Quantifying the Collision Dose in Rugby League: A Systematic Review, Meta-analysis, and Critical Analysis

Naughton, Mitchell; Jones, Ben; Hendricks, Sharief; D, King; Murphy, Alexander B.; Cummins, Cloe

doi:10.1186/s40798-019-0233-9

Cited by 34 publications

(46 citation statements)

References 79 publications

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“…Rugby league includes repeated contacts (eg, tackles) 13 and close proximity interactions between players, similar to other rugby and football codes. 14 The repeated close contact interactions between participants during a match represent theoretical opportunities for transmission of SARS-CoV-2, via droplets, aerosols and fomites.…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 transmission during rugby league matches: do players become infected after participating with SARS-CoV-2 positive players?

et al. 2021

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ObjectivesTo examine the interactions between SARS-CoV-2 positive players and other players during rugby league matches and determine within-match SARS-CoV-2 transmission risk.MethodsFour Super League matches in which SARS-CoV-2 positive players were subsequently found to have participated were analysed. Players were identified as increased-risk contacts, and player interactions and proximities were analysed by video footage and global positioning system (GPS) data. The primary outcome was new positive cases of SARS-CoV-2 within 14 days of the match in increased-risk contacts and other players participating in the matches.ResultsOut of 136 total players, there were 8 SARS-CoV-2 positive players, 28 players identified as increased-risk contacts and 100 other players in the matches. Increased-risk contacts and other players were involved in 11.4±9.0 (maximum 32) and 4.0±5.2 (maximum 23) tackles, respectively. From GPS data, increased-risk contacts and other players were within 2 m of SARS-CoV-2 positive players on 10.4±18.0 (maximum 88) and 12.5±20.7 (maximum 121) occasions, totalling 65.7±137.7 (maximum 689) and 89.5±169.4 (maximum 1003) s, respectively. Within 14 days of the match, one increased-risk contact and five players returned positive SARS-CoV-2 reverse transcriptase PCR (RT-PCR) tests, and 27 increased-risk contacts and 95 other participants returned negative SARS-CoV-2 RT-PCR tests. Positive cases were most likely traced to social interactions, car sharing and wider community transmission and not linked to in-match transmission.ConclusionDespite tackle involvements and close proximity interactions with SARS-CoV-2 positive players, in-match SARS-CoV-2 transmission was not confirmed. While larger datasets are needed, these findings suggest rugby presents a lower risk of viral transmission than previously predicted.

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Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 transmission during rugby league matches: do players become infected after participating with SARS-CoV-2 positive players?

et al. 2021

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“…In these cases, high-speed running efforts and the importance of tackle success is important [ 67 ]. As a consequence of the high-frequency collisions, especially the head/face collisions, complementary training programs are essential to reduce injury incidence [ 68 , 69 ].…”

Section: Discussionmentioning

confidence: 99%

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

Pino-Ortega

Rojas-Valverde

Gómez-Carmona

et al. 2021

IJERPH

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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).

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“…( 2003 ), Faria et al. ( 2005b , 2005a ) and Phillips and Hopkins ( 2020 ), and we refer to Lucia et al. ( 2003 ) for an overview of the physiological aspects in the Tour de France.…”

Section: Related Literaturementioning

confidence: 99%

Result-based talent identification in road cycling: discovering the next Eddy Merckx

2021

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In various sports large amounts of data are nowadays collected and analyzed to help scouts with identifying talented young athletes. In contrast, the literature on result-based talent identification in road cycling is remarkably scarce. The purpose of this paper is to provide insight into the possibilities of the use of publicly available data to discover new talented Under-23 (U23) riders via statistical learning methods (linear regression and random forest techniques). At the same time, we try to find out the main determinants of success for U23 riders in their first years of professional cycling. We collect results for more than 25000 road cycling races from 2007–2018 and consider more than 2500 riders from over 80 countries. We use the data from 2007 to 2017 to train and validate our models, and use the data from 2018 to predict how well U23 riders will perform in their first three elite years. Our results reveal that past U23 race results appear to be important predictors of future cycling performance.

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Quantifying the Collision Dose in Rugby League: A Systematic Review, Meta-analysis, and Critical Analysis

Cited by 34 publications

References 79 publications

SARS-CoV-2 transmission during rugby league matches: do players become infected after participating with SARS-CoV-2 positive players?

SARS-CoV-2 transmission during rugby league matches: do players become infected after participating with SARS-CoV-2 positive players?

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

Result-based talent identification in road cycling: discovering the next Eddy Merckx

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