Updating and complementing a previous review on eye-tracking technology and the dynamics of natural gaze behavior in sports, this short review focuses on the progress concerning researched sports tasks, applied methods of gaze data collection and analysis as well as derived gaze measures for the time interval of 2016–2022. To that end, a systematic review according to the PRISMA guidelines was conducted, searching Web of Science, PubMed Central, SPORTDiscus, and ScienceDirect for the keywords: eye tracking, gaze behavio*r, eye movement, and visual search. Thirty-one studies were identified for the review. On the one hand, a generally increased research interest and a wider area of researched sports with a particular increase in official’s gaze behavior were diagnosed. On the other hand, a general lack of progress concerning sample sizes, amounts of trials, employed eye-tracking technology and gaze analysis procedures must be acknowledged. Nevertheless, first attempts to automated gaze-cue-allocations (GCA) in mobile eye-tracking studies were seen, potentially enhancing objectivity, and alleviating the burden of manual workload inherently associated with conventional gaze analyses. Reinforcing the claims of the previous review, this review concludes by describing four distinct technological approaches to automating GCA, some of which are specifically suited to tackle the validity and generalizability issues associated with the current limitations of mobile eye-tracking studies on natural gaze behavior in sports.

The present study aims to reveal the effects of positioning on decision-making performance in top-level refereeing in association football. To this end, for all 64 matches of the FIFA World Cup 2014, potential foul-play situations were videometrically analysed in terms of the referee’s position relative to the infringement. Contrary to earlier studies, viewing angles were analysed in addition to viewing distances and error rates were considered for not only falsely whistled but also falsely non-whistled events. Moreover, direct logistic regression analysis was applied to detect position-dependent differences. For the total of 1,527 potential foul play situations, an overall low error rate of 6.9% was found. The similar numbers of total whistle (n = 52) and non-whistle errors (n = 54) reflect referees’ ability to balance both types of errors. Regarding the overall viewing-distance effect, referees were 2.58 times (95% CI 1.47–4.54) more likely to commit a whistle error at 10–15 m and 5.51 times (95% CI 1.35–22.47) more likely to commit a non-whistle error at 0–5 m, corresponding to the position ranges occurring with the highest (10–15 m: 30.3%) and lowest (0–5 m: 5.8%) frequencies. In contrast, no significant effects of viewing-angle on decision-making accuracy could be revealed.

This study tests Bayesian integration in a complex sensorimotor task: returning tennis serves. We found reliability-based prior-likelihood integration on two timescales: 1) over a “match” (increasing reliability of prior information) and 2) over a single serve (increasing reliability of sensory information). More generally, this study exemplifies how leveraging extended reality technology provides a means to reduce the internal versus external validity trade-off by studying motor control under real-world task demands while ensuring rigorous experimental control.

Sensorimotor training on an unstable base of support is considered to lead to improvements in balance and coordination tasks. Here, we intend to lay the groundwork for generating cost-effective real-time kinematic feedback for coordination training on devices with an unstable base of support, such as Sensopros or slacklines, by establishing a model for estimating relevant tape kinematic data from angle measurements alone. To assess the accuracy of the model in a real-world setting, we record a convenience sample of three people performing ten exercises on the Sensopro Luna and compare the model predictions to motion capture data of the tape. The measured accuracy is reported for each target measure separately, namely the roll angle and $XYZ$-position of the tape segment directly below the foot. After the initial assessment of the model in its general form, we also propose how to adjust the model parameters based on preliminary measurements to adapt it to a specific setting and further improve its accuracy. The results show that the proposed method is viable for recording tape kinematic data in real-world settings, and may therefore serve as a performance indicator directly or form the basis for estimating posture and other measures related to human motor control in a more intricate training feedback system.

We extend the study of sensorimotor behavior under risk from simple finger-pointing movements (Trommershäuser et al., Trends Cogn Sci 12: 291–297, 2008) to a complex throwing task in virtual reality. Our results suggest that, in complex sensorimotor behavior, risk evaluation of potential movements is not confined to a cognitive planning phase before movement but is optimized in action, with the motor system continuously biasing competing action options toward regions of higher expected rewards.