Limited Return to Preinjury Performance in NCAA Division I American Football Players With Hamstring Injuries

Background

Hamstring strains are common among elite athletes, but their effect on return to the same level of play in American football has been incompletely characterized.

Purpose

Data on National Collegiate Athletics Association Division I college football players with acute hamstring strains were gathered to identify the effects these injuries have on both return to play and athletic performance regarding velocity, workload, and acceleration.

Study Design

Case Series; Level of evidence, 4.

Methods

Injury data for a single Division I football team were prospectively recorded over a 4-year period. Players wore global navigation satellite system and local positioning system (GNSS/LPS) devices to record movement data in practices and games. The practice and game data were cross-referenced to evaluate players with isolated acute hamstring strains. Comparisons were made regarding players' pre- and postinjury ability to maintain high velocity (>12 mph [19.3 kph]), maximal velocity, triaxial acceleration, and inertial movement analysis (IMA). There were 58 hamstring injuries in 44 players, of which 25 injuries from 20 players had GNSS/LPS data.

Results

Players were able to return to play from all 25 injury incidences at a mean of 9.2 days. At the final mean follow-up of 425 days, only 4 players had reached preinjury function in all measurements; 12 players were able to return in 2 of the 4 metrics; and only 8 players reached their preinjury ability to maintain high velocity. For those who did not achieve this metric, there was a significant difference between pre- and postinjury values (722 vs 442 m; P = .016). A total of 14 players were able to regain their IMA. Players who returned to prior velocity or acceleration metrics did so at a mean of 163 days across all metrics.

Conclusion

While players may be able to return to play after hamstring strain, many players do not reach preinjury levels of acceleration or velocity, even after 13.5 months. Further studies are needed to confirm these findings, assess clinical relevance on imaging performance, and improve hamstring injury prevention and rehabilitation.

A Comparison of a Novel Stretchable Smart Patch for Measuring Runner’s Step Rates with Existing Measuring Technologies

A novel wearable smart patch can monitor various aspects of physical activity, including the dynamics of running, but like any new device developed for such applications, it must first be tested for validity. Here, we compare the step rate while running in place as measured by this smart patch to the corresponding values obtained utilizing ‘‘gold standard’’ MEMS accelerometers in combination with bilateral force plates equipped with HBM load cells, as well as the values provided by a three-dimensional motion capture system and the Garmin Dynamics Running Pod. The 15 healthy, physically active volunteers (age = 23 ± 3 years; body mass = 74 ± 17 kg, height = 176 ± 10 cm) completed three consecutive 20-s bouts of running in place, starting at low, followed by medium, and finally at high intensity, all self-chosen. Our major findings are that the rates of running in place provided by all four systems were valid, with the notable exception of the fast step rate as measured by the Garmin Running Pod. The lowest mean bias and LoA for these measurements at all rates were associated consistently with the smart patch.

Gradual vs. Maximal Acceleration: Their Influence on the Prescription of Maximal Speed Sprinting in Team Sport Athletes

The primary purpose of this study was to determine if a difference existed between peak speed attained when performing a sprint with maximal acceleration versus from a gradual build-up. Additionally, this investigation sought to compare the actual peak speed achieved when instructed to reach 75% and 90% of maximum speed. Field sport athletes (n = 21) performed sprints over 60 m under the experimental conditions, and the peak speed was assessed with a radar gun. The gradual build-up to maximum speed (8.30 ± 0.40 m∙s⁻¹) produced the greater peak speed (effect size = 0.3, small) than the maximum acceleration run (8.18 ± 0.40 m∙s⁻¹), and the majority of participants (62%) followed this pattern. For the sub-maximum runs, the actual mean percentage of maximum speed reached was 78 ± 6% for the 75% prescribed run and 89 ± 5% for the 90% prescription. The errors in attaining the prescribed peak speeds were large (~15%) for certain individuals, especially for the 75% trial. Sprint training for maximum speed should be performed with a gradual build-up of speed rather than a maximum acceleration. For sub-maximum interval training, the ability to attain the prescribed target peak speed can be challenging for field sport athletes, and therefore where possible, feedback on peak speeds reached should be provided after each repetition.

State-of-the-Art Methods for Skeletal Muscle Glycogen Analysis in Athletes-The Need for Novel Non-Invasive Techniques

Muscle glycogen levels have a profound impact on an athlete’s sporting performance, thus measurement is vital. Carbohydrate manipulation is a fundamental component in an athlete’s lifestyle and is a critical part of elite performance, since it can provide necessary training adaptations. This paper provides a critical review of the current invasive and non-invasive methods for measuring skeletal muscle glycogen levels. These include the gold standard muscle biopsy, histochemical analysis, magnetic resonance spectroscopy, and musculoskeletal high frequency ultrasound, as well as pursuing future application of electromagnetic sensors in the pursuit of portable non-invasive quantification of muscle glycogen. This paper will be of interest to researchers who wish to understand the current and most appropriate techniques in measuring skeletal muscle glycogen. This will have applications both in the lab and in the field by improving the accuracy of research protocols and following the physiological adaptations to exercise.

Annual improvement in fitness test performance for elite junior Australian football cohorts

OBJECTIVES

The study examined the change in fitness test performance of elite junior Australian football cohorts tested over the span of seven years.

DESIGN

Annual cross-sectional observation study.

METHODS

A total of 1714 elite junior male Australian football players were eligible for the study and completed annual late pre-season fitness testing between 2009 and 2015. The testing comprised anthropometric (height, mass, and skinfolds) and performance tests (standing vertical jump, left and right foot running vertical jumps, 5- and 20-m sprinting, agility, and shuttle run test). A linear regression analysed the performance change for each test over time for two analyses: (1) the entire cohort, and (2) a stratified analysis of 'high' (top 20% of players) and 'low' (bottom 20% of players) performers for each performance test.

RESULTS

There was a moderate (f(2)=0.20) improvement in the standing vertical jump for the entire cohort. Small (f(2)≥0.03) changes occurred for the right and left foot running vertical jumps, agility, and shuttle run, whilst trivial/small (f(2)≤0.02) changes were observed for skinfolds, 5- and 20-m sprinting for the entire cohort. The most notable difference in the stratified analysis was that the 'low' performance groups had a greater improvement in the shuttle run, and 5- and 20-m sprinting.

CONCLUSIONS

Findings indicate a small overall annual improvement in fitness test performance of elite junior cohorts over time that seems to permeate through both 'high' and 'low' performers for most tests. The results might suggest an increase in the professionalism of players and junior developmental pathways.

Wearable Performance Devices in Sports Medicine

Context:

Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine.

Evidence Acquisition:

Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerometers, and physiologic monitors in sports.

Study Design:

Clinical review.

Level of Evidence:

Level 4.

Results:

Wearable sensors provide a method of monitoring real-time physiologic and movement parameters during training and competitive sports. These parameters can be used to detect position-specific patterns in movement, design more efficient sports-specific training programs for performance optimization, and screen for potential causes of injury. More recent advances in movement sensors have improved accuracy in detecting high-acceleration movements during competitive sports.

Conclusion:

Wearable devices are valuable instruments for the improvement of sports performance. Evidence for use of these devices in professional sports is still limited. Future developments are needed to establish training protocols using data from wearable devices.

Influence of physical fitness, age, experience, and weekly training load on match performance in elite Australian football

Season long competition schedules in football create unique challenges for coaches in balancing the requirements of recovery, developing and maintaining physical fitness, and adjusting the training load before each match. The aim of this study was to investigate the influence of player characteristics (physical fitness, age, and playing experience) and weekly in-season training load on elite match performance across an Australian football season. Twenty-five players (age: 24.1 ± 3.0 years; height: 188.3 ± 7.3 cm; weight: 90.4 ± 8.3 kg) from one elite team participated in this study. Before the season, player's age, experience, height, and weight along with measures of aerobic (6-minute run) and anaerobic (6 × 40 m repeated sprints) physical fitness were recorded. Individual player training load during the season was measured using global positioning system technology for the main training session of the week. Player match performance was calculated weekly from 33 individual playing statistics. Multilevel modeling was used to investigate the relationship between weekly training load and match performance and to explore the influence of player characteristics on this relationship. Playing experience (p < 0.01) and aerobic fitness (p < 0.05) displayed positive relationships with performance, whereas player age (p < 0.01) showed a negative relationship. Most players coped well with weekly variations in training load; however, the relationship was moderated by the results of the preseason repeated sprint test (p < 0.05). The adverse effect on playing performance in selected players after a more intense training session suggests that recovery from the session may be delayed in players who exhibit a better anaerobic fitness profile.