Understanding the Influence of the Head Coach on Soccer Training Drills—An 8 Season Analysis

How Do Young Soccer Players Train? A 5-Year Analysis of Weekly Training Load and its Variability Between Age Groups in an Elite Youth Academy

ABSTRACT

Connolly, DR, Stolp, S, Gualtieri, A, Ferrari Bravo, D, Sassi, R, Rampinini, E, and Coutts, AJ. How do young soccer players train? A 5-year analysis of weekly training load and its variability between age groups in an elite youth academy. J Strength Cond Res 38(8): e423-e429, 2024-The aim of this study was to quantify the session rating of perceived exertion (sRPE), duration, and training load accrued across typical training weeks undertaken by youth soccer players. Differences between starters, nonstarters, and variations in training load variables were also investigated. Data were collected from 230 elite youth players in 4 age groups (U15, U16, U17, and U19) during 5 competitive seasons. Mixed models were used to describe variation between age groups and compare starters with nonstarters, with season as a fixed covariate effect. Week-to-week variation in training load was expressed as the percentage coefficient of variation. The main findings may be used to highlight a significant effect of age and playing status on training intensity, duration, and internal training load. Weekly training load increased progressively from the U15 to U17, with significant differences between each age group (p < 0.03). Lower mean weekly perceived intensity (sRPE) was noted in U15 when compared with the older age groups (4.2 vs. 4.6-4.9 arbitrary unit for U16 to U19, p < 0.001). Low weekly training load variation was observed across the different phases of the season in each age group, with the preseason exhibiting the greatest variance (3.6-6.2%). Differences in the training load are likely more attributable to changes in training duration rather than sRPE. Control of session duration seems to play an important role when aiming to control load in the academy environment, and practitioners should closely monitor the differences in duration and load being recorded between starters and nonstarters.

Three-, Four-, and Five-Day Microcycles: The Normality in Professional Football

PURPOSE

This study aimed to quantify training and match-day (MD) load during 3-, 4-, and 5-day microcycles in professional adult football, as well as to analyze the effect of the microcycle length on training load produced the day after the match (MD + 1) and the day before the match (MD - 1).

METHODS

The study involved 20 male professional football players whose external and internal loads were monitored for a whole season. The training exposure, total distance covered, high-speed-running distance, sprint distance (SD), individual SD above 80% of the individual maximum velocity (D > 80%), and the number of accelerations and decelerations were quantified, as well as rating of perceived exertion and session rating of perceived exertion training load.

RESULTS

Microcycle length affected most of the variables of interest: high-speed-running distance (F = 9.04, P < .01), SD (F = 13.90, P < .01), D > 80% (F = 20.25, P < .01), accelerations (F = 10.12, P < .01), and decelerations (F = 6.01, P < .01). There was an interaction effect between the training day and microcycle type for SD (F = 5.46, P < .01), D > 80% (F = 4.51, P < .01), accelerations (F = 2.24, P = .06), and decelerations (F = 3.91, P < .01).

CONCLUSIONS

Coaches seem to be influenced by shorter microcycles in their training proposal, preferring sessions with a reduced muscle impact during shorter microcycles. Independent of the length of the congested fixture microcycle, the daily load seems to decrease when MD approaches.

Worst Case Scenarios in Soccer Training and Competition: Analysis of Playing Position, Congested Periods, and Substitutes

Aim: To understand mean (WCSmean) and peak (WCSpeak) worst case scenarios within training and game play in male professional soccer. Methods: Thirty-one (n = 31) first team players were monitored across 37 matches and 14 MD-3 sessions. Playing status was distinguished, football drills analyzed, and performance explored in long-period: >6 days, moderate-period: 5-6 days, and congested-period: ≤4 days. Relative total distance (TD), high-speed running distance (HSRD, >19.8 km·h-1), sprint distance (SD, >25.2 km·h-1), accelerations/decelerations (A+D, >3 m·s-2), accelerations (Acc, >3 m·s-2), and decelerations (Dec, >-3 m·s-2) were measured as well as Maximum acceleration (Max Acc; m·s-2) and deceleration (Max Dec; m·s-2). Results: Analysis of variance found differences between matches and training in WCSmean for TD, HSRD, SD, and Max Dec in all positions (p < .001; partial η2 > .275). Fullbacks displayed differences between match and training in Max Acc (moderate ESs; p < .001), while center backs and central midfielders in Max Dec (large ESs; p > .05). Main effects of playing status were discovered for all metrics except Max Dec (p < .001; partial η2 > .124). Analysis showed differences between long- and congested-period for A+D and Dec (large ESs; p ≤ .05). Conclusions: Findings provide more insights into short peak intensity demands of soccer showing that the maximum high velocity action of acceleration and deceleration is not being replicated in training. Nonstarters lack maximum intensity exposure in matches (WCSpeak) increasing the gap between training and competition even higher during congested fixture periods.

Quantifying technical load and physical activity in professional soccer players during pre-season matches with IMU technology

This study aimed to record, analyze and quantify professional soccer players' technical (TL) and physical load (PL) in friendly matches to compare their records during the first and second halves and between players with different positions. Eighteen professional soccer players, 24.6 ± 2.7 years, 1.78 ± 0.3 height (m), 74.6 ± 4.5 body mass (kg), 9.8 ± 2.2 body fat (%), and 65.6 ± 2.7 maximal oxygen consumption (VO2max, ml·kg-1·min-1) were monitored during six preseason friendly matches to analyze the activity profile using technical and physical variables through inertial measurement unit (IMU). No significant differences were found between the periods for the TL and PL. Significant differences were found between specific positions: Full Back (FB: n = 4), Central Defender (CD: n = 3), Midfielder (MD: n = 4), Winger (WG: n = 4), and Forward (FW: n = 3), both the TL and PL. We conclude that the PL profile based on his playing position is independent of the development of the PL shown during friendly matches. The monitoring, quantifying, and controlling of the TL added to the PL provides a more holistic vision of soccer players in friendly matches. The relative ease IMU application technology offers an alternative with less time-cost and more significant benefits than other types of technologies applied up to now.

Physical predictors for retention and dismissal of professional soccer head coaches: an analysis of locomotor variables using logistic regression pipeline

Introduction

Soccer has enormous global popularity, increasing pressure on clubs to optimize performance. In failure, the tendency is to replace the Head coach (HC). This study aimed to check the physical effects of mid-season replacements of HCs, investigating which external load variables can predict retention or dismissal.

Methods

The data was collected in training and matches of a professional adult male soccer team during three complete seasons (2020/21-2022/2023). The sample included 6 different HCs (48.8 ± 7.4 years of age; 11.2 ± 3.9 years as a HC). The 4 weeks and 4 games before and after the replacement of HCs were analysed. External load variables were collected with Global Positioning System (GPS) devices. A logistic regression (LR) model was developed to classify the HCs' retention or dismissal. A sensitivity analysis was also conducted to determine the specific locomotive variables that could predict the likelihood of HC retention or dismissal.

Results

In competition, locomotor performance was better under the dismissed HCs, whereas the new HC had better values during training. The LR model demonstrated a good prediction accuracy of 80% with a recall and precision of 85% and 78%, respectively, amongst other model performance indicators. Meters per minute in games was the only significant variable that could serve as a potential physical marker to signal performance decline and predict the potential dismissal of an HC with an odd ratio of 32.4%.

Discussion

An in-depth analysis and further studies are needed to understand other factors' effects on HC replacement or retention.

Quantifying Exposure and Intra-Individual Reliability of High-Speed and Sprint Running During Sided-Games Training in Soccer Players: A Systematic Review and Meta-analysis

BACKGROUND

Sided games (i.e., small sided, medium sided, large sided) involve tactical, technical, physical, and psychological elements and are commonly implemented in soccer training. Although soccer sided-games research is plentiful, a meta-analytical synthesis of external load exposure during sided games is lacking.

OBJECTIVE

The objective of this systematic review and meta-analysis was to: (1) synthesize the evidence on high-speed and sprint running exposure induced by sided games in adult soccer players, (2) establish pooled estimates and intra-individual reliability for high-speed and sprint running exposure, and (3) explore the moderating effects of game format and playing constraints.

METHODS

A literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Four databases (PubMed/MEDLINE, Scopus, SPORTDiscus, Web of Science Core Collection) were systematically searched up to 25 January, 2022. Eligibility criteria were adult soccer players (population); training programs incorporating sided games (intervention); game manipulations including number of players, pitch dimension, and game orientation (comparator); and high-speed, very high-speed, and sprint relative (m[Formula: see text]min^-1) running distances and associated intra-individual reliability (outcome). Eligible study risk of bias was evaluated using RoBANS. Pooled estimates for high-speed and sprint running exposure, and their intra-individual reliability, along with the moderating effect of tracking device running velocity thresholds, pitch dimension (i.e., area per player), and game orientation (i.e. score or possession), were determined via a multi-level mixed-effects meta-analysis. Estimate uncertainty is presented as 95% compatibility intervals (CIs) with the likely range of relative distances in similar future studies determined via 95% prediction intervals.

RESULTS

A total of 104 and 7 studies met our eligibility criteria for the main and reliability analyses, respectively. The range of relative distances covered across small-sided games, medium-sided games, and large-sided games was 14.8 m[Formula: see text]min^-1 (95% CI 12.3-17.4) to 17.2 m[Formula: see text]min^-1 (95% CI 13.5-20.8) for high-speed running, 2.7 m[Formula: see text]min^-1 (95% CI 1.8-3.5) to 3.6 m[Formula: see text]min^-1 (95% CI 2.3-4.8) for very high-speed running, and 0.2 m[Formula: see text]min^-1 (95% CI 0.1-0.4) to 0.7 m[Formula: see text]min^-1 (95% CI 0.5-0.9) for sprinting. Across different game formats, 95% prediction intervals showed future exposure for high-speed, very high-speed running, and sprinting to be 0-46.5 m[Formula: see text]min^-1, 0-14.2 m[Formula: see text]min^-1, and 0-2.6 m[Formula: see text]min^-1, respectively. High-speed, very high-speed running, and sprinting showed poor reliability with a pooled coefficient of variation of 22.8% with distances being moderated by device speed thresholds, pitch dimension, and game orientation.

CONCLUSIONS

This review is the first to provide a detailed synthesis of exposure and intra-individual reliability of high-speed and sprint running during soccer sided games. Our estimates, along with the moderating influence of common programming variables such as velocity thresholds, area per player, and game orientation should be considered for informed planning of small-sided games, medium-sided games, and large-sided games soccer training.

CLINICAL TRIAL REGISTRATION

Open Science Framework available through https://osf.io/a4xr2/ .

The Maximal Intensity Period: Rationalising its Use in Team Sports Practice

Quantifying the highest intensity of competition (the maximal intensity period [MIP]) for varying durations in team sports has been used to identify training targets to inform the preparation of players. However, its usefulness has recently been questioned since it may still underestimate the training intensity required to produce specific physiological adaptations. Within this conceptual review, we aimed to: (i) describe the methods used to determine the MIP; (ii) compare the data obtained using MIP or whole-match analysis, considering the influence of different contextual factors; (iii) rationalise the use of the MIP in team sports practice and (iv) provide limitations and future directions in the area. Different methods are used to determine the MIP, with MIP values far greater than those derived from averaging across the whole match, although they could be affected by contextual factors that should be considered in practice. Additionally, while the MIP might be utilised during sport-specific drills, it is inappropriate to inform the intensity of interval-based, repeated sprint and linear speed training modes. Lastly, MIP does not consider any variable of internal load, a major limitation when informing training practice. In conclusion, practitioners should be aware of the potential use or misuse of the MIP.

The effect of mid-season coach turnover on running match performance and match outcome in professional soccer players

The aim of this research was to examine the physical match performance and match outcome before and after coach turnover in professional soccer teams compared with a control group containing coaches working continuously for 3 consecutive seasons. Analysed data included 325 performances of teams led by dismissed coaches (DC), 313 of teams led by new coaches (NC), and 580 of teams led by unchanged coaches (UnC). Variables, such as average number of collected points, total distance (TD), total distance per minute (TD/min), high-speed running (HSR), sprinting and number of high-intensity runs (NHIR), were analysed in the last 15 games of DC and 15 matches of NC. These periods were divided into 3 blocks out of 5 matches (5-match blocks). NC collected a significantly higher number of points than DC (p = 0.015), whereas average points collected by UNC were significantly greater than DC (p < 0.001 and NC (p = 0.012). TD and TD/min for DC were significantly lower (p < 0.001) compared with both NC and UnC, whereas significant differences in HSR (p = 0.003) and NHIR (p = 0.03) were identified between DC and NC. The current study reported that mid-season coach turnover may result in short-term improvement in team results and physical match performance. However, this effect disappears after a period of approximately 5 games.

Locomotor and technical characteristics of female soccer players training: exploration of differences between competition standards

OBJECTIVES

To (i) quantify the differences in locomotor and technical characteristics between different drill categories in female soccer and (ii) explore the training drill distributions between different standards of competition.

METHODS

Technical (ball touches, ball releases, high-speed ball releases) and locomotor data (total distance, high-speed running distance [>5.29 m∙s^-1]) were collected using foot-mounted inertial measurement units from 458 female soccer players from three Women's Super League (WSL; n = 76 players), eight Women's Championship (WC; n = 217) and eight WSL Academy (WSLA; n = 165) teams over a 28-week period. Data were analysed using general linear mixed effects.

RESULTS

Across all standards, the largest proportion of time was spent in technical (TEC) (WSL = 38%, WC = 28%, WSLA = 29%) and small-sided extensive games (SSGe) (WSL = 20%, WC = 31%, WSLA = 30%) drills. WSL completed more TEC and tactical (TAC) training whilst WC and WSLA players completed more SSGe and possession (POS) drills. Technical drills elicited the highest number of touches, releases and the highest total distance and high-speed activity. Position-specific drills elicited the lowest number of touches and releases and the lowest total distance. When the technical and locomotor demand of each drill were made relative to time, there were limited differences between drills, suggesting drill duration was the main moderating factor.

CONCLUSION

Findings provide novel understanding of the technical and locomotor demands of different drill categories in female soccer. These results can be used by coaches and practitioners to inform training session design.

Quantifying volume and high-speed technical actions of professional soccer players using foot-mounted inertial measurement units

AIMS

The aims of the study were two-fold: i) examine the validity and reliability of high-speed kicking actions using foot-mounted inertial measurement unit's (IMU), ii) quantify soccer players within-microcycle and inter-positional differences in both the frequency and speed of technical actions.

METHODS

During the in-season phase (25 weeks) of the UK domestic season, 21 professional soccer player ball releases, high-speed ball releases and ball release index were analysed. Pearson product-moment correlation coefficient and confidence intervals were used to determine the validity between the systems, whilst a general linear mixed model analysis approach was used to establish estimated marginal mean values for total ball releases, high-speed ball releases and ball release index.

RESULTS

Good concurrent validity was observed for ball release velocity and high-speed kicks against a high-speed camera (r2- 0.96, CI 0.93-0.98). Ball releases, high-speed ball releases and ball release index all showed main effects for fixture proximity (p>0.001), playing positions (p>0.001) and across different training categories (p>0.001). The greatest high-speed ball releases were observed on a match-day (MD)+1 (17.6 ± 11.9; CI- 16.2 to 19) and MD-2 (16.8 ± 15; CI- 14.9 to 18.7), with MD+1 exhibiting the highest number of ball releases (161.1 ± 51.2; CI- 155.0 to 167.2) and ball release index (145.5 ± 45.2; CI- 140.1 to 150.9) across all fixture proximities. Possessions (0.3 ± 0.9; CI- 0.3 to 0.4) and small-sided games (1.4 ± 1.6; CI- 1.4 to 1.5), had the lowest values for high-speed ball releases with technical (6.1 ± 7.2; CI- 5.7 to 6.6) and tactical (10.0 ± 10.5; CI- 6.9 to 13.1) drills showing the largest high-speed ball releases.

CONCLUSIONS

The present study provides novel information regarding the quantification of technical actions of professional soccer players. Insights into absolute and relative frequency and intensity of releases in different drill types, provide practitioners with valuable information on technical outputs that can be manipulated during the process of planning training programmes to produce desired outcomes. Both volume and speed of ball release actions should be measured, when monitoring the technical actions in training according to fixture proximity, drill type and player position to permit enhanced training prescription.

A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league

This study investigated differences in external training load between microcycle lengths and its variation between microcycles, players, and head coaches. Commonly used external training load variables including total-, high-speed- (5-7 m∙s-1), and sprint-distance (> 7 m∙s-1) alongside combined high acceleration and deceleration distance (> 2 m∙s-2). Which were also expressed relative to time were collected using microtechnology within a repeated measures design from 54 male rugby league players from one Super League team over four seasons. 4337 individual observations across ninety-one separate microcycles and six individual microcycle lengths (5 to 10 day) were included. Linear mixed effects models established the differences in training load between microcycle-length and the variation between-microcycles, players and head coaches. The largest magnitude of difference in training load was seen when comparing 5-day with 9-day (ES = 0.31 to 0.53) and 10-day (ES = 0.19 to 0.66) microcycles. The greatest number of differences between microcycles were observed in high- (ES = 0.3 to 0.53) and sprint-speed (ES = 0.2 to 0.42) variables. Between-microcycle variability ranged between 11% to 35% dependent on training load variable. Training load also varied between players (5-65%) and head coaches (6-20%) with most variability existing within high-speed (19-43%) and sprinting (19-65%). Overall, differences in training load between microcycle lengths exist, likely due to manipulation of session duration. Furthermore, training load varies between microcycle, player and head coach.