate and neutralise their effects.
Conclusion
Cognitive biases systematically shape athlete behaviour, often in ways that directly undermine long-term performance goals. Yet these biases are neither arbitrary nor immutable. Their influence can be altered by strategically manipulating constraints, redesigning choice environments, and structuring behavioural cues in alignment with how humans actually make decisions.
By integrating Kahneman and Tversky’s work on judgement and decision-making with behavioural design frameworks such as Wendel’s, practitioners can construct preparation environments that channel natural cognitive tendencies toward desirable behaviours rather than away from them. This marks a change from athlete-centred blame to system-centred design, and it is foundational to Applied Behavioural Sports Science.