Out of your zone? 21 years of travel and performance in Super Rugby

An exploratory study into the relationship between playing at home or away and concussion

PRIMARY OBJECTIVE

To investigate the effect of home and away game travel on risk of concussion across different levels of rugby union.

RESEARCH DESIGN

Exploration study across school, university, and professional rugby teams.

METHODS AND PROCEDURES

Retrospective analysis of concussion incidence and symptomology of surveillance data and prospective data collection for potential concussions via surveys. Data was collected from school rugby teams (n = 344 matches, over 2 years), a university rugby (n = 6 matches), and a professional rugby team (n = 64 matches, over two seasons).

MAIN OUTCOMES AND RESULTS

School level rugby had an increased prevalence of concussions in away matches (p = 0.02). Likewise, there was a significant increase (p < 0.05) in concussions at away matches in university rugby. In addition, the professional rug by team had significant differences in recovery times and symptoms with away fixtures, including longer recovery times (p < 0.01), more initial symptoms (p < 0.01), as well as greater and more severe symptoms at 48 hours (p < 0.05).

CONCLUSIONS

This research highlights an increased prevalence of concussion in school and university-aged rugby players away from home, as well as increased symptoms, symptom severity, and recovery times in professional rugby players.

Associations of circadian change, travel distance, and their interaction with basketball performance: a retrospective analysis of 2014-2018 National Basketball Association data

This investigation aimed to clarify the influence of circadian change and travel distance on National Basketball Association (NBA) team performance using a dataset from the 2014-2018 seasons. Data from 9,840 games were acquired from an open-access source. Game point differential and team free-throw percentage served as outcome variables. Time zone change (TZΔ) captured raw circadian delay/advance based on travel for a game and adjusted TZΔ (AdjTZΔ) evolved TZΔ by allowing acclimation to a novel TZ. We also further categorized AdjTZΔ into AdjTZΔ_A, which assumed travel the day before each game and AdjTZΔ_B, which assumed teams spent as many days in their home city as possible. Travel distance for each game was calculated. Linear mixed-effects modeling estimated associations, with games nested within team and year. Adjusted associations accounted for differences in team ability, whether the game was home or away, and whether the game occurred on the second half of a back-to-back game sequence. Greater circadian misalignment, regardless of delay or advance, and increasing travel distance negatively influenced NBA game performance. Yet, results suggest that performance outcomes may be more influenced by travel distance than circadian misalignment. Moreover, circadian misalignment and travel distance interacted to significantly influence game point differential. Furthermore, differences in results across analyses were observed between AdjTZΔ_A and AdjTZΔ_B, which suggests that subtle differences in constructed travel schedules can have notable impact on NBA performance outcomes. Lastly, playing on the second half of a back-to-back sequence emerged as a robust predictor of performance disadvantage, which corroborates the existing literature and provides further support for NBA schedule changes purposed to enhance competitive equity by reducing the number of back-to-back games across a season. These findings can help guide NBA teams on key strategies for reducing travel-related disadvantages and inform schedule makers on critical factors to prioritize across future schedules to attenuate competitive inequity from travel. Furthermore, they can help direct teams towards scenarios that are best to target for load management purposes due to the cumulative disadvantage arising from travel-related factors, opponent quality, game location, and game sequence.

The effects of travel on performance: a 13-year analysis of the National Rugby League (NRL) competition

The purpose was to investigate the effects of travel on performance in the National Rugby League (NRL). A total of 4,704 observations from 2,352 NRL matches (2007-2019) were analysed. The effect of travel on match outcome (i.e., win/loss) was analysed using a generalized linear mixed model, and the points difference using a linear mixed model. For every 1,000 km travelled in the NRL, the estimated probability of winning a match was reduced by -2.7% [-5.7 to 0.3%] and the estimated points difference by -1.1 [-2.0 to -0.2] points. In relation to every 1,000 km travelled, the 2007-2009 seasons had the greatest reduction in the likelihood of winning a match (-2.7% [-4.7 to -0.6%]), with the 2018-2019 seasons having the greatest likelihood (1.1% [-1.2 to 3.3%]). Regarding inter-state travel, teams from the state of Queensland had the greatest reduction in the likelihood of winning a match while the team from the state of Victoria had the greatest likelihood, although there were no clear differences between states. These data suggest that travel has impacted performance in NRL matches although this effect has reduced over time. These findings are useful for practitioners that prepare athletes in sports where frequent short-haul travel is required.

Sport Performance Analysis with a Focus on Racket Sports: A Review

Athletes, both professional and amateur, are always looking for ways to improve their performance. With the introduction and increasing availability of modern technologies and smart devices arose the need to measure and analyze performance, but likewise, the use of these innovations as a competitive advantage also arose. Scientific publications reflect the wide range of available approaches and technologies, as well as the growing interest in various sports. As a result, we concentrated on a systematic review of publications that presented performance analysis tools and methods in all sports, with a final focus on racket sports. Clarivate Analytics’ Web of Science (WoS) and Elsevier Inc.’s SCOPUS databases were searched for 1147 studies that conducted performance analysis and sports research and were published in English. The data in the systematic review are current, up until 18 May 2021. A general review was performed on 759 items, and then 65 racket sports publications were thoroughly scrutinized. We concentrated on performance data, data collection and analysis tools, performance analysis methods, and software. We also talked about performance prediction. In performance research, we have identified specific approaches for specific sports as well as key countries. We are also considering expanding performance analysis in to E-sports in the future.