Longitudinal changes in Super League match locomotor and event characteristics: A league-wide investigation over three seasons in rugby league

The effects of rule changes in football-code team sports: a systematic review

Rule changes within football-code team sports aim to improve performance, enhance player welfare, increase competitiveness, and provide player development opportunities. This manuscript aimed to review research investigating the effects of rule changes in football-code team sports. A systematic search of electronic databases (PubMed, ScienceDirect, CINAHL, MEDLINE, and SPORTDiscus) was performed to August 2023; keywords related to rule changes, football-code team sports, and activity type. Studies were excluded if they failed to investigate a football-code team sport, did not quantify the change of rule, or were review articles. Forty-six studies met the eligibility criteria. Four different football codes were reported: Australian rules football (n = 4), rugby league (n = 6), rugby union (n = 16), soccer (n = 20). The most common category was physical performance and match-play characteristics (n = 22). Evidence appears at a high risk of bias partly due to the quasi-experimental nature of included studies, which are inherently non-randomised, but also due to the lack of control for confounding factors within most studies included. Rule changes can result in unintended consequences to performance (e.g., longer breaks in play) and effect player behaviour (i.e., reduce tackler height in rugby) but might not achieve desired outcome (i.e., unchanged concussion incidence). Coaches and governing bodies should regularly and systematically investigate the effects of rule changes to understand their influence on performance and injury risk. It is imperative that future studies analysing rule changes within football codes account for confounding factors by implementing suitable study designs and statistical analysis techniques.

Validation of field-based running tests to determine maximal aerobic speed in professional rugby league

Practitioners place importance on high-speed running (HSR) to monitor training practice and match-play demands, whilst attempting to maximise fitness and minimize the risk of injury occurrence. Practitioners apply various methods to quantify HSR, such as absolute thresholds, percentage of maximum sprint speed and maximal aerobic speed (MAS). A recent survey demonstrates the 5-minute run and 1200m shuttle test (ST) to be implemented among rugby league practitioners to quantify HSR by incorporating MAS. However, it is unclear as to how valid these methods are to accurately quantify MAS. Therefore, the aim of this study was to assess the validity of the 5-minute run and 1200m ST when compared to a gold standard measure for MAS. Twenty 1st team professional rugby league players competing in the European Super League participated in this study. Players were required to complete an incremental treadmill test, 5-minute run and 1200m ST over a two-week period in pre-season. MAS, peak heart rate (HRmax), peak lactate (Lapeak) and rating of perceived exertion (RPE) where collected upon completion of each test. Results demonstrated the 1200m ST to have a higher correlation for MAS than the 5-minute run (1200m ST: r = 0.73, 5-minute run: r = 0.64). However, when assessing validity using the level of agreement between data, the 5-minute run underreported MAS by 0.45 m·s-1 whereas the 1200m ST underreported MAS by 0.77 m·s-1. Ultimately, both field-based tests used in this study underreport MAS when compared to an incremental treadmill test, although the 5-minute run provides a closer agreement and therefore a more valid measurement for MAS than the 1200m ST.

Identification of pattern mining algorithm for rugby league players positional groups separation based on movement patterns

The application of pattern mining algorithms to extract movement patterns from sports big data can improve training specificity by facilitating a more granular evaluation of movement. Since movement patterns can only occur as consecutive, non-consecutive, or non-sequential, this study aimed to identify the best set of movement patterns for player movement profiling in professional rugby league and quantify the similarity among distinct movement patterns. Three pattern mining algorithms (l-length Closed Contiguous [LCCspm], Longest Common Subsequence [LCS] and AprioriClose) were used to extract patterns to profile elite rugby football league hookers (n = 22 players) and wingers (n = 28 players) match-games movements across 319 matches. Jaccard similarity score was used to quantify the similarity between algorithms' movement patterns and machine learning classification modelling identified the best algorithm's movement patterns to separate playing positions. LCCspm and LCS movement patterns shared a 0.19 Jaccard similarity score. AprioriClose movement patterns shared no significant Jaccard similarity with LCCspm (0.008) and LCS (0.009) patterns. The closed contiguous movement patterns profiled by LCCspm best-separated players into playing positions. Multi-layered Perceptron classification algorithm achieved the highest accuracy of 91.02% and precision, recall and F1 scores of 0.91 respectively. Therefore, we recommend the extraction of closed contiguous (consecutive) over non-consecutive and non-sequential movement patterns for separating groups of players.

Understanding elite rugby league players' experience of collision, effective contact coaching techniques, and player contact psychology: A focus group study

The current study performed a series of online focus groups to understand elite rugby league players' experiences of collision. Eighteen rugby league players comprising different playing positions from four teams were recruited to participate in a series of online focus groups, via the Microsoft Team's platform, facilitated by a moderator. Players were competing in Europe's elite rugby league competition, the European Super League (ESL), during the 2021 season. All focus group data were transcribed, coded and analysed using reflexive thematic analysis guide to ensure robust exploring, interpreting and reporting through pattern-based analysis. The findings are split into five key themes: 1) the three-man tackle - the perceived optimal defensive strategy with simultaneous contact, 2) not all collisions are the same; matchplay events change the collision intensity, 3) bracing and blindsiding - two factors that influence experiences of collision and concussion, 4) coaching philosophies and orientations, 5) psychological readiness for collision. Collision sports have an inherent risk of injury; however, in some players' subjective experiences, there are collision types that have a greater association with risk or intensity (blind-sided collisions or long closing distances). It is essential that future research comprehends the effects of these collision types and the further themes.

Contributors to negative biopsychosocial health or performance outcomes in rugby players (CoNBO): a systematic review and Delphi study protocol

The importance of contributors that can result in negative player outcomes in sport and the feasibility and barriers to modifying these to optimise player health and well-being have yet to be established. Within rugby codes (rugby league, rugby union and rugby sevens), within male and female cohorts across playing levels (full-time senior, part-time senior, age grade), this project aims to develop a consensus on contributors to negative biopsychosocial outcomes in rugby players (known as the CoNBO study) and establish stakeholder perceived importance of the identified contributors and barriers to their management. This project will consist of three parts; part 1: a systematic review, part 2: a three-round expert Delphi study and part 3: stakeholder rating of feasibility and barriers to management. Within part 1, systematic searches of electronic databases (PubMed, Scopus, MEDLINE, SPORTDiscus, CINAHL) will be performed. The systematic review protocol is registered with PROSPERO. Studies will be searched to identify physical, psychological and/or social factors resulting in negative player outcomes in rugby. Part 2 will consist of a three-round expert Delphi consensus study to establish additional physical, psychological and/or social factors that result in negative player outcomes in rugby and their importance. In part 3, stakeholders (eg, coaches, chief executive officers and players) will provide perceptions of the feasibility and barriers to modifying the identified factors within their setting. On completion, several manuscripts will be submitted for publication in peer-reviewed journals. The findings of this project have worldwide relevance for stakeholders in the rugby codes. PROSPERO registration number CRD42022346751.

Ready for impact? A validity and feasibility study of instrumented mouthguards (iMGs)

OBJECTIVES

Assess the validity and feasibility of current instrumented mouthguards (iMGs) and associated systems.

METHODS

Phase I; four iMG systems (Biocore-Football Research Inc (FRI), HitIQ, ORB, Prevent) were compared against dummy headform laboratory criterion standards (25, 50, 75, 100 g). Phase II; four iMG systems were evaluated for on-field validity of iMG-triggered events against video-verification to determine true-positives, false-positives and false-negatives (20±9 player matches per iMG). Phase III; four iMG systems were evaluated by 18 rugby players, for perceptions of fit, comfort and function. Phase IV; three iMG systems (Biocore-FRI, HitIQ, Prevent) were evaluated for practical feasibility (System Usability Scale (SUS)) by four practitioners.

RESULTS

Phase I; total concordance correlation coefficients were 0.986, 0.965, 0.525 and 0.984 for Biocore-FRI, HitIQ, ORB and Prevent. Phase II; different on-field kinematics were observed between iMGs. Positive predictive values were 0.98, 0.90, 0.53 and 0.94 for Biocore-FRI, HitIQ, ORB and Prevent. Sensitivity values were 0.51, 0.40, 0.71 and 0.75 for Biocore-FRI, HitIQ, ORB and Prevent. Phase III; player perceptions of fit, comfort and function were 77%, 6/10, 55% for Biocore-FRI, 88%, 8/10, 61% for HitIQ, 65%, 5/10, 43% for ORB and 85%, 8/10, 67% for Prevent. Phase IV; SUS (preparation-management) was 51.3-50.6/100, 71.3-78.8/100 and 83.8-80.0/100 for Biocore-FRI, HitIQ and Prevent.

CONCLUSION

This study shows differences between current iMG systems exist. Sporting organisations can use these findings when evaluating which iMG system is most appropriate to monitor head acceleration events in athletes, supporting player welfare initiatives related to concussion and head acceleration exposure.