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Football

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Countermovement Jump Standards in Rugby League: What is a "Good" Performance?

Journal of strength and conditioning research
McMahon, JJ, Lake, JP, Dos'Santos, T, Jones, PA, Thomasson, ML, and Comfort, P. Countermovement jump standards in rugby league: what is a "good" performance? J Strength Cond Res 36(6): 1691-1698, 2022-The countermovement jump (CMJ) is considered an i...

The use of technical-tactical and physical performance indicators to classify between levels of match-play in elite rugby league.

Science & medicine in football
This study aimed to identify which physical and technical-tactical performance indicators (PI) can classify between levels of rugby league match-play. Data were collected from 46 European Super League (ESL) and 36 under-19 Academy (Academy) level mat...

Relationship between training load and recovery in collegiate American football players during pre-season training.

Science & medicine in football
: The purpose of this study was to examine the relationship between training load and next-day recovery in collegiate American football (AF) players during pre-season.: Seventeen athletes (Linemen, n = 6; Non-linemen, n = 11) participated in the 14-d...

Keeping it 100: Social Media and Self-Presentation in College Football Recruiting.

Big data
Social media provides a platform for individuals to craft personal brands and influence their perception by others, including potential employers. Yet there remains a need for more research investigating the relationship between individuals' online i...

Motion Sensors-Based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-Field Activities in Rugby Players.

Sensors (Basel, Switzerland)
Anterior cruciate ligament (ACL) injuries are common among athletes. Despite a successful return to sport (RTS) for most of the injured athletes, a significant proportion do not return to competitive levels, and thus RTS post ACL reconstruction still...

Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact.

Journal of neurotrauma
Head injury models are notoriously time consuming and resource demanding in simulations, which prevents routine application. Here, we extend a convolutional neural network (CNN) to instantly estimate element-wise distribution of peak maximum principa...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning.

Sensors (Basel, Switzerland)
The applicability of sensor-based human activity recognition in sports has been repeatedly shown for laboratory settings. However, the transferability to real-world scenarios cannot be granted due to limitations on data and evaluation methods. On the...

Rapid Estimation of Entire Brain Strain Using Deep Learning Models.

IEEE transactions on bio-medical engineering
OBJECTIVE: Many recent studies suggest that brain deformation resulting from head impacts are linked to the corresponding clinical outcome, such as mild traumatic brain injury (mTBI). Even if several finite element (FE) head models have been develope...

Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...