Anthropometrics, Physical Performance, and Injury Characteristics of Youth American Football

Evaluation of the Back-in-Action test Battery In Uninjured High School American Football Players

Background

Return to sport testing is an established routine, especially for athletes who have ruptured their anterior cruciate ligament (ACL). Various tests are performed, often combined in test batteries, such as the Back-in-action (BIA) test battery. Unfortunately, pre-injury performance is often unknown, and only few athletes pass the high demands of these test batteries.

Purpose

The aim of the study was to determine the performance of under 18 American football players on the BIA to establish pre-injury sport specific benchmarks for future RTS testing and to compare these values to data from an age-matched reference group.

Methods

Fifty-three healthy male American football players underwent a functional assessment using the "Back-in-action" test battery evaluating agility, speed (Parkour-Jumps and Quick-Feet test), balance (using a PC based balance board), and power (Counter-Movement-Jump [CMJ]) as objective measures. Their results were compared with a previously tested reference group (RP) and within the american football players (AF) through three subgroups according to field playing position.

Results

Overall, the American football (AF) athletes showed lower balance scores for both legs (AF: 3.71/3.57/3.61; RP: 3.4/3.2/3.2; p<0.002) compared to the reference population (RP). CMJ height and Quick-Feet results were not statistically different (p>0.05), Parkour-Jump times (AF: 8.18/ 8.13 sec.; RP: 5.9/5.9sec.; p<0.001) were significantly slower. Power output in all CMJ's (AF: 46.86/36.94/37.36 W/kg; RP: 43.2/29.5/29 W/kg; p<0.001) was significantly higher than the RP. Passing and running game involved players (G2 & G3) showed significantly better balance scores (G2+G3: 3.36/3.27/3.33; G1: 4.22/4.06/4.10; p<0.001), higher jump height (G2&G3: 38.87/24.02/24.96 cm; G1: 32.03/19.50/18.96 cm; p<0.001) and more watts/kg (G2&G3: 48.83/37.21/37.64 W/kg; G1: 43.95/36.88/36.53 W/kg; p<0.001) compared to blocking players like Linemen (G1) and to the age matched reference population (RP).

Conclusion

Only 53% of the healthy athletes would have been cleared for sport using the BIA test criteria, which highlights the challenging passing criteria. Despite significantly greater power measurements, scores of balance and agility were poorer compared to the reference group, especially for linemen. These data may serve as sport and position specific reference for high school American football players, instead of using the non-specific reference group data.

Study design

cross-sectional study.

Level of evidence

IIb.

The impact of sport-specific physical fitness change patterns on lower limb non-contact injury risk in youth female basketball players: a pilot study based on field testing and machine learning

Background: In recent years, identifying players with injury risk through physical fitness assessment has become a hot topic in sports science research. Although practitioners have conducted many studies on the relationship between physical fitness and the likelihood of injury, the relationship between the two remains indeterminate. Consequently, this study utilized machine learning to preliminary investigate the relationship between individual physical fitness tests and injury risk, aiming to identify whether patterns of physical fitness change have an impact on injury risk. Methods: This study conducted a retrospective analysis by extracting the records of 17 young female basketball players from the sport-specific physical fitness monitoring and injury registration database in Fujian Province. Sports-specific physical fitness tests included physical performance, physiological, biochemical, and subjective perceived responses. The data for each player was standardized individually using Z-scores. Synthetic minority over-sampling techniques and edited nearest neighbor algorithms were used to sample the training set to address the negative impact of class imbalance on model performance. Feature extraction was performed on the dataset using linear discriminant analysis, and the prediction model was constructed using the cost-sensitive neural network. Results: The 10 replicate 5-fold stratified cross-validation showed that the lower limb non-contact injury prediction model based on the cost-sensitive neural network had achieved good discrimination and calibration (average Precision: 0.6360; average Recall: 0.8700; average F2-Score: 0.7980; average AUC: 0.8590; average Brier-score: 0.1020), which could be well applied in training practice. According to the attribution analysis, agility and speed were important physical attributes that affect youth female basketball players' non-contact lower limb injury risk. Specifically, there was enhance in the performance of the 1-min double under, accompanied by an increase in urinary ketone and urinary blood levels following the agility test. The 3/4 basketball court sprint performance improved, while urinary protein and RPE levels decreased after the speed test. Conclusion: The sport-specific physical fitness change pattern can impact the lower limb non-contact injury risk of young female basketball players in Fujian Province, specifically in terms of agility and speed. These findings will provide valuable insights for planning athletes' physical training programs, managing fatigue, and preventing injuries.

Descriptive Epidemiology of Injuries in Professional Speedball Athletes

CONTEXT

Speedball is an increasingly popular racquet sport played in more than 25 countries. Our objective was to describe injury incidence and patterns among Egyptian national-level speedball athletes.

DESIGN

Descriptive epidemiological.

METHODS

We conducted a survey of athletes who were registered with the Egyptian Speedball Federation during the 2018-2019 professional season. The survey inquired about injury types and athlete exposures (AEs). The response rate was 63% (100/160 athletes). Respondent ages ranged from 18 to 41 years. We analyzed demographic characteristics; number, location, and mechanism of injuries; treatment; and speedball participation time lost because of injury.

RESULTS

Of 100 respondents, 65 reported having sustained at least one injury during the season for a total of 90 injuries and a rate of 4.7 injuries per 1000 AEs (95% confidence interval, 3.7 to 5.7). More injuries occurred during practice (77%) than during competition (23%). Thirty percent of respondents reported having missed a competition because of injury. The most frequent anatomic locations of injury were the shoulder (50%; 2.4/1000 AEs), elbow (14%; 0.68/1000 AEs), and low back (9%; 0.4/1000 AEs). The most frequently cited causes of injury were increased intensity of training (40%) and lack of warming up (18%). Seventy-seven percent of injured respondents underwent treatment by a health care professional, and 9% of these respondents underwent surgery.

CONCLUSION

The shoulder was the most common anatomic location for injuries in speedball athletes. Our results suggest that attention should be directed toward sport-specific injury prevention and intervention strategies because speedball is a fast-growing sport in several countries.

Comparison of Functional Movement Screen, Star Excursion Balance Test, and Physical Fitness in Junior Athletes with Different Sports Injury Risk

Objectives

The aim of this study was to assess the relationships between functional movement screen (FMS), star excursion balance test (SEBT), agility T test, and vertical jump test scores and sports injury risk in junior athletes. We compared these assessments and the differences between groups with high and low risks of sports injury. Subjects and Methods. Eleven volleyball, 12 basketball, and 9 handball athletes were recruited. All participants followed the routine training in school sports teams. Weekly training schedules followed a similar pattern. The 32 junior athletes (age = 16.06 ± 0.21 years; height = 167.28 ± 6.32 cm; and body mass = 68.45 ± 9.67 kg) were assessed using the FMS, SEBT, agility T test, and vertical jump test in random order. The correlations of composite and individual item scores of these assessments were analyzed, and the differences between groups with high and low risks of sports injury were compared.

Results

All participants completed the study protocol. No significant differences were observed between FMS, SEBT, agility T test, and vertical jump test scores in groups with high and low risks of sports injuries. Fair and moderate-to-good correlations were observed for anterior reach maximum of SEBT and deep squat (r = 0.47, P = 0.02) as well as inline lunge (r = 0.53, P = 0.01) of FMS. The hurdle step of FMS also exhibited moderate-to-good (r = 0.52, P = 0.01) and fair (r = 0.42, P = 0.04) correlations with posterior medial and posterior lateral reach maximum of SEBT, respectively. A fair correlation was observed between posterior lateral reach maximum of SEBT and rotary stability of FMS (r = −0.23, P = 0.03). Fair and moderate-to-good correlations were identified for agility T test and maximum anterior reach in the SEBT (r = −0.42, P = 0.04) and trunk stability push-up in the FMS, respectively (r = −0.57 and P = 0.006).

Conclusions

Junior athletes with a high risk of sports injury did not exhibit differences in terms of FMS, SEBT, and physical fitness test scores. Deep squat, hurdle step, inline lunge, and rotary stability scores in the FMS were correlated with the item scores in the SEBT, which may be due to the use of similar movement patterns. Scores for anterior reach maximum in the SEBT and trunk stability push-up in the FMS were correlated with agility T test scores, suggesting a similar task requirement of trunk stability and dynamic weight shifting ability.

The Epidemiology of Injuries in Middle School Football, 2015-2017: The Advancing Healthcare Initiatives for Underserved Students Project

BACKGROUND

Although data exist on injuries in youth football leagues, there are limited recent data on injury incidence in middle school football. Updated injury incidence estimates can help drive the development of injury prevention strategies.

PURPOSE

Describe the epidemiology of injuries in middle school football during school years 2015-2016 to 2017-2018.

STUDY DESIGN

Descriptive epidemiology study.

METHODS

Data originated from 9 public middle schools in Virginia during school years 2015-2016 to 2017-2018. Certified athletic trainers collected injury and athlete-exposure (AE) data from school-sanctioned games and practices in boys', football. Injury counts and rates per 1000 AEs were calculated. Injury rate ratios with 95% CIs compared rates between games and practices.

RESULTS

Overall, 664 middle school boys', football injuries were reported, leading to an overall injury rate of 20.54 per 1000 AEs (95% CI, 18.98-22.11). The time loss injury rate (inclusive of injuries with participation restriction time ≥24 hours) was 9.28 per 1000 AEs (95% CI, 8.23-10.33). The injury rate was higher in competition than practice (36.19 vs 17.97 per 1000 AEs; injury rate ratio, 2.01; 95% CI, 1.69-2.40). Most injuries were to the head/face (competition, 20.6%; practice, 15.8%) and hand/wrist (competition, 18.8%; practice, 16.4%) and were diagnosed as contusions (competition, 30.9%; practice, 25.9%) and sprains (competition, 19.4%; practice, 12.6%). Competitions also had a large proportion of concussions (10.3%). Overall, 80.0% and 66.9% of injuries were due to contact in competition and practice, respectively; of these contact-related injuries, 62.1% and 41.6% were specifically player contact.

CONCLUSION

Injury distributions parallel those found in previous research from middle school and other sport settings. Injury rates in middle school football were higher than those reported in previous findings in high school and college. However, caution must be taken when interpreting findings in relation to other surveillance systems with varying methodologies. Still, the findings highlight the need for injury prevention strategies within middle school football, particularly as related to contact-related mechanisms.