Injury risk factors in young soccer players detected by a multivariate survival model

Hamstring Muscle Stiffness in Athletes with and without Anterior Cruciate Ligament Reconstruction History: A Retrospective Study

Introduction: Sports requiring sprinting, jumping, and kicking tasks frequently lead to hamstring strain injuries (HSI). One of the structural risk factors of HSI is the increased passive stiffness of the hamstrings. Anterior cruciate ligament (ACL) injury history is associated with a 70% increase in the incidence of HSI, according to a recent meta-analysis. The same report recommended that future research should concentrate on the relationships between the HSI risk factors. Hence, the present study aimed to retrospectively compare changes in the passive stiffness of the hamstrings in athletes with and without ACL reconstruction history. Methods: Using ultrasound-based shear-wave elastography, the mid-belly passive muscle stiffness values of the biceps femoris long head, semimembranosus, and semitendinosus muscles were assessed and compared amongst athletes with and without a history of ACL reconstruction. Results: There were no significant differences in the biceps femoris long head (injured leg (IL): 26.19 ± 5.28 KPa, uninjured contralateral (UL): 26.16 ± 7.41 KPa, control legs (CL): 27.64 ± 5.58 KPa; IL vs. UL: p = 1; IL vs. CL: p = 1; UL vs. CL: p = 1), semimembranosus (IL: 24.35 ± 5.58 KPa, UL: 24.65 ± 8.35 KPa, CL: 22.83 ± 5.67 KPa; IL vs. UL: p = 1; IL vs. CL: p = 1; UL vs. CL, p = 1), or semitendinosus (IL: 22.45 ± 7 KPa, UL: 25.52 ± 7 KPa, CL: 22.54 ± 4.4 KPa; IL vs. UL: p = 0.487; IL vs. CL: p = 1; UL vs. CL, p = 0.291) muscle stiffness values between groups. Conclusions: The passive mid-muscle belly stiffness values of the biceps femoris long head, semitendinosus, and semimembranosus muscles did not significantly differ between previously injured and uninjured athletes; therefore, further assessment for other muscle regions of hamstrings may be necessary. To collect more comprehensive data related to the structural changes that may occur following ACL reconstructions in athletes, a future study should examine the passive stiffness of wider muscle regions from origin to insertion.

Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis

This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professional soccer players; (2) carried out for at least 2 sessions, exercises, or competitions; (3) correlated training load (TL) with non-contact injuries; (4) applied ML approaches to predict TL and non-contact injuries. TL included: IL indicators (Rating of Perceived Exertion, RPE; Session-RPE, Heart Rate, HR) and EL indicators (Global Positioning System, GPS variables); the relationship between EL and IL through index, ratio, formula; ML indicators included performance measures, predictive performance of ML methods, measure of feature importance, relevant predictors, outcome variable, predictor variable, data pre-processing, features selection, ML methods. Twenty-five studies were included. Eleven addressed the relationship between EL and IL. Five used EL/IL indexes. Five studies predicted IL indicators. Three studies investigated the association between EL and IL with IR. One study predicted IR using ML. Significant positive correlations were found between S-RPE and total distance (TD) (r = 0.73; 95% CI (0.64 to 0.82)) as well as between S-RPE and player load (PL) (r = 0.76; 95% CI (0.68 to 0.84)). Association between IL and EL and their relationship with injuries were found. RPE, S-RPE, and HR were associated with different EL indicators. A positive relationship between EL and IL indicators and IR was also observed. Moreover, new indexes or ratios (integrating EL and IL) to improve knowledge regarding TL and fitness status were also applied. ML can predict IL indicators (HR and RPE), and IR. The present systematic review was registered in PROSPERO (CRD42021245312).

FIFA 11+ Kids program effects on jump kinetics in soccer players - A randomized controlled clinical trial

This study aimed to analyse the effects of the FIFA 11+ Kids programme on jump kinetics in soccer players. Twenty-four athletes (aged 9-11 years) were randomly allocated to the following groups: 1) the FIFA 11+ Kids programme (FT, n = 12), and 2) control training (CT, n = 12). Kinetic assessments of vertical jump (VJ), drop landing (DL), and anterior jump + maximum vertical jump (AJ) were performed on a force platform before and after eight weeks of training. Post-intervention impulse peak force and maximum impulse force (VJ) were significantly greater than the baseline values in the FT group (P < 0.001). Post-intervention landing peak force values for the first and second landings (DL) were significantly greater than the baseline values in the FT group (P = 0.01 and P = 0.05, respectively). Post-intervention landing peak force in the first landing (AJ) was significantly greater than the baseline values in the FT group (P = 0.005). The FT was effective in improving the impulsion performance during VJ. However, it increased the landing forces during DL and VJ.

London International Consensus and Delphi study on hamstring injuries part 3: rehabilitation, running and return to sport

Hamstring injuries (HSIs) are the most common athletic injury in running and pivoting sports, but despite large amounts of research, injury rates have not declined in the last 2 decades. HSI often recur and many areas are lacking evidence and guidance for optimal rehabilitation. This study aimed to develop an international expert consensus for the management of HSI. A modified Delphi methodology and consensus process was used with an international expert panel, involving two rounds of online questionnaires and an intermediate round involving a consensus meeting. The initial information gathering round questionnaire was sent to 46 international experts, which comprised open-ended questions covering decision-making domains in HSI. Thematic analysis of responses outlined key domains, which were evaluated by a smaller international subgroup (n=15), comprising clinical academic sports medicine physicians, physiotherapists and orthopaedic surgeons in a consensus meeting. After group discussion around each domain, a series of consensus statements were prepared, debated and refined. A round 2 questionnaire was sent to 112 international hamstring experts to vote on these statements and determine level of agreement. Consensus threshold was set a priori at 70%. Expert response rates were 35/46 (76%) (first round), 15/35 (attendees/invitees to meeting day) and 99/112 (88.2%) for final survey round. Statements on rehabilitation reaching consensus centred around: exercise selection and dosage (78.8%-96.3% agreement), impact of the kinetic chain (95%), criteria to progress exercise (73%-92.7%), running and sprinting (83%-100%) in rehabilitation and criteria for return to sport (RTS) (78.3%-98.3%). Benchmarks for flexibility (40%) and strength (66.1%) and adjuncts to rehabilitation (68.9%) did not reach agreement. This consensus panel recommends individualised rehabilitation based on the athlete, sporting demands, involved muscle(s) and injury type and severity (89.8%). Early-stage rehab should avoid high strain loads and rates. Loading is important but with less consensus on optimum progression and dosage. This panel recommends rehabilitation progress based on capacity and symptoms, with pain thresholds dependent on activity, except pain-free criteria supported for sprinting (85.5%). Experts focus on the demands and capacity required for match play when deciding the rehabilitation end goal and timing of RTS (89.8%). The expert panellists in this study followed evidence on aspects of rehabilitation after HSI, suggesting rehabilitation prescription should be individualised, but clarified areas where evidence was lacking. Additional research is required to determine the optimal load dose, timing and criteria for HSI rehabilitation and the monitoring and testing metrics to determine safe rapid progression in rehabilitation and safe RTS. Further research would benefit optimising: prescription of running and sprinting, the application of adjuncts in rehabilitation and treatment of kinetic chain HSI factors.

Sports Injuries of a Portuguese Professional Football Team during Three Consecutive Seasons

Professional football players are exposed to high injury risk due to the physical demands of this sport. The purpose of this study was to characterize the injuries of a professional football team in the First Portuguese League over three consecutive sports seasons. Seventy-one male professional football players in the First Portuguese Football League were followed throughout the sports seasons of 2019/2020, 2020/2021, and 2021/2022. In total, 84 injuries were recorded. Each player missed an average of 16.6 days per injury. Lower limbs were massively affected by injuries across all three seasons, mainly with muscular injuries in the quadriceps and hamstrings and sprains in the tibiotarsal structure. Overall, the injury incidence was considerably higher in matches than in training. The two times of the season that proved most conducive to injuries were the months of July and January. Our results emphasize the importance of monitoring sports performance, including injury occurrence, and assisting in identifying risk factors in professional football. Designing individualized training programs and optimizing prevention and recovery protocols are crucial for maximizing this global process.

Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players

Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of injury risk based on body composition variables and selected physical fitness tests for elite football players through a sports season. The sample comprised 36 male elite football players who competed in the First Portuguese Soccer League in the 2020/2021 season. The models were calculated based on 22 independent variables that included players' information, body composition, physical fitness, and one dependent variable, the number of injuries per season. In the net elastic analysis, the variables that best predicted injury risk were sectorial positions (defensive and forward), body height, sit-and-reach performance, 1 min number of push-ups, handgrip strength, and 35 m linear speed. This study considered multiple-input single-output regression-type models. The analysis showed that the most accurate model presented in this work generates an error of RMSE = 0.591. Our approach opens a novel perspective for injury prevention and training monitorization. Nevertheless, more studies are needed to identify risk factors associated with injury prediction in elite soccer players, as this is a rising topic that requires several analyses performed in different contexts.

Adiposity as a Risk Factor for Sport Injury in Youth: A Systematic Review

OBJECTIVE

To determine whether high or low adiposity is associated with youth sport-related injury.

DATA SOURCES

Ten electronic databases were searched to identify prospective studies examining the association between adiposity [body mass index (BMI) or body fat] and a future time-loss or medical attention sport-related musculoskeletal injury or concussion in youth aged 20 years and younger. Two independent raters assessed the quality (Downs and Black criteria) and risk of bias (Joanna Briggs Institute Critical Appraisal Tool). Random-effects meta-analyses were used to calculate pooled odds ratio [95% confidence interval (CI)] of injury.

MAIN RESULTS

Of 11 424 potentially relevant records, 38 articles were included with 17 eligible for meta-analyses. In qualitative synthesis, no clear association was identified between adiposity and any sport injury; however, 16/22 studies identified high adiposity as a significant risk factor for lower-extremity injury. Meta-analyses revealed higher BMI in youth with any sport-related injury and lower BMI in youth who developed a bone stress injury (BSI) compared with noninjured controls. The pooled OR (95% CI) examining the association of BMI and injury risk (excluding bone injury) was 1.18 (95% CI: 1.03-1.34). A major source of bias in included articles was inconsistent adjustment for age, sex, and physical activity participation.

CONCLUSIONS

Level 2b evidence suggests that high BMI is associated with greater risk of youth sport injury, particularly lower-extremity injury and excluding BSI or fracture. Although pooled mean differences were low, anthropometric risk of injury seems to be dependent on type and site of injury in youth sport.

Forecasting football injuries by combining screening, monitoring and machine learning

Identifying players or circumstances associated with an increased risk of injury is fundamental for successful risk management in football. So far, time-constant and volatile risk factors are generally considered separately in either a screening (constant) or a monitoring (volatile) approach each resulting in a restricted set of explanatory variables. Consequently, improvements in predictive accuracy may be expected when screening and monitoring data are combined, especially when analysed with current machine learning (ML) techniques. This trial was designed as a prospective observational cohort study aiming to forecast non-contact time-loss injuries in male professional football (soccer). Injuries were registered according to the Fuller consensus. Gradient boosting with ROSE upsampling within a leave-one-out cross-validation was used for data analysis. The hierarchical data structure was considered throughout. Different splits of the original dataset were used to probe the robustness of results. Data of 88 players from 4 teams and 51 injuries could be analysed. The cross-validated performance of the gradient boosted model (ROC area under the curve 0.61) was promising and higher compared to models without integration of screening data. Importantly, holdout test set performance was similar (ROC area under the curve 0.62) indicating prospect of generalizability to new cases. However, the variation of predictive accuracy and feature importance with different splits of the original dataset reflects the relatively low number of events. It is concluded that ML-based injury forecasting based on the integration of screening and monitoring data is promising. However, external prospective verification and continued model development are required.

Machine Learning for Understanding and Predicting Injuries in Football

Attempts to better understand the relationship between training and competition load and injury in football are essential for helping to understand adaptation to training programmes, assessing fatigue and recovery, and minimising the risk of injury and illness. To this end, technological advancements have enabled the collection of multiple points of data for use in analysis and injury prediction. The full breadth of available data has, however, only recently begun to be explored using suitable statistical methods. Advances in automatic and interactive data analysis with the help of machine learning are now being used to better establish the intricacies of the player load and injury relationship. In this article, we examine this recent research, describing the analyses and algorithms used, reporting the key findings, and comparing model fit. To date, the vast array of variables used in analysis as proxy indicators of player load, alongside differences in approach to key aspects of data treatment-such as response to data imbalance, model fitting, and a lack of multi-season data-limit a systematic evaluation of findings and the drawing of a unified conclusion. If, however, the limitations of current studies can be addressed, machine learning has much to offer the field and could in future provide solutions to the training load and injury paradox through enhanced and systematic analysis of athlete data.

Correlation between preseason body composition and sports injury in an English Premier League professional football team

Objectives

To identify the correlation between preseason body composition and incidence coupled with injury burden throughout the season in adult male professional football players.

Methods

A retrospective case series was performed for linear regression analysis of preseason body composition variables and injury data. R2 >0.10 was deemed of adequate correlation.

Results

All 36 professional football players in the male first team of an English Premier League professional football team were recruited, with none lost to follow-up. The total and mean incidence of injuries was 83.00 and 2.31 (95% CI 1.72 to 2.89), respectively. The mean injury burden was 58.32 (95% CI 37.67 to 78.98) days missed. Simple linear regression analysis indicated no significant or adequate correlations between incidence and preseason body composition variables. Injury burden revealed non-significant adequate negative correlations to body mass (R2=0.17), body mass index (BMI) (R2=0.15), waist circumference (R2=0.17), total bone mineral density (BMD) (R2=0.11) and mean embedded structures (R2=0.10).

Conclusions

Players with decreased body mass, BMI, waist circumference, total BMD and mean embedded structures may be prone to greater injury burden. Further studies with a larger sample size that incorporates multiple football teams are warranted to investigate this.

Predictive Analytic Techniques to Identify Hidden Relationships between Training Load, Fatigue and Muscle Strains in Young Soccer Players

This study aimed to analyze different predictive analytic techniques to forecast the risk of muscle strain injuries (MSI) in youth soccer based on training load data. Twenty-two young soccer players (age: 13.5 ± 0.3 years) were recruited, and an injury surveillance system was applied to record all MSI during the season. Anthropometric data, predicted age at peak height velocity, and skeletal age were collected. The session-RPE method was daily employed to quantify internal training/match load, and monotony, strain, and cumulative load over the weeks were calculated. A countermovement jump (CMJ) test was submitted before and after each training/match to quantify players' neuromuscular fatigue. All these data were used to predict the risk of MSI through different data mining models: Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM). Among them, SVM showed the best predictive ability (area under the curve = 0.84 ± 0.05). Then, Decision tree (DT) algorithm was employed to understand the interactions identified by the SVM model. The rules extracted by DT revealed how the risk of injury could change according to players' maturity status, neuromuscular fatigue, anthropometric factors, higher workloads, and low recovery status. This approach allowed to identify MSI and the underlying risk factors.

Effect of body composition on Functional Movement Screen scores in elite youth male soccer players

BACKGROUND

The Functional Movement Screen (FMS) is a clinical assessment tool used to determine musculoskeletal dysfunctions and asymmetries in athletes.

OBJECTIVE

The aim of this study was to investigate whether FMS scores differed between elite youth male soccer players with low body fat percentage and those with normal body fat percentage and between those with and without a history of soccer injury.

METHODS

Fifty-three elite youth male soccer players were included in the study. The participants' injury histories were recorded, followed by body composition assessment and FMS tests. The participants were grouped according to body fat percentage and injury history for data analysis.

RESULTS

The mean age, weight and height of the participants were 17.11 ± 0.91 years, 68.78 ± 7.41 kg and 1.77 ± 0.57 meters, respectively. Comparisons of the groups according to body fat percentage and injury history revealed no differences in FMS scores (p> 0.05).

CONCLUSION

Lower body fat percentage did not confer an advantage or disadvantage to elite youth male soccer players in terms of FMS scores FMS scores provide limited information to predict injuries in elite youth male players.

Epidemiology of Injuries in First Division Spanish Women's Soccer Players

The epidemiology of injuries in female soccer has been studied extensively in several national leagues. Even so, data on the first division Spanish league are limited. The objective of this study was to describe the epidemiology of the first division of the Spanish Women’s Soccer League and to analyze data in relation to game position, circumstance, or the moment of injury. Fifteen teams and 123 players participated in the study. Players’ characteristics and their injuries (location, type, diagnosis, circumstance, and moment) were collected. Injuries were described by their frequencies (number and percentage) and incidence rates (IR) with 95% confidence intervals (CIs). Lower limb injuries accounted for 86.8% of total injuries. Anterior cruciate ligament (ACL) and meniscus injuries occurred in totality in non-contact circumstance (0.35/1000 h; 95% CI, 0.18 to 0.62 and 0.23/1000 h; 95% CI, 0.10 to 0.45, respectively). Match injury IRs (19.02/1000 h; 95% CI, 14.89 to 23.97) were significantly higher than training (1.70/1000 h; 95% CI, 1.27 to 2.22). As a conclusion, structures such as the ACL or meniscus are most commonly injured in the non-contact circumstance in the first division of the Spanish Women’s Soccer League. In addition, match situations involve a greater risk of injury than training, increasing the risk to the ankle and knee injuries as the season progresses.

Recalibrating the risk of hamstring strain injury (HSI): A 2020 systematic review and meta-analysis of risk factors for index and recurrent hamstring strain injury in sport

OBJECTIVE

To systematically review risk factors for hamstring strain injury (HSI).

DESIGN

Systematic review update.

DATA SOURCES

Database searches: (1) inception to 2011 (original), and (2) 2011 to December 2018 (update). Citation tracking, manual reference and ahead of press searches.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies presenting prospective data evaluating factors associated with the risk of index and/or recurrent HSI.

METHOD

Search result screening and risk of bias assessment. A best evidence synthesis for each factor and meta-analysis, where possible, to determine the association with risk of HSI.

RESULTS

The 78 studies captured 8,319 total HSIs, including 967 recurrences, in 71,324 athletes. Older age (standardised mean difference=1.6, p=0.002), any history of HSI (risk ratio (RR)=2.7, p<0.001), a recent HSI (RR=4.8, p<0.001), previous anterior cruciate ligament (ACL) injury (RR=1.7, p=0.002) and previous calf strain injury (RR=1.5, p<0.001) were significant risk factors for HSI. From the best evidence synthesis, factors relating to sports performance and match play, running and hamstring strength were most consistently associated with HSI risk. The risk of recurrent HSI is best evaluated using clinical data and not the MRI characteristics of the index injury.

SUMMARY/CONCLUSION

Older age and a history of HSI are the strongest risk factors for HSI. Future research may be directed towards exploring the interaction of risk factors and how these relationships fluctuate over time given the occurrence of index and recurrent HSI in sport is multifactorial.

Improving predictor selection for injury modelling methods in male footballers

Objectives

This objective of this study was to evaluate whether combining existing methods of elastic net for zero-inflated Poisson and zero-inflated Poisson regression methods could improve real-life applicability of injury prediction models in football.

Methods

Predictor selection and model development was conducted on a pre-existing dataset of 24 male participants from a single English football team's 2015/2016 season.

Results

The elastic net for zero-inflated Poisson penalty method was successful in shrinking the total number of predictors in the presence of high levels of multicollinearity. It was additionally identified that easily measurable data, that is, mass and body fat content, training type, duration and surface, fitness levels, normalised period of 'no-play' and time in competition could contribute to the probability of acquiring a time-loss injury. Furthermore, prolonged series of match-play and increased in-season injury reduced the probability of not sustaining an injury.

Conclusion

For predictor selection, the elastic net for zero-inflated Poisson penalised method in combination with the use of ZIP regression modelling for predicting time-loss injuries have been identified appropriate methods for improving real-life applicability of injury prediction models. These methods are more appropriate for datasets subject to multicollinearity, smaller sample sizes and zero-inflation known to affect the performance of traditional statistical methods. Further validation work is now required.

Efficacy of Injury Prevention Training Is Greater for High-Risk vs Low-Risk Elite Female Youth Soccer Players

BACKGROUND

The efficacy of robustness training for high- versus low-risk individuals within high-risk groups is currently unknown.

PURPOSE

To explore the efficacy of robustness training on injury risk factors among female youth soccer players and to examine if high-risk athletes are greater responders to such training.

STUDY DESIGN

Controlled laboratory study.

METHODS

A total of 125 elite youth female soccer players on the English FA talent pathway were randomly selected into a training group (n = 71) or a control group (n = 54). Relative leg stiffness, 2-dimensional knee valgus and knee flexion range of motion from a single-legged countermovement jump, and probability of high knee abduction moment (pKAM) risk were all determined before and after a 16-week robustness training program. For further analysis, participants in the training group were split into groups based on risk: high risk (pKAM >0.80, n = 33) and low risk (pKAM <0.55, n = 33). Magnitude-based inferences were used to explore differences between the control and intervention groups and the high- and low-risk groups.

RESULTS

Magnitude-based inferences demonstrated significant beneficial effects in the training group for knee valgus, pKAM, and leg stiffness as compared with the control group. The control group demonstrated possible worthwhile differences in knee flexion range of motion as compared with the intervention group. The high-risk group demonstrated likely/very likely worthwhile differences versus the low-risk group for all parameters.

CONCLUSION/CLINICAL RELEVANCE

Robustness training induces significant beneficial improvements in injury risk factors among female youth soccer players. The beneficial effects of this multidimensional program are greater for those classified as high risk.

Analysis of Scoring Sequences in Matches of the Portuguese Premier League

The aim of this study was to examine the sequences of the first two goals scored in soccer matches in accordance with a range of different match contexts. Data from 1506 matches played in the Portuguese Premier League during six consecutive competitive seasons (2009-10 to 2014-2015) were analysed using descriptive statistics and the chi-square test in order to verify the association between variables and a Cox regression analysis was used to predict the time the second goal was scored in function of the time of the first goal scored in the match and the scoreline. The results revealed a higher frequency of the second goals being scored in the second half of a match (58%) and in the last 5 min periods of each half. A positive association was found for home teams and score-doubling goals (58%), as well as for away teams and score-equalizing goals (56%). For home and away teams the score-doubling goal of a match was strongly and positively associated with a win outcome for home (93%) and away teams (92%), while the score-equalizing goals were associated with a draw (home and away teams: 44%) and loss outcome (home: 33% and away teams: 32%). Finally, the Cox model showed that if the first goal was scored in the second half of the match, the probability of the second goal being scored was three times higher compared to the first half.

Effective injury forecasting in soccer with GPS training data and machine learning

Injuries have a great impact on professional soccer, due to their large influence on team performance and the considerable costs of rehabilitation for players. Existing studies in the literature provide just a preliminary understanding of which factors mostly affect injury risk, while an evaluation of the potential of statistical models in forecasting injuries is still missing. In this paper, we propose a multi-dimensional approach to injury forecasting in professional soccer that is based on GPS measurements and machine learning. By using GPS tracking technology, we collect data describing the training workload of players in a professional soccer club during a season. We then construct an injury forecaster and show that it is both accurate and interpretable by providing a set of case studies of interest to soccer practitioners. Our approach opens a novel perspective on injury prevention, providing a set of simple and practical rules for evaluating and interpreting the complex relations between injury risk and training performance in professional soccer.

Training Effects of the FIFA 11+ Kids on Physical Performance in Youth Football Players: A Randomized Control Trial

OBJECTIVE

To analyze the training effects of the FIFA 11+ kids on several parameters of physical performance in male youth football players.

MATERIALS AND METHODS

Twenty-three youth players were randomized within each team into two groups (control vs. intervention). The intervention group performed the FIFA 11+ kids programme 2 times a week for 4 weeks; the control groups completed their normal warm-up routines. Thirteen physical performance measures {range of motion (hip, knee, and ankle joints), dynamic postural control (measured throughout the Y balance test), 20 m sprint time, slalom dribble with a ball, agility, vertical jumping height [counter movement jump (CMJ) and drop jump (DJ)], horizontal jump distance, accuracy when volleying a ball [measured throughout the Wall Volley test]} were assessed. All physical performance parameters were compared via magnitude-based inference analysis.

RESULTS

Significant between-group differences in favor of the FIFA 11+ players were found for dynamic postural control {anterior [mean and 90% confidence intervals (CI) = 1 cm, from -1.6 to 3.5 cm] and posteromedial (mean and 90% CI = 5.1 cm, from -1.8 to 12 cm) and posterolateral (mean and 90% CI = 4.8 cm, from 0.6 to 9.0 cm) distances}, agility run (mean and 90% CI = 0.5 s, from -0.9 to 0 s), vertical jump height [CMJ (mean and 90% CI = 3.1 cm, from 0.2 to 6.1 cm) and DJ (mean and 90% CI = 1.7 cm, from -0.5 to 3.9 cm)], and horizontal jump distance (mean and 90% CI = 2.5 cm, from -8 to 15 cm). The control groups showed better performance in 20 m sprint time (mean and 90% CI = -0.05 s, from -0.11 to 0.07) and wall volley tests (mean and 90% CI = 0.2, from -0.2 to 0.6) compared to the intervention group.

CONCLUSION

The main findings of this study suggest that just 4 weeks of implementation of the FIFA 11+ kids produces improved physical performance compared with traditional warm-up routines in youth soccer players.

Dynamic balance performance and noncontact lower extremity injury in college football players: an initial study

Background:

Field expedient screening tools that can identify individuals at an elevated risk for injury are needed to minimize time loss in American football players. Previous research has suggested that poor dynamic balance may be associated with an elevated risk for injury in athletes; however, this has yet to be examined in college football players.

Hypothesis:

To determine if dynamic balance deficits are associated with an elevated risk of injury in collegiate football players. It was hypothesized that football players with lower performance and increased asymmetry in dynamic balance would be at an elevated risk for sustaining a noncontact lower extremity injury.

Study Design:

Prospective cohort study.

Methods:

Fifty-nine collegiate American football players volunteered for this study. Demographic information, injury history, and dynamic balance testing performance were collected, and noncontact lower extremity injuries were recorded over the course of the season. Receiver operator characteristic curves were calculated based on performance on the Star Excursion Balance Test (SEBT), including composite score and asymmetry, to determine the population-specific risk cut-off point. Relative risk was then calculated based on these variables, as well as previous injury.

Results:

A cut-off point of 89.6% composite score on the SEBT optimized the sensitivity (100%) and specificity (71.7%). A college football player who scored below 89.6% was 3.5 times more likely to get injured.

Conclusion:

Poor performance on the SEBT may be related to an increased risk for sustaining a noncontact lower extremity injury over the course of a competitive American football season.

Clinical Relevance:

College football players should be screened preseason using the SEBT to identify those at an elevated risk for injury based upon dynamic balance performance to implement injury mitigation strategies to this specific subgroup of athletes.

Investigation of characteristics and risk factors of sports injuries in young soccer players: a retrospective study

Background

The participation of children and adolescents in sports has become increasingly frequent, including soccer. This growing involvement gives rise to concerns regarding the risk of sports injuries. Therefore, the aim of the present study was to describe the musculoskeletal injuries in young soccer players.

Methods

301 male soccer players with a mean age 14.67 ± 2.08 years were randomly recruited. The Referred Condition Inquiry was used to collect information on the mechanism of injury and anatomic site affected as well as personal data on the participants. The variables were analyzed based on the degree of association using Goodman’s test for contrasts between multinomial populations, with the p < 0.05.

Results

Among the 301 athletes, 24.25% reported at least one injury. With regard to height, taller individuals reported more injuries than shorter individuals (62.5% and 37.5%, respectively; p < 0.05). Injuries were more frequent among players with a training duration greater than five years (69.65%) in comparison to those who trained for a shorter duration (30.35%) (p < 0.05). The lower limbs, especially the ankle/foot and knee, were the most affected anatomic sites. Impact was the most common mechanism of injury.

Conclusion

The young practitioners of soccer analyzed had low rates of injury. The main causal mechanism was the impact. A taller height and longer exposure to training were the main risk factors for injury among young soccer players.