Longitudinal development of match‐running performance in elite male youth soccer players

Saward, Chris; Morris, John G.; Nevill, Mary E.; Nevill, Alan M.; Sunderland, Caroline

doi:10.1111/sms.12534

Cited by 46 publications

(73 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The emphasis on running-based performances for retention in both groups is likely related to the observation that match-running performance requirements (e.g. total and sprinting distance and peak game speed) typically increase in subsequent age groups following retention from U14 and U16 groups 56,62 . Furthermore, sprinting is an important action during decisive moments within football, such as reaching a ball before an opponent to score or prevent a goal 63 .…”

Section: Discussionmentioning

confidence: 99%

The influence of birth quartile, maturation, anthropometry and physical performances on player retention: Observations from an elite football academy

Patel

Nevill

Smith

et al. 2020

International Journal of Sports Science & Coaching

View full text Add to dashboard Cite

Understanding the factors that influence player retention within elite youth football can be used to enhance current practices. This study investigated an English Category 1 academy to determine if birth quartile, somatic maturity, anthropometric and physical performance characteristics are associated with player retention across the developmental pathway. Birth dates of 355 elite players from U11 to U21 groups were categorised into birth quartiles and logistic regression (odds ratio) analysis was used to determine differences in retention. Multilevel modelling compared somatic maturity, anthropometry, countermovement jump, sprint time (10 and 30 m), agility T-test, Yo-Yo Intermittent Recovery Level 1 or 2 performance between retained and dropout players. Logistic regression (odds ratio) analysis revealed no significant differences between birth quartiles for the likelihood of being retained across age groups. Multilevel modelling revealed that retained players were typically older, advanced in maturity, and superior in body size and physical performances compared to dropouts, with small to medium effect sizes typically observed. This study indicates that within a highly selective cohort of young football players, somatic maturity, anthropometric and physical performance characteristics, but not birth quartile, distinguish individuals that are subsequently retained or dropout in an age group dependent manner. Youth football organisations should seek to implement multidisciplinary and dynamic talent selection and retention strategies in order to prevent the inappropriate discrimination and loss of talented young players.

show abstract

Section: Discussionmentioning

confidence: 99%

The influence of birth quartile, maturation, anthropometry and physical performances on player retention: Observations from an elite football academy

Patel

Nevill

Smith

et al. 2020

International Journal of Sports Science & Coaching

View full text Add to dashboard Cite

show abstract

“…The mean age for the youngest group identified was 7.9 years [20], and the oldest group included 20-year-old players [57]. The majority of evaluations were from the European continent (62% of the total): England (14%) [13,15,19,26,33,44,47], Italy (10%) [20,24,37,57,66], Denmark [38,54,67], Portugal [43,62,65], Poland [23,55,64], Spain [56,61], San Marino [39,40], Norway [31,59], Turkey [29], Croatia [50] and Austria [49]. Other investigations were conducted in Asia, particularly in Qatar (18%) [12, 14, 17, 18, 41, 42, [35], Castellano et al [36], with permission Strict rules applied to Q2 (no information = 0 point; only age/age group was informed = 1 point; maturity offset also measured = 2 points); Q3 (0-1 item described = 0 point; 2-3 items described = 1 point; 4-5 items described = 2 points); and Q8 (description of mean, standard deviation and null hypothesis significance test [p-value] = 1 point; also included effect size/magnitude-based inferences = 2 points)…”

Section: Methodological Qualitymentioning

confidence: 99%

“…The main study objectives identified were primarily to characterize general game demands (22%) [12,14,15,23,24,26,27,29,43,48,64] and to compare the running performance between playing positions (20%) [12,14,18,19,23,27,48,62,65,66], age groups (26%) [12-18, 20, 26, 27, 60, 66, 67] and match halves/periods (36%) [12, 14, 16, 20, 23, 24, 29, 31, 32, 37-40, 45, 48, 56, 57, 64]. Further studies also examined the influence of biological maturity [38,51,60], playing standards [33,38,48,54] and retained versus released players [15,19,26] and compared match running performances between game formats [37,54,61] and between specific training regimens [63]. Approximately one-third of all the studies evaluated relationships between the variables of match running performance and (1) anthropometric measures (e.g., height, body weight, and skinfolds) [50,60], (2) physiological markers [45,57] [71])…”

Section: Study Objectivesmentioning

confidence: 99%

“…This is reflected by a notable shift in the body of knowledge over the current decade compared with 10 years ago, when a review showed a lack of information on match play running performance in youth soccer players [4]. While several further reviews have collated and appraised the TMA literature, none have solely examined younger populations (e.g., Mohr et al [5], Sarmento and colleagues [6,10], Lago-Peñas [7], Carling et al [8], Reilly et al [9], Taylor et al [11]) despite a plethora of original investigations comparing performance across different age groups [12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Match Running Performance in Young Soccer Players: A Systematic Review

et al. 2019

View full text Add to dashboard Cite

Background To date, athletic performance has been extensively assessed in youth soccer players through laboratory and field testing. Only recently has running performance via time-motion analysis been assessed during match play. Match running data are often useful in a practical context to aid game understanding and decision making regarding training content and prescriptions. A plethora of previous reviews have collated and appraised the literature on time-motion analysis in professional senior players, but none have solely examined youth players. Objective The aim of the present systematic review was to provide a critical appraisal and summary of the original research articles that have evaluated match running performance in young male soccer players. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement, literature searches were performed in four databases: PubMed, ISI Web of Science, SPORTDiscus and SciELO. We used the following descriptors: soccer, football, young, youth, junior, physical performance, running performance, match running performance, movement patterns, time-motion analysis, distances covered, activity profile, work rate, match analysis, and match performance. Articles were included only if they were original articles written in the English language, studied populations of male children and/or adolescents (aged ≤ 20 years), were published/ahead of print on or before 31 December 2017 and showed at least one outcome measure regarding match running performance, such as total distance covered, peak game speed or indicators of activities performed at established speed thresholds. Results A total of 5801 records were found. After duplicates were removed and exclusion and inclusion criteria applied, 50 articles were included (n = 2615 participants). Their outcome measures were extracted and findings were synthesized. The majority of the reviewed papers covered the European continent (62%) and used global positioning systems (GPS) (64%). Measurement error of the tools used to obtain position data and running metrics was systematically overlooked among the studies. The main aims of studies were to examine differences across playing positions (20%), age groups (26%) and match halves (36%). Consistent findings pointed to the existence of positional role and age effects on match running output (using fixed running speed thresholds), but there was no clear consensus about reductions in activity over the course of match play. Congested schedules negatively affected players' running performance. While over 32% of all studies assessed the relationships between match running performance and physical capacity, biochemical markers and body composition, ~ 70% of these did not account for playing position. Conclusions This review collated scientific evidence that can aid soccer conditioning professionals in understanding external match loads across youth categories. Coaches working with youth development programs should consider that data derived from a given po...

show abstract

“…For example, in the research that has examined youth and female populations there has been little justification provided for the speed zones selected, except that the thresholds were lowered to reflect the lower locomotor performance capacities of younger 44 and female cohorts. 45 One approach to has been to use mean cohort-specific physical fitness (ie, anaerobic threshold 46,47 ) or performance characteristics such as maximal sprint speed 48,49 from normative data sets to anchor player-independent (arbitrary) speed thresholds. The advantage of this approach is that the locomotor profile of the activity will be representative for the cohort, however, this will be limited by frequent changes in speed zones owing to squad composition and seasonal variations in physical fitness, precluding longitudinal analysis of locomotor trends.…”

Section: Speed Thresholdsmentioning

confidence: 99%

Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport

Malone¹,

Lovell²,

Varley³

et al. 2017

International Journal of Sports Physiology and Performance

442

475

View full text Add to dashboard Cite

Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance. Keywords: microtechnology, athlete tracking, method, MEMS, time-motion analysisGlobal positioning system (GPS) is a satellite navigation network that provides location and time information of tracking devices. Initially developed for military purposes, this system now has much wider application, including its use in athlete tracking and load quantification. GPS satellites orbit the Earth and send precise time information (from an atomic clock) to the GPS receivers (at the speed of light) to determine the duration of signal transit. 1 A minimum of four satellites are required to determine the position of the GPS receiver trigonometrically. Commercial GPS systems are now commonly used in individual-and team-sports at all levels. The development and subsequent acceptance of microtechnology in sport has led to the integration of other micro inertial sensors within GPS devices, such as triaxial accelerometers, magnetometers, and gyroscopes; collectively termed as micro electrical mechanical systems (MEMS). Thus, GPS and MEMS technology provides practitioners with a wide array of data that can be used to assess athlete physical loading and activity profile.The use of GPS in sport allows practitioners to evaluate athletic training programs, and researchers to better investigate applied research questi...

show abstract

Longitudinal development of match‐running performance in elite male youth soccer players

Abstract: Although retained players covered more low-speed distance than released players, further study of the actions comprising low-speed distance during match-play is warranted to better understand factors differentiating retained and released players.

Cited by 46 publications

References 24 publications

The influence of birth quartile, maturation, anthropometry and physical performances on player retention: Observations from an elite football academy

The influence of birth quartile, maturation, anthropometry and physical performances on player retention: Observations from an elite football academy

Match Running Performance in Young Soccer Players: A Systematic Review

Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport

Contact Info

Product

Resources

About