Lauren Christine Benson

Change of direction (COD) maneuvers in soccer create tactical advantages, but also expose the player to an increased risk of injury. COD ability is commonly tested with pre-planned drills including cuts greater than 90°. These tests do not take into consideration positional differences players encounter during games. This case-series study used principal component analysis (PCA) to examine situational differences during COD movements between playing positions in youth soccer games. For each of the four teams included (26 females, 27 males), one game was analyzed using video-analysis. Two independent reviewers identified situational patterns and a PCA was used to examine differences between playing positions. Three principal components explained 89% of the variation in the data and were categorized as the total quantity of CODs, attacking/goal-scoring and defensive reacting types of CODs. One-way ANOVA on the individual principal component (PC) scores showed significant differences (p < 0.05) between centre midfielders, goalkeepers, and centrebacks in the quantity of CODs (PC1), and between wingers and fullbacks and centre backs in attacking/goal-scoring CODs (PC2), whereas PC3 was not different between playing positions. Differences between playing positions suggest that training and testing protocols in soccer could be enhanced to better match the individual and playing position-based needs.

Dance is a popular physical activity. Increased dance training has been associated with an increased risk of injury. Given the established association between training load (TL) and injury in sport, knowledge of how TL is currently being measured in dance is critical. The objective of this study is to summarise published literature examining TL monitoring in dance settings. Six prominent databases (CINAHL, EMBASE, Medline, ProQuest, Scopus, SportDiscus) were searched and nine dance-specific journals were handsearched up to May 2022. Selected studies met inclusion criteria, where original TL data were collected from at least one dancer in a class, rehearsal and/or performance. Studies were excluded if TL was not captured in a dance class, rehearsal or performance. Two reviewers independently assessed each record for inclusion at title, abstract and full-text screening stages. Study quality was assessed using Joanna Briggs Institute Critical Appraisal Tool checklists for each study design. The 199 included studies reported on female dancers (61%), ballet genre (55%) and the professional level (31%). Dance hours were the most common tool used to measure TL (90%), followed by heart rate (20%), and portable metabolic systems (9%). The most common metric for each tool was mean weekly hours (n=381; median=9.5 hours, range=0.2–48.7 hours), mean heart rate (n=143) and mean oxygen consumption (n=93). Further research on TL is needed in dance, including a consensus on what tools and metrics are best suited for TL monitoring in dance.

The aim of this study was to assess center of mass (COM) acceleration and movement during change of direction (COD) maneuvers during a competitive soccer game to elucidate situation-specific demands of COD performance. This information can assist in developing soccer-specific tests and training methods. Fifteen elite-level female youth soccer players were tracked for one game with inertial measurement units (IMU) attached to the lower back. COD movements in combination with situational patterns were identified using high-speed video. LASSO regression was used to identify the most important predictors associated with higher vertical peak accelerations (PA_v) of the COM during COD movements. COD angle, running speed, contact, and challenge from the opposition were identified as important features related to higher PA_v. This study adds to the literature on the demands of COD performance in soccer match-play. The unique approach with game-specific situational data from female youth players provides increased insight into the game-demands of COD and agility performance. PA_v in games was higher with larger COD angles, increased running speed, or with contact when the player was challenged by the opposition. A larger study including more games is warranted to increase confidence in using these variables as a basis for training or testing agility.

This study aimed to examine the utility of inertial measurement unit (IMU) technology to identify angle, step-specific, and side-specific differences between youth soccer players with and without a history of lower limb injury during soccer-specific field tests. Thirty-two youths (mean age 16.4 years) who were elite soccer players (Females n = 13, Males n = 19) wore IMUs during pre- and postseason soccer-specific change-of-direction assessments. A response feature analysis was used to compare the change in peak resultant acceleration of the groups at a level of significance of p < 0.05. Statistical analysis revealed significant differences in change of peak resultant acceleration of right leg final foot contact in a 180° pivot turn (p = 0.012, ES = 1.0) and a 90° cut (p = 0.04, ES = 0.75) between the two groups. These data suggest that players with a history of lower limb injury might experience greater angle and side-specific change within a season in peak resultant acceleration when compared with injury-free athletes. This study demonstrates that IMUs may present a useful method to analyze youth soccer players’ change of direction movement after returning to play. These results can inform future studies investigating player monitoring and may prove to be a useful tool for coaches when designing individualized training programs in this population.

Neuromuscular training (NMT) warm-up programs effectively prevent injuries in youth, but monitoring exercise fidelity is challenging. The purpose of this study was to compare the exercise fidelity as measured via an inertial measurement unit (IMU) with direct observations of selected exercises. Youth basketball and soccer players performed single leg jumps, squat jumps, Nordic hamstring curls, and/or single leg balance exercises as part of an NMT warm-up. An IMU was placed on the lower back of each participant and the warm-up was video recorded. A physiotherapist evaluated the volume aspect of exercise fidelity (i.e., performing the prescribed number of repetitions) using the video recordings and a checklist. Algorithms were developed to count the number of repetitions from the IMU signal. The repetitions from the algorithms were compared with the physiotherapist’s evaluation, and accuracy, precision, and recall were calculated for each exercise. A total of 91 (39 female, 52 male) athletes performed at least one of the four warm-up exercises. There was an accuracy, precision, and recall of greater than 88% for all exercises. The single leg jump algorithm classified all sets correctly. IMUs may be used to quantify exercise volume for exercises that involve both impact during landing and changes in orientation during rotations.

Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.

Overuse injuries are common in basketball. Wearable technology enables the workload to be monitored in sport settings. However, workload–injury models lack a biological basis both in the metrics recorded and how workload is accumulated. We introduce a new metric for monitoring workload: weighted jump height, where each jump height is weighted to represent the expected effect of the jump magnitude on damage to the tendon. The objectives of this study were to use principal components analysis to identify distinct modes of variation in all workload metrics accumulated over 1, 2, 3, and 4 weeks and to examine differences among the modes of variation in workload metrics between participants before the injury and uninjured participants. Forty-nine youth basketball players participated in their typical basketball practices and games, and lower extremity injuries were classified as patellar or Achilles tendinopathy, other overuse, or acute. An inertial measurement unit recorded the number and height of all jumps, and session rating of perceived exertion was recorded. The previous 1-, 2-, 3-, and 4-week workloads of jump count, jump height, weighted jump height, and session rating of perceived exertion were summed for each participant-week. Principal components analysis explained the variance in the accumulated workload variables. Using the retained principal components, the difference between the workload of injured participants in the week before the injury and the mean workload of uninjured participants was described for patellar or Achilles tendinopathy, overuse lower extremity injury, and any lower extremity injury. Participants with patellar or Achilles tendinopathy and overuse lower extremity injuries had a low workload magnitude for all variables in the 1, 2, 3, and 4 weeks before injury compared with the weeks before no injury. Participants with overuse lower extremity injuries and any lower extremity injury had a high previous 1-week workload for all variables along with a low previous 3- and 4-week jump count, jump height, and weighted jump height before injury compared with the weeks before no injury. Weighted jump height represents the cumulative damage experienced by tissues due to repetitive loads. Injured youth basketball athletes had a low previous 3- and 4-week workloads coupled with a high previous 1-week workload.

Missing data can influence calculations of accumulated athlete workload. The objectives were to identify the best single imputation methods and examine workload trends using multiple imputation. External (jumps per hour) and internal (rating of perceived exertion; RPE) workload were recorded for 93 (45 females, 48 males) high school basketball players throughout a season. Recorded data were simulated as missing and imputed using ten imputation methods based on the context of the individual, team and session. Both single imputation and machine learning methods were used to impute the simulated missing data. The difference between the imputed data and the actual workload values was computed as root mean squared error (RMSE). A generalized estimating equation determined the effect of imputation method on RMSE. Multiple imputation of the original dataset, with all known and actual missing workload data, was used to examine trends in longitudinal workload data. Following multiple imputation, a Pearson correlation evaluated the longitudinal association between jump count and sRPE over the season. A single imputation method based on the specific context of the session for which data are missing (team mean) was only outperformed by methods that combine information about the session and the individual (machine learning models). There was a significant and strong association between jump count and sRPE in the original data and imputed datasets using multiple imputation. The amount and nature of the missing data should be considered when choosing a method for single imputation of workload data in youth basketball. Multiple imputation using several predictor variables in a regression model can be used for analyses where workload is accumulated across an entire season.

A high incidence of overuse knee injuries among youth basketball players may be attributed to number of jumps. Wearable technology may be an effective tool for measuring jump load compared to traditional counting methods. The purpose of this study was to validate a commercially available jump counter (VERT® Classic) in youth basketball practices and games, and to identify the characteristics (i.e., height, direction, takeoff) of jumps recorded by the VERT® Classic. 46 (19F, 27M) youth basketball players wore a VERT® Classic and were recorded on video during games and practices. The number of jumps recorded by the VERT® Classic and evaluated by video raters were compared for each jump characteristic using intraclass correlation coefficient (ICC(3,k)), mean offset, and limits of agreement. The number and percent of VERT® Classic jumps and corresponding video jumps according to timestamp were reported. VERT® Classic jumps had excellent reliability with video-counted jumps over 15 cm (ICC(3,k) = 0.958), with a mean offset of −2.4 jumps (fewer VERT® Classic) and limits of agreement −12.6 to 7.8 jumps. Pairs of corresponding jumps represented 68.0% of total video jumps and 92.0% of VERT® Classic jumps. The VERT® Classic can provide an estimate of jump load in youth basketball.

Excessive forces and/or loading rates during landing may place ballet dancers at risk for overuse injury. The ability to estimate and monitor the landing forces of ballet dancers could help to improve injury prevention and rehabilitation; however, force platforms are not conducive to testing outside of a laboratory. Fortunately, it may be possible to indirectly assess landing forces via a wearable accelerometer. The purposes of this study were to examine the relationship between impact accelerations, recorded via a pelvis-worn accelerometer, and the peak forces and loading rates during performance of a common ballet manoeuvre, and to examine if a wearable accelerometer is sensitive to fatigue-related changes in landing forces. Fifteen ballet dancers continuously performed a ballet manoeuvre until self-determined exhaustion while impact accelerations and landing forces were simultaneously recorded using an accelerometer and force platforms. We observed very strong, positive relationships between the impact accelerations and the peak forces and loading rates during the landings. In addition, the changes in impact accelerations with fatigue paralleled the changes in the peak forces and loading rates. As a result, it appears that a wearable accelerometer could be used to estimate and monitor landing forces in ballet dancers.