Faster visual reaction times in elite athletes are not linked to better gaze stability

Abstract

The issue of whether visually-mediated, simple reaction time (VRT) is faster in elite athletes is contentious. Here, we examined if and how VRT is affected by gaze stability in groups of international cricketers (16 females, 28 males), professional rugby-league players (21 males), and non-sporting controls (20 females, 30 males). VRT was recorded via a button-press response to the sudden appearance of a stimulus (circular target—diameter 0.8°), that was presented centrally, or 7.5° to the left or right of fixation. The incidence and timing of saccades and blinks occurring from 450 ms before stimulus onset to 225 ms after onset were measured to quantify gaze stability. Our results show that (1) cricketers have faster VRT than controls; (2) blinks and, in particular, saccades are associated with slower VRT regardless of the level of sporting ability; (3) elite female cricketers had steadier gaze (fewer saccades and blinks) compared to female controls; (4) when we accounted for the presence of blinks and saccades, our group comparisons of VRT were virtually unchanged. The stability of gaze is not a factor that explains the difference between elite and control groups in VRT. Thus we conclude that better gaze stability cannot explain faster VRT in elite sports players.

Differences on Prosaccade Task in Skilled and Less Skilled Female Adolescent Soccer Players

“…The findings of the present study shed some light on understanding of the relationship between saccadic eye movement and skill level in the field of sport and expertise. Besides, these findings supported the results of previous studies, indicating that cognitive ability differed as a function of skill level ( Fontani et al, 2006 ; Brams et al, 2019 ; Barrett et al, 2020 ). Furthermore, the present study implies some practical applications for determining or predicting soccer players’ skill level and cognitive abilities by analyzing their saccadic eye movements during some eye movement tasks.…”

“…Similarly, Zwierko (2008) found that handball players had shorter response time to peripheral stimulus compared to nonathletes. A recent study showed that cricketers had faster visual reaction times than nonathletes and cricketers’ stability of gaze is associated with faster visual reaction time ( Barrett et al, 2020 ). Moreover, some researchers examined the search behaviors of skilled and less skilled soccer players when viewing film of defensive scenarios in soccer finding that skilled players exhibited more fixations, shorter duration, and more fixation locations than less skilled players ( Ward and Williams, 2003 ; Williams and Ericsson, 2005 ; Williams, 2009 ; Roca et al, 2011 ).…”

Comparison of whole-body sensorimotor skill learning between strength athletes, endurance athletes and healthy sedentary adults

“…Furthermore, CWB-SRTT does not contain specific movement patterns related to common practice routines of endurance or strength athletes. Although athletes of various disciplines generally have lower visual and auditory reaction times compared to non-athletes ( Atan and Akyol, 2014 ; Barrett et al., 2020 ), several studies indicate that these differences are highly sport- and task-specific ( Dogan, 2009 ; Kida et al., 2005 ). Furthermore, CWB-SRTT represents an extension of the simple, choice, and serial reaction time tasks.…”

“…Accordingly, some studies show elite athletes of different sports to outperform lower-level athletes in cognitive functions ( Scharfen and Memmert, 2019 ). Generally, these enhanced abilities potentially enable many athlete populations to better anticipate upcoming motor events and prepare and carry out optimal motor responses ( Barrett et al., 2020 ). On a behavioral level, this is, for example, expressed by lower reaction times of athletes within simple reaction time paradigms ( Atan and Akyol, 2014 ; Riedesel and Mahoney, 2013 ).…”

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

“…Raw data to define marginal distributions Brunyé et al, 2013;Giles et al, 2014;Mathiassen et al, 2014;Solis et al, 2015;Inoue et al, 2016;Harris et al, 2017;Hutchinson et al, 2017;Klein et al, 2017;Rosenbaum et al, 2017;Heuberger et al, 2018;Sandra and Otto, 2018;Schumacher et al, 2018;Angelidis et al, 2019;Bock et al, 2019;Goldfarb et al, 2019;Okano et al, 2019;Pyke et al, 2019;Sanabria et al, 2019;Wei et al, 2019;Barrett et al, 2020;Baumert et al, 2020;Fiedler et al, 2020;Holgado et al, 2020;Johnson et al, 2020;Knelange and López-Moliner, 2020;Larsen et al, 2020;Lin H. et al, 2020;Madore et al, 2020;Pahwa et al, 2020;Rodas and Greene, 2020;Rodeback et al, 2020;Timme and Brand, 2020;Tsukahara et al, 2020;Vine et al, 2020;von Helversen and Rieskamp, 2020;Pavlov and Kotchoubey, 2021 Effect size estimates to define xy relationships Lisper and Kjellberg, 1972;Glenville et al, 1978;Larsson, 1989;…”