Performance Analysis in Rugby Union: a Critical Systematic Review

Testing in Intermittent Sports-Importance for Training and Performance Optimization in Adult Athletes

ABSTRACT

Performance in intermittent sports relies on the interplay between multiple physiological systems determining the capacity to perform short explosive efforts as well as repeated intense actions with limited recovery over the course of an entire game. Testing should reflect these demands to allow for sport- and position-specific capacity analyses that eventually may translate into optimized training and improved performance. This may include individual load management and optimized training prescription, intensity targeting for specific positions or individual athletes, as well as benchmarking for monitoring of training progression and enhanced engagement of athletes. This review provides an overview of available tests in different exercise domains identified as relevant (from assessment of single explosive actions to intermittent endurance capacity), forming the basis for recommendations on how to compose a comprehensive yet feasible test battery that may be integrated into the seasonal competition and training plan. The test procedures should cover the performance spectrum of relevance for the individual athlete-also in team sports to account for positional differences. We emphasize the benefits of sport-specific tests, highlight parameters of importance for test standardization, and discuss how the applied test battery may be supplemented with secondary tests directed toward specific energy systems to allow for more in-depth analyses when required (e.g., in terms of an underperforming athlete). The synergy between testing and tracking of match performance (utilizing time-motion or global positioning systems) is highlighted, and although tracking cannot substitute for testing, combining the tools may provide a comprehensive overview of the physiological demands and performance during competition contextualized to the athletes' maximal exercise capacity.

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.

Classifying Winning Performances in International Women's Rugby Union

PURPOSE

The efficacy of isolated and relative performance indicators (PIs) has been compared in rugby union; the latter more effective at discerning match outcomes. However, this methodology has not been applied in women's rugby. The aim of this study was to identify PIs that maximize prediction accuracy of match outcome, from isolated and relative data sets, in women's rugby union.

METHODS

Twenty-six PIs were selected from 110 women's international rugby matches between 2017 and 2022 to form an isolated data set, with relative data sets determined by subtracting corresponding opposition PIs. Random forest classification was completed on both data sets, and feature selection and importance were used to simplify models and interpret key PIs. Models were used in prediction on the 2021 World Cup to evaluate performance on unseen data.

RESULTS

The isolated full model correctly classified 75% of outcomes (CI, 65%-82%), whereas the relative full model correctly classified 78% (CI, 69%-86%). Reduced respective models correctly classified 74% (CI, 65%-82%) and 76% (CI, 67%-84%). Reduced models correctly predicted 100% and 96% of outcomes for isolated and relative test data sets, respectively. No significant difference in accuracy was found between data sets. In the relative reduced model, meters made, clean breaks, missed tackles, lineouts lost, carries, and kicks from hand were significant.

CONCLUSIONS

Increased relative meters made, clean breaks, carries, and kicks from hand and decreased relative missed tackles and lineouts lost were associated with success. This information can be utilized to inform physical and tactical preparation and direct physiological studies in women's rugby.

Team Behavior and Performance: An Exploration in the Context of Professional Rugby Union

PURPOSE

To explore complex system behavior and subsequent team performance in professional rugby union.

METHODS

Here, we present 2 studies. In the first, we used global positioning system technology to measure player clustering during stoppages in play in nearly 100 games of professional rugby union to explore team (complex system) behavior and performance. In the second, we measured stress hormones (cortisol and testosterone) prior to team meetings and analyzed these relative to amount of time and the frequency with which players looked at peer presenters, as well as subsequent training performance, to explain how stress may lead to behaviors observed in the first study and subsequent match performance.

RESULTS

No link between player clustering during stoppages of play and performance was observed. When players (complex system agents) demonstrated greater levels of stress (as indicated by greater cortisol-awakening response and a greater decline in testosterone-to-cortisol ratio across the morning), they tended to look at peer presenters more; however, training quality declined (P = .02). Correlational analysis also showed that training quality was related to testosterone-to-cortisol ratio (P = .04).

CONCLUSIONS

Team behavior is complex and can be unpredictable. It is possible that under stress, complex system agents (ie, rugby union players) look at (and cluster toward) their teammates more; however, meaningful interaction may not necessarily occur. Furthermore, while complex system (team) analysis may be valuable strategically in rugby union in the context of describing behavior, without understanding "how" or "why" intrateam/interagent behaviors emerge it may have little meaning.

New Zealand Youth Rugby Sevens: A Comparative Match Demands Study

Rugby sevens has established itself on the world stage since its inclusion in the 2016 Olympics. Participation among New Zealand (NZ) youth has surged. Sevens games have specific high demands, but little is known about these competitive demands in regards to youth. Two NZ male youth squads (U15, n = 13; U19, n = 14) were monitored during a national sevens tournament. Microsensor technology captured heart rate (HR) and kinematic performance. The rating of perceived exertion (RPE) was collected for U15 matches only. U19 and U15 players ran 108 ± 11 and 116 ± 13 m·min^-1 at an average speed (V_AVG) of 6.5 ± 0.6 and 6.9 ± 0.8 km·h^-1. Peak speeds (V_PEAK) reached 33.7 km·h^-1, and high-intensity running distance (HIRD) averaged 252 ± 102 m. U15 (44.3 ± 9.2 game^-1) and U19 (39.4 ± 6.1 game^-1) showed different sprint rates. U15 covered more moderate-velocity distance (20-80% V_MAX) and less low-velocity distance (<20% V_MAX). RPE was 13 ± 1 (U15). An average HR of 90.0 ± 3.9% HR_MAX was recorded. Upwards of 57% of game time was played at >95% HR_MAX. Youth sevens competition is specifically demanding. U15 can experience greater loads than older peers in rugby. Coaches can use this information to optimize players' physical development.

Performance indicators associated with match outcome within the United Rugby Championship

OBJECTIVES

The aims of this study were to: i) identify performance indicators associated with match outcomes in the United Rugby Championship; ii) compare the efficacy of isolated and relative datasets to predict match outcome; and iii) investigate whether reduced statistical models can reproduce predictive accuracy.

DESIGN

Retrospective analysis of key performance indicators in the United Rugby Championship.

METHODS

Twenty-seven performance indicators were selected from 96 matches (2020-21 United Rugby Championship). Random forest classification was completed on isolated and relative datasets, using a binary match outcome (win/lose). Maximum relevance and minimum redundancy performance indicator selection was utilised to reduce models. In addition, models were tested on 53 matches from the 2021-22 season to ascertain prediction accuracy.

RESULTS

Within the 2020-21 datasets, the full models correctly classified 83% of match performances for the relative dataset and 64% for isolated data, the equivalent reduced models classified 85% and 66% respectively. The reduced relative model successfully predicted 90% of match performances in the 21-22 season, highlighting that five performance indicators were significant: kicks from hand, metres made, clean breaks, turnovers conceded and scrum penalties.

CONCLUSIONS

Relative performance indicators were more effective in predicting match outcomes than isolated data. Reducing features used in random forest classification did not degrade prediction accuracy, whilst also simplifying interpretation for practitioners. Increased kicks from hand, metres made, and clean breaks compared to the opposition, as well as fewer scrum penalties and turnovers conceded were all indicators of winning match outcomes within the United Rugby Championship.

Match Analysis in Team Ball Sports: An Umbrella Review of Systematic Reviews and Meta-Analyses

Background

Match analysis has evolved exponentially over the past decades in team sports resulting in a significant number of published systematic reviews and meta-analyses. An umbrella review of the available literature is needed to provide an integrated overview of current knowledge and contribute to more robust theoretical explanations of team performance.

Methods

The Web of Science (all databases), PubMed, Cochrane Library (Cochrane Database of Systematic Reviews), Scopus, and SPORTDiscus databases were searched for relevant publications prior to 19 February 2021. Appraisal of the methodological quality of included articles was undertaken using the tool for Assessing the Methodological Quality of Systematic Reviews (AMSTAR-2). Twenty-four studies were reviewed that met the following criteria: (1) contained relevant data from match analyses in team ball sports; (2) were defined as systematic reviews or/and meta-analyses; and (3) were written in the English language.

Results

The overall methodological quality of the 24 included reviews, obtained through the AMSTAR-2, revealed very low confidence ratings (Critically Low, n = 12) for the results of most systematic reviews of match analyses in team ball sports. Additionally, the results showed that research is focused mainly on four levels of analysis: (1) dyadic (microlevel); (2) individual (molecular level; predominant); (3) group (mesolevel), and (4) team dynamics (macrolevel). These levels of analysis included tactical, technical, physical, and psychosocial variables. Team performance was contextualized at two levels, with reference to: (1) match context (e.g. match status, match location, match period, quality of opposition) and (2) sociodemographic and environmental constraints (sex, age groups, competitive level, altitude, temperature, pitch surface).

Conclusions

The evolution of methods for match analysis in team ball sports indicates that: (1) an individual-level performance analysis was predominant; (2) the focus on intermediate levels of analysis, observing performance in dyadic and group interactions, has received less attention from researchers; (3) neglected areas of research include psychosocial aspects of team sports and women’s performance; and (4) analyses of match contexts need greater depth.

Registration: The protocol was registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols with the number 202080067 and the DOI number https://doi.org/10.37766/inplasy2020.8.0067.

Identifying the Current State and Improvement Opportunities in the Information Flows Necessary to Manage Professional Athletes: A Case Study in Rugby Union

In sporting environments, the knowledge necessary to manage athletes is built on information flows associated with player management processes. In current literature, there are limited case studies available to illustrate how such information flows are optimized. Hence, as the first step of an optimization project, this study aimed to evaluate the current state and the improvement opportunities in the player management information flow executed within the High-Performance Unit (HPU) at a professional rugby union club in England. Guided by a Business Process Management framework, elicitation of the current process architecture illustrated the existence of 18 process units and two core process value chains relating to player management. From the identified processes, the HPU management team prioritized 7 processes for optimization. In-depth details on the current state (As-Is) of the selected processes were extracted from semi-structured, interview-based process discovery and were modeled using Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) standards. Results were presented for current issues in the information flow of the daily training load management process, identified through a thematic analysis conducted on the data obtained mainly from focus group discussions with the main stakeholders (physiotherapists, strength and conditioning coaches, and HPU management team) of the process. Specifically, the current state player management information flow in the HPU had issues relating to knowledge creation and process flexibility. Therefore, the results illustrate that requirements for information flow optimization within the considered environment exist in the transition from data to knowledge during the execution of player management decision-making processes.

Guidelines for performing systematic reviews in sports science

Most of the reviews carried out in sports science have used the general items suggested by Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). Due to the specific requirements of each knowledge area, several modifications of the PRISMA are necessary to optimize the process of the systematic reviews and, in consequence, the quality of the conclusions provided in this type of study. Therefore, this work aimed to adapt PRISMA to provide specific guidelines to carry out systematic reviews in sports science. The methodology criteria (search strategy, databases, and eligibility) and the results section (flow diagrams and study contents) were adapted based on previous studies, and several new considerations were added to design the new guidelines. We compiled 28 items suggested by sports science researchers and included two new items: (i) population/problem (i.e., age, level, and country) and (ii) the entire training process, which is monitored and compared between groups (e.g., total training load). To maximize the benefit of this document, we encourage people to read it in conjunction with the PRISMA statement. The main differences between PRISMA and the PRISMA adapted to sports science were related to registration, search strategy, flow diagrams, and results. Application of the new guidelines could improve the information provided to readers and make it easier to generalize and compare the results in sports science.

A Machine Learning Approach to Analyze Home Advantage during COVID-19 Pandemic Period with Regards to Margin of Victory and to Different Tournaments in Professional Rugby Union Competitions

Home advantage (HA) is the tendency for sporting teams to perform better at their home ground than away from home, it is also influenced by the crowd support, and its existence has been well established in a wide range of team sports including rugby union. Among all the HA determinants, the positive contribute of the crowd support on the game outcome can be analyzed in the unique pandemic situation of COVID-19. Therefore, the aim of the present study was to analyze the HA of professional high-level rugby club competition from a complex dynamical system perspective before and during the COVID-19 pandemic. HA was analyzed in northern and southern hemisphere rugby tournaments with (2013–2019) and without (2020/21) crowd support by the means of the exhaustive chi-square automatic interaction detection (CHAID) decision trees (DT). HA was mitigated by the crowd absence especially in closed games, although differences between tournaments emerged. Both for northern and southern hemisphere, the effect of playing without the crowd support had a negative impact on the home team advantage. These findings evidenced that in ghost games, where differences in the final score were less than a converted try (7 points), HA has disappeared.

Applied sport science and medicine of women's rugby codes: a systematic-scoping review and consensus on future research priorities protocol

Women's rugby (rugby league, rugby union and rugby sevens) has recently grown in participation and professionalisation. There is under-representation of women-only cohorts within applied sport science and medicine research and within the women's rugby evidence base. The aims of this article are: Part 1: to undertake a systematic-scoping review of the applied sport science and medicine of women's rugby, and Part 2: to develop a consensus statement on future research priorities. This article will be designed in two parts: Part 1: a systematic-scoping review, and Part 2: a three-round Delphi consensus method. For Part 1, systematic searches of three electronic databases (PubMed (MEDLINE), Scopus, SPORTDiscus (EBSCOhost)) will be performed from the earliest record. These databases will be searched to identify any sport science and medicine themed studies within women's rugby. The Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews will be adhered to. Part 2 involves a three-round Delphi consensus method to identify future research priorities. Identified experts in women's rugby will be provided with overall findings from Part 1 to inform decision-making. Participants will then be asked to provide a list of research priority areas. Over the three rounds, priority areas achieving consensus (≥70% agreement) will be identified. This study has received institutional ethical approval. When complete, the manuscript will be submitted for publication in a peer-reviewed journal. The findings of this article will have relevance for a wide range of stakeholders in women's rugby, including policymakers and governing bodies.

Does perceived wellness influence technical-tactical match performance? A study in youth international rugby using partial least squares correlation analysis

The purpose of this study was to determine the relationship between matchday wellness status and a technical-tactical performance construct during rugby match-play. One hundred and thirty-three male rugby union players (73 forwards and 60 backs) from five under-18 national squads who participated in the under-18 Six Nations competition completed a subjective wellness questionnaire on each matchday morning. Players subjectively rated each item (sleep quality, fatigue, muscle soreness, stress and mood) on a five-point Likert scale to calculate their daily wellness status (i.e. difference between matchday and baseline perceived wellness). Technical-tactical performance during match-play was quantified by coding individual key performance indicators (e.g. number of carries, number of tackles). Partial least squares correlation analysis (PLSCA) was employed to compute the latent variables of perceived wellness status (X matrix) and technical-tactical performance (Y matrix) for each player observation (n = 271). The latent variables are a construct of each variable group, enabling higher dimensional data to be visualised more simply. Linear mixed-effect models were later conducted to assess the relationships between the latent variables. The effect of perceived wellness status on technical-tactical performance was statistically significant in forwards (p = .042), not statistically significant in backs (p = .120) and accounted for 4.9% and 1.9% variance in the technical-tactical performance construct, respectively. The findings of this study suggest that perceived wellness status can influence technical-tactical match performance, but the practical significance of these findings should be interpreted with caution given the amount of variance in technical-tactical performance accounted by the models.

Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby

Since the accelerating development of technology applied to team sports and its subsequent high amount of information available, the need for data mining leads to the use of data reduction techniques such as Principal Component Analysis (PCA). This systematic review aims to identify determinant variables in soccer, basketball and rugby using exploratory factor analysis for, training design, performance analysis and talent identification. Three electronic databases (PubMed, Web of Science, SPORTDiscus) were systematically searched and 34 studies were finally included in the qualitative synthesis. Through PCA, data sets were reduced by 75.07%, and 3.9 ± 2.53 factors were retained that explained 80 ± 0.14% of the total variance. All team sports should be analyzed or trained based on the high level of aerobic capacity combined with adequate levels of power and strength to perform repeated high-intensity actions in a very short time, which differ between team sports. Accelerations and decelerations are mainly significant in soccer, jumps and landings are crucial in basketball, and impacts are primarily identified in rugby. Besides, from these team sports, primary information about different technical/tactical variables was extracted such as (a) soccer: occupied space, ball controls, passes, and shots; (b) basketball: throws, rebounds, and turnovers; or (c) rugby: possession game pace and team formation. Regarding talent identification, both anthropometrics and some physical capacity measures are relevant in soccer and basketball. Although overall, since these variables have been identified in different investigations, further studies should perform PCA on data sets that involve variables from different dimensions (technical, tactical, conditional).

Rugby league ball carrier injuries: The relative importance of tackle characteristics during the European Super League

Rugby league carries a high injury incidence with 61% of injuries occurring at tackles. The ball carrier has a higher injury incidence than the defender, therefore understanding mechanisms occurring during injurious tackles are important. Given the dynamic, open nature of tackling, characteristics influencing tackle outcome likely encompass complex networks of dependencies. This study aims to identify important classifying characteristics of the tackle related to ball carrier injurious and non-injurious events in rugby league and identify the characteristics capability to correctly classify those events. Forty-one ball carrier injuries were identified and 205 matched non-injurious tackles were identified as controls. Each case and control were analysed retrospectively through video analysis. Random forest models were built to (1) filter tackle characteristics possessing relative importance for classifying tackles resulting in injurious/non-injurious outcomes and (2) determine sensitivity and specificity of tackle characteristics to classify injurious and non-injurious events. Six characteristics were identified to possess relative importance to classify injurious tackles. This included 'tackler twisted ball carrier's legs when legs were planted on ground', 'the tackler and ball carrier collide heads', 'the tackler used body weight to tackle ball carrier', 'the tackler has obvious control of the ball carrier' 'the tackler was approaching tackle sub-maximally' and 'tackler's arms were below shoulder level, elbows were flexed'. The study identified tackle characteristics that can be modified in attempt to reduce injury. Additional injury data are needed to establish relationship networks of characteristics and analyse specific injuries. Sensitivity and specificity results of the random forest were 0.995 and 0.525.