Expert-Novice comparisons in Sports Performance: from the Quiet Eye to the Zone

Recently, we published a blog about The Quiet Eye, an important sports metric for understanding the moment before a critical movement (like a shot or serve, or maybe a pitch, pass, or putt). Eye tracking is an effective wearable for measuring and training the quiet eye, but this research can also be supplemented with metrics related to cognitive load or stress (such as heart rate variability from ECG). Plenty of research across different sports has shown that the Quiet Eye differs between experienced players and novices and can be trained to enhance performance.

In light of this recent blog (and in anticipation of the Super Bowl), this article discusses how wearables are used in sports performance research to investigate and quantify expert-novice differences.

Expert-novice comparisons across sports increasingly explore attention and rely on eye tracking

Sports performance experts conduct expert-novice comparisons to see what distinguishes the pros from the amateurs in order to identify opportunities for improvement and develop strategies to exploit those opportunities. While there are many differences between experts and novices (such as experience and perhaps physique), there is increasing use of eye tracking because visual attention is strongly linked to performance in many sports.

Because we have some conscious control over what we pay attention to, when, and for how long, we can learn to alter our visual attention (to some extent). Understanding the quiet eye, field of vision, visual search strategies, attention allocation, depth perception, anticipatory skills, and response time can all be explored with eye tracking.

Expert-novice comparisons should be multi-modal

But expert-novice differences are not just about attention and execution. Expertise differentiation is also about perception, decision-making, and performance under pressure. This is where sports research becomes more multimodal and nonconscious behaviors give valuable information into what players may not be aware of or have more trouble controlling in the moment. These are the techniques that help researchers understand phenomena such as what it means to get into the zone or what predicts the yips or the twisties.

• Supplement eye tracking with other modalities: This gives different nuances to the data. Are players holding their breath or consciously changing their breathing during or prior to the quiet eye? Does their heart rate change?
• Simulations, Augmented and Virtual Reality: These technologies are becoming more popular in sports performance research and training to allow players to experience scenarios repeatedly and train their decision-making. They have also been used to mentally prepare players by exposing them to stadiums and environments before major tournaments or competitions. Biofeedback and neurofeedback tools have also been used to give players insights into their own nonconscious responses.
• Event-related potentials (ERPs): EEG has been used to understand motion-in depth perception, allowing coaches to understand how depth perception during motion differs with experienced players. These can also be combined with simulations and virtual reality mentioned previously.  EEG is also used for neurofeedback in training sessions, fatigue and metal state monitoring, as well as cognitive load assessment.
• Heart rate variability (HRV): This metric from ECG gives powerful insights into a player’s stress levels and cognitive load during play and before competitions.

While metrics like ERP and HRV reflect nonconscious processes, it does not mean that athletes cannot improve performance. Rather, the metrics are used to track progress and evaluate how effective a training strategy is. For example, effective relaxation techniques and breathing exercises are expected to alter HRV.

Final Thoughts: Considerations for Expert-Novice Comparisons

Situational insights: Is your metric dependent on the tedium of the practice or does it withstand the elevated excitement and pressure of game day? Can you use self-report measures regarding prior sleep and diet to determine how they influence your metrics?

Consider your Controls: Who are you calling a rookie? If you are comparing pro athletes to amateurs in the same sport, make sure the physiological differences are not due to age. While all of the study participants might be athletic, children and adults have different physiology and are at different phases of development.

Hold that Baseline: It is also important to keep as many variables in the testing environment as similar as possible. You don’t want to test experts on a cold day and then test novices on a warm day, if you can avoid it. You don’t want to test one group in the morning and then the other in the afternoon. While it can be impossible to recreate an identical set-up with all variables accounted for, be mindful of your study design and its limitations.