Pub Date : 2021-02-19DOI: 10.1080/24733938.2021.1879393
Susanne Ellens, Daniel Hodges, Sean McCullagh, J. Malone, M. Varley
ABSTRACT This study assessed the interchangeability between 10-Hz multi-GNSS GPS devices (Vector®) and two optical tracking systems (TRACAB® and Second Spectrum®). The agreement between data from the optical tracking systems when processed with manufacturer and GPS-filtered software was also assessed. Thirty players competing in the English Premier League were monitored using three different tracking systems across five matches. To determine the interchangeability between systems, player movement variables including, total distance, high-speed running distance (19.8–25.2 km·h−1), sprinting distance (>25.2 km·h−1), efforts >19.8 km·h−1 and maximal speed were compared. Equations were formed using linear regression and linear mixed-effects models to allow interchangeability of player movement variables between systems. Over half of the variance of most interchangeability equations were explained and associated with very strong positive correlations (r > 0.72). Small to huge differences were found between systems for most player movement variables. Data of optical tracking systems had decreased values in speed variables >19.8 km·h−1 when processed through GPS software. This study provides equations for practitioners to interchange player movement variables between TRACAB, Second Spectrum and Vector GPS systems with reduced error. This will enable practitioners to combine and share data captured with different tracking systems to analyse and improve their training.
{"title":"Interchangeability of player movement variables from different athlete tracking systems in professional soccer","authors":"Susanne Ellens, Daniel Hodges, Sean McCullagh, J. Malone, M. Varley","doi":"10.1080/24733938.2021.1879393","DOIUrl":"https://doi.org/10.1080/24733938.2021.1879393","url":null,"abstract":"ABSTRACT This study assessed the interchangeability between 10-Hz multi-GNSS GPS devices (Vector®) and two optical tracking systems (TRACAB® and Second Spectrum®). The agreement between data from the optical tracking systems when processed with manufacturer and GPS-filtered software was also assessed. Thirty players competing in the English Premier League were monitored using three different tracking systems across five matches. To determine the interchangeability between systems, player movement variables including, total distance, high-speed running distance (19.8–25.2 km·h−1), sprinting distance (>25.2 km·h−1), efforts >19.8 km·h−1 and maximal speed were compared. Equations were formed using linear regression and linear mixed-effects models to allow interchangeability of player movement variables between systems. Over half of the variance of most interchangeability equations were explained and associated with very strong positive correlations (r > 0.72). Small to huge differences were found between systems for most player movement variables. Data of optical tracking systems had decreased values in speed variables >19.8 km·h−1 when processed through GPS software. This study provides equations for practitioners to interchange player movement variables between TRACAB, Second Spectrum and Vector GPS systems with reduced error. This will enable practitioners to combine and share data captured with different tracking systems to analyse and improve their training.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2021.1879393","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45793804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1080/24733938.2021.1876243
D. Read, Sean Williams, Hugh H K Fullagar, J. Weakley
ABSTRACT 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.
{"title":"The effects of travel on performance: a 13-year analysis of the National Rugby League (NRL) competition","authors":"D. Read, Sean Williams, Hugh H K Fullagar, J. Weakley","doi":"10.1080/24733938.2021.1876243","DOIUrl":"https://doi.org/10.1080/24733938.2021.1876243","url":null,"abstract":"ABSTRACT 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.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2021.1876243","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44170204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-03DOI: 10.1080/24733938.2020.1869811
G. Praça, A. Andrade, S. Bredt, F. Moura, Pedro Emílio Drumond Moreira
ABSTRACT Background This study compared the physical, physiological, and spatiotemporal responses of soccer athletes in small-sided games (SSG) in two experimental conditions: progression to the target rule (PG), in which they should take the ball to the opponent’s endline to score points, and SSG with regular rules (RG), in which they should score goals to win the game. Methods Twenty U-20 athletes played both SSG formats. The SSG were played as four 4-minute bouts with four minutes of passive recovery in two consecutive days. Heart rate, physical (distances and accelerations), and positional data (length, width, and spatial exploration) were collected by a 10 hz GPS device and compared between the protocols using a MANOVA with Bonferroni’s correction for multiple comparisons. Results Results showed that the RG condition demanded more spatial exploration eliciting greater occupation of the pitch width. There were higher mean and maximum heart rates and greater low-to-moderate distances and accelerations in the RG, while the PG rule increased the distances covered at the highest speed and acceleration zones. Conclusions The progression to the target rule should be adopted to emphasize players’ ability to use the width during the offensive phase. Additionally, the PG rule should also be used to emphasize the development of speed and acceleration skills.
{"title":"Progression to the target vs. regular rules in Soccer small-sided Games","authors":"G. Praça, A. Andrade, S. Bredt, F. Moura, Pedro Emílio Drumond Moreira","doi":"10.1080/24733938.2020.1869811","DOIUrl":"https://doi.org/10.1080/24733938.2020.1869811","url":null,"abstract":"ABSTRACT Background This study compared the physical, physiological, and spatiotemporal responses of soccer athletes in small-sided games (SSG) in two experimental conditions: progression to the target rule (PG), in which they should take the ball to the opponent’s endline to score points, and SSG with regular rules (RG), in which they should score goals to win the game. Methods Twenty U-20 athletes played both SSG formats. The SSG were played as four 4-minute bouts with four minutes of passive recovery in two consecutive days. Heart rate, physical (distances and accelerations), and positional data (length, width, and spatial exploration) were collected by a 10 hz GPS device and compared between the protocols using a MANOVA with Bonferroni’s correction for multiple comparisons. Results Results showed that the RG condition demanded more spatial exploration eliciting greater occupation of the pitch width. There were higher mean and maximum heart rates and greater low-to-moderate distances and accelerations in the RG, while the PG rule increased the distances covered at the highest speed and acceleration zones. Conclusions The progression to the target rule should be adopted to emphasize players’ ability to use the width during the offensive phase. Additionally, the PG rule should also be used to emphasize the development of speed and acceleration skills.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2021-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2020.1869811","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44370397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-24DOI: 10.1080/24733938.2021.1922739
D. Borg, Robert Nguyen, Nicholas J. Tierney
ABSTRACT Methods A survey of 136 articles published in 2019 (sampled at random) was conducted to determine whether a statement about missing data was included. Results The proportion of studies reporting on missing data was low, at 11.0% (95% confidence interval = 6.3% to 17.5%). Recommendations We recommend that researchers describe the number and percentage of missing values, including when there are no missing values. Exploratory analysis should be conducted to explore missing values, and visualisations describing missingness overall should be provided in the paper, or at least in supplementary materials. Missing values should almost always be imputed, and imputation methods should be explored to ensure they are appropriately representative. Researchers should consider these recommendations and pay greater attention to missing data and its influence on research results.
{"title":"Missing data: current practice in football research and recommendations for improvement","authors":"D. Borg, Robert Nguyen, Nicholas J. Tierney","doi":"10.1080/24733938.2021.1922739","DOIUrl":"https://doi.org/10.1080/24733938.2021.1922739","url":null,"abstract":"ABSTRACT Methods A survey of 136 articles published in 2019 (sampled at random) was conducted to determine whether a statement about missing data was included. Results The proportion of studies reporting on missing data was low, at 11.0% (95% confidence interval = 6.3% to 17.5%). Recommendations We recommend that researchers describe the number and percentage of missing values, including when there are no missing values. Exploratory analysis should be conducted to explore missing values, and visualisations describing missingness overall should be provided in the paper, or at least in supplementary materials. Missing values should almost always be imputed, and imputation methods should be explored to ensure they are appropriately representative. Researchers should consider these recommendations and pay greater attention to missing data and its influence on research results.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2021.1922739","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43095723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1080/24733938.2020.1854842
P. Gamble, L. Chia, Sian V. Allen
ABSTRACT The ongoing advances and prevalence of technology in football is spurring a more prominent role for technology and data in driving decisions and practice. Sports science practitioners naturally play an integral part in the adoption of these technologies and are among the most enthusiastic proponents of a data-driven approach that promotes objective metrics and seeks to minimise or eliminate subjectivity. With the speed of these developments, there are a number of pitfalls that have been overlooked. In this commentary we describe the pervasive forces driving the adoption of technology solutions and critically examine the logic underpinning the present drive for metrics-based practice in football. In addition to highlighting some important gaps in what we are presently able to capture, we uncover some common flaws in how we implement new technology and use data. We propose that there is a fundamental need to reframe how we are seeking to employ data and more specifically make the necessary switch from being data-driven to data-informed. We propose some solutions to assist practitioners in being purposeful in their use of these tools and leverage the benefits of technology and data in a way that better supports decision-making and complements coaching practice.
{"title":"The illogic of being data-driven: reasserting control and restoring balance in our relationship with data and technology in football","authors":"P. Gamble, L. Chia, Sian V. Allen","doi":"10.1080/24733938.2020.1854842","DOIUrl":"https://doi.org/10.1080/24733938.2020.1854842","url":null,"abstract":"ABSTRACT The ongoing advances and prevalence of technology in football is spurring a more prominent role for technology and data in driving decisions and practice. Sports science practitioners naturally play an integral part in the adoption of these technologies and are among the most enthusiastic proponents of a data-driven approach that promotes objective metrics and seeks to minimise or eliminate subjectivity. With the speed of these developments, there are a number of pitfalls that have been overlooked. In this commentary we describe the pervasive forces driving the adoption of technology solutions and critically examine the logic underpinning the present drive for metrics-based practice in football. In addition to highlighting some important gaps in what we are presently able to capture, we uncover some common flaws in how we implement new technology and use data. We propose that there is a fundamental need to reframe how we are seeking to employ data and more specifically make the necessary switch from being data-driven to data-informed. We propose some solutions to assist practitioners in being purposeful in their use of these tools and leverage the benefits of technology and data in a way that better supports decision-making and complements coaching practice.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2020.1854842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42606765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1080/24733938.2020.1828615
R. Julian, D. Sargent
Since the FIFA Women’s World Cup in 2019, there has been increased media attention on the menstrual cycle and how it may contribute to overall football performance and success. The menstrual cycle ...
{"title":"Periodisation: tailoring training based on the menstrual cycle may work in theory but can they be used in practice?","authors":"R. Julian, D. Sargent","doi":"10.1080/24733938.2020.1828615","DOIUrl":"https://doi.org/10.1080/24733938.2020.1828615","url":null,"abstract":"Since the FIFA Women’s World Cup in 2019, there has been increased media attention on the menstrual cycle and how it may contribute to overall football performance and success. The menstrual cycle ...","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2020.1828615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47076835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/24733938.2019.1694167
Gordon Rennie, N. Dalton-Barron, S. McLaren, D. Weaving, Richard Hunwicks, C. Barnes, S. Emmonds, Barry G. Frost, B. Jones
ABSTRACT Purpose Understanding differences in locomotor and collision characteristics between phases of play can help rugby league coaches develop training prescription. There are no data currently available describing these differences at the elite international level. The aim of our study was to determine the differences in average speed (m∙min−1), high-speed running (>5.5 m∙s−1) per minute and collision frequencies per minute (n∙min−1) between attack and defence during the 2017 Rugby League World Cup (RLWC). Methods: Microtechnology data were collected from 24 male professional rugby league players from the same international squad across six matches of the RLWC. Data were then subject to exclusion criteria and stratified into forwards (n = 9) and backs (n = 7) before being analysed with linear mixed-effects models. Results: When comparing attack with defence, forwards and backs had substantially slower average speeds (effect size [ES]; ±90% confidence limits: −2.31; ±0.31 and −1.17; ±0.25) and substantially greater high-speed distance per minute (1.61; ±0.59 and 4.41; ±1.19). Forwards completed substantially more collisions per minute when defending (2.75; ±0.32) whilst backs completed substantially more when attacking (0.63; ±0.70). There was greater within- and between-player variability for collision frequency (coefficient of variation [CV] range; 25–28%) and high-speed distance (18–33%) per minute when compared to average speed (6–12%). Conclusions: There are distinct differences in locomotor and collision characteristics when attacking and defending during international rugby league match-play, yet the variability of high-speed running and collisions per minute is large. These data may be useful to plan or evaluate training practices.
{"title":"Locomotor and collision characteristics by phases of play during the 2017 rugby league World Cup","authors":"Gordon Rennie, N. Dalton-Barron, S. McLaren, D. Weaving, Richard Hunwicks, C. Barnes, S. Emmonds, Barry G. Frost, B. Jones","doi":"10.1080/24733938.2019.1694167","DOIUrl":"https://doi.org/10.1080/24733938.2019.1694167","url":null,"abstract":"ABSTRACT Purpose Understanding differences in locomotor and collision characteristics between phases of play can help rugby league coaches develop training prescription. There are no data currently available describing these differences at the elite international level. The aim of our study was to determine the differences in average speed (m∙min−1), high-speed running (>5.5 m∙s−1) per minute and collision frequencies per minute (n∙min−1) between attack and defence during the 2017 Rugby League World Cup (RLWC). Methods: Microtechnology data were collected from 24 male professional rugby league players from the same international squad across six matches of the RLWC. Data were then subject to exclusion criteria and stratified into forwards (n = 9) and backs (n = 7) before being analysed with linear mixed-effects models. Results: When comparing attack with defence, forwards and backs had substantially slower average speeds (effect size [ES]; ±90% confidence limits: −2.31; ±0.31 and −1.17; ±0.25) and substantially greater high-speed distance per minute (1.61; ±0.59 and 4.41; ±1.19). Forwards completed substantially more collisions per minute when defending (2.75; ±0.32) whilst backs completed substantially more when attacking (0.63; ±0.70). There was greater within- and between-player variability for collision frequency (coefficient of variation [CV] range; 25–28%) and high-speed distance (18–33%) per minute when compared to average speed (6–12%). Conclusions: There are distinct differences in locomotor and collision characteristics when attacking and defending during international rugby league match-play, yet the variability of high-speed running and collisions per minute is large. These data may be useful to plan or evaluate training practices.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2019.1694167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43959431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/24733938.2019.1679872
Shane Mangan, Kieran Collins, Con Burns, C. O'Neill
ABSTRACT Introduction The current research examines the positional technical and running performance of sub-elite Gaelic football match-play and compares technical and running performance between Division 1 and Division 2 teams. Methods Sixty eight sub-elite Gaelic football players from two teams were monitored via global positioning system (GPS) microtechnology (GPEXE LT 18 Hz, Exelio, Udine, Italy) and a video camera across 30 competitive matches (n = 336). Comparisons between teams and playing positions were examined for selected technical and running performance variables. Results Playing position had large effects on several variables including number of possessions (ES = 0.18), number of shots (ES = 0.45), total m per minute (ES = 0.403), average speed (ES = 0.40), number of power events (ES = 0.3) and recovery time between power events (ES = 0.31). Playing standard had trivial to small effects on all technical performance variables (ES ≤ 0.47) and trivial to small effects (ES ≤ 0.48) on all running performance variables. Conclusion The current study demonstrates that there are distinct positional demands in sub-elite Gaelic football. The findings of this research also demonstrate that there is little difference in the technical and running performance of Division 1 and Division 2 sub-elite teams.
{"title":"The positional technical and running performance of sub-elite Gaelic football","authors":"Shane Mangan, Kieran Collins, Con Burns, C. O'Neill","doi":"10.1080/24733938.2019.1679872","DOIUrl":"https://doi.org/10.1080/24733938.2019.1679872","url":null,"abstract":"ABSTRACT Introduction The current research examines the positional technical and running performance of sub-elite Gaelic football match-play and compares technical and running performance between Division 1 and Division 2 teams. Methods Sixty eight sub-elite Gaelic football players from two teams were monitored via global positioning system (GPS) microtechnology (GPEXE LT 18 Hz, Exelio, Udine, Italy) and a video camera across 30 competitive matches (n = 336). Comparisons between teams and playing positions were examined for selected technical and running performance variables. Results Playing position had large effects on several variables including number of possessions (ES = 0.18), number of shots (ES = 0.45), total m per minute (ES = 0.403), average speed (ES = 0.40), number of power events (ES = 0.3) and recovery time between power events (ES = 0.31). Playing standard had trivial to small effects on all technical performance variables (ES ≤ 0.47) and trivial to small effects (ES ≤ 0.48) on all running performance variables. Conclusion The current study demonstrates that there are distinct positional demands in sub-elite Gaelic football. The findings of this research also demonstrate that there is little difference in the technical and running performance of Division 1 and Division 2 sub-elite teams.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2019.1679872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46582756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-18DOI: 10.1080/24733938.2020.1780468
R. Wilson, N. Smith, B. Bedo, R. Aquino, F. Moura, P. Santiago
ABSTRACT Team sports such as soccer require individuals to play specific team roles, and success in each role is likely to be associated with a certain combination of traits. Despite this, scientific protocols for talent identification do not consider the diversity of roles played by individual players in a team. Here, we aimed to identify those players suited to the maintenance of possession by testing each individual’s sprinting, dribbling, passing, athleticism, and fitness, and showing how these traits were related to success in a small-sided possession game (4 vs 3). Passing and dribbling performance but not athleticism were the best predictors of game success. On average, 79.4 ± 8.0% of passes were successful, and those players that made a higher number of successful passes were significantly more likely to receive/possess the ball (r = 0.91; P < 0.0001). Passing success in games was best predicted by performance in dribbling and passing tests but not sprinting, fitness, or running anaerobic sprint test (F2,23 = 20.74; adjusted r2 = 0.61; P < 0.001). By identifying those traits associated with other game-specific activities, one could further improve talent identification protocols that reflect the diversity of player-types and help design individual-specific training regimes.
{"title":"Technical skill not athleticism predicts an individual’s ability to maintain possession in small-sided soccer games","authors":"R. Wilson, N. Smith, B. Bedo, R. Aquino, F. Moura, P. Santiago","doi":"10.1080/24733938.2020.1780468","DOIUrl":"https://doi.org/10.1080/24733938.2020.1780468","url":null,"abstract":"ABSTRACT Team sports such as soccer require individuals to play specific team roles, and success in each role is likely to be associated with a certain combination of traits. Despite this, scientific protocols for talent identification do not consider the diversity of roles played by individual players in a team. Here, we aimed to identify those players suited to the maintenance of possession by testing each individual’s sprinting, dribbling, passing, athleticism, and fitness, and showing how these traits were related to success in a small-sided possession game (4 vs 3). Passing and dribbling performance but not athleticism were the best predictors of game success. On average, 79.4 ± 8.0% of passes were successful, and those players that made a higher number of successful passes were significantly more likely to receive/possess the ball (r = 0.91; P < 0.0001). Passing success in games was best predicted by performance in dribbling and passing tests but not sprinting, fitness, or running anaerobic sprint test (F2,23 = 20.74; adjusted r2 = 0.61; P < 0.001). By identifying those traits associated with other game-specific activities, one could further improve talent identification protocols that reflect the diversity of player-types and help design individual-specific training regimes.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2020.1780468","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45132092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-04DOI: 10.1080/24733938.2020.1775436
F. Impellizzeri, M. Franchi, F. Sarto, T. Meyer, A. Coutts
Some authors of this editorial have recently published a call for awareness about the health consequences (e.g. increased injury risk) of home confinement in sport programming (Sarto et al. 2020). ...
{"title":"Sharing information is probably more helpful than providing generic training recommendations on return to play after COVID-19 home confinement","authors":"F. Impellizzeri, M. Franchi, F. Sarto, T. Meyer, A. Coutts","doi":"10.1080/24733938.2020.1775436","DOIUrl":"https://doi.org/10.1080/24733938.2020.1775436","url":null,"abstract":"Some authors of this editorial have recently published a call for awareness about the health consequences (e.g. increased injury risk) of home confinement in sport programming (Sarto et al. 2020). ...","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2020.1775436","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47528331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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