ABSTRACT
Notational analysis is a popular tool for understanding what constitutes optimal performance in traditional sports. However, this approach has been seldom used in esports. The popular esport "Rocket League" is an ideal candidate for notational analysis due to the availability of an online repository containing data from millions of matches. The purpose of this study was to use Random Forest models to identify in-match metrics that predicted match outcome (performance indicators or "PIs") and/or in-game player rank (rank indicators or "RIs"). We evaluated match data from 21,588 Rocket League matches involving players from four different ranks. Upon identifying goal difference (GD) as a suitable outcome measure for Rocket League match performance, Random Forest models were used alongside accompanying variable importance methods to identify metrics that were PIs or RIs. We found shots taken, shots conceded, saves made, and time spent goalside of the ball to be the most important PIs, and time spent at supersonic speed, time spent on the ground, shots conceded and time spent goalside of the ball to be the most important RIs. This work is the first to use Random Forest learning algorithms to highlight the most critical PIs and RIs in a prominent esport.
ABSTRACT
There is a scarcity of research examining the effects of long-distance transmeridian travel (LDTT) on the sleep and match performance of team sport players. To address this, 37 elite male rugby union players from a Super Rugby team undertaking LDTT were recruited. The participants completed validated sleep questionnaires and wore a wrist-worn activity monitor (Readiband™) during a Super Rugby season (including during periods of LDTT crossing 5, 6, and 13 time-zones) to ascertain objective measures of sleep. Sleep measures were compared using mixed model analysis to ascertain the effects of competition and LDTT on sleep. Total sleep time (TST) increased in the days prior to matches, and decreased following matches (accompanied by a later time at sleep onset), particularly when next-day early-morning flights were required. TST was decreased when sleep was attempted during LDTT, except for in the last travel bout where players napped in addition to achieving night-time sleep. TST was also reduced for the night immediately following LDTT, except for in Condition 3 where players delayed wake time and also achieved naps. This study exemplifies the challenges that team-sport athletes face in obtaining regular sleep when LDTT is required.
Subject(s)
Rugby , Sleep , Athletes , Humans , Male , Polysomnography , TravelABSTRACT
Globally, depression and anxiety are the two most prevalent mental health disorders. They occur both acutely and chronically, with various symptoms commonly expressed subclinically. The treatment gap and stigma associated with such mental health disorders are common issues encountered worldwide. Given the economic and health care service burden of mental illnesses, there is a heightened demand for accessible and cost-effective methods that prevent occurrence of mental health illnesses and facilitate coping with mental health illnesses. This demand has been exacerbated post the advent of the COVID-19 pandemic and the subsequent increase in incidence of mental health disorders. To address these demands, a growing body of research is exploring alternative solutions to traditional mental health treatment methods. Commercial video games have been shown to impart cognitive benefits to those playing regularly (ie, attention control, cognitive flexibility, and information processing). In this paper, we specifically focus on the mental health benefits associated with playing commercial video games to address symptoms of depression and anxiety. In light of the current research, we conclude that commercial video games show great promise as inexpensive, readily accessible, internationally available, effective, and stigma-free resources for the mitigation of some mental health issues in the absence of, or in addition to, traditional therapeutic treatments.
ABSTRACT
STUDY OBJECTIVES: To synthesize original articles exploring the effects of sleep restriction on cognitive performance specifically for Elite Cognitive Performers, i.e. those who engage in cognitively demanding tasks with critical or safety-critical outcomes in their occupation or area of expertise. METHODS: Backward snowballing techniques, gray literature searches, and traditional database searches (Embase, MEDLINE, Web of Science, Google Scholar, PSYCinfo, and SportDiscus) were used to obtain relevant articles. A quality assessment was performed, and the risk of training effects was considered. Results were narratively synthesized. Fourteen articles fit the criteria. Cognitive outcomes were divided into three categories defined by whether cognitive demands were "low-salience," "high-salience stable," or "high-salience flexible." RESULTS: Low-salience tests (i.e. psychomotor vigilance tasks & serial reaction tests), mainly requiring vigilance and rudimentary attentional capacities, were sensitive to sleep restriction, however, this did not necessarily translate to significant performance deficits on low-salience occupation-specific task performance. High-salience cognitive outcomes were typically unaffected unless when cognitive flexibility was required. CONCLUSIONS: Sleep restriction is of particular concern to occupations whereby individuals perform (1) simple, low-salience tasks or (2) high-salience tasks with demands on the flexible allocation of attention and working memory, with critical or safety-critical outcomes.
