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Andrew C. Fry, PhD, CSCS*D, FNSCA – Professor, University of Kansas

Patrick Moodie – Co-Founder & Managing Partner, Dynamic Athletics Research Institute

Eric M. Mosier, PhD, USAW – Assistant Professor , Northwest Missouri State University

Nicole Moodie – Associate Professor, Rockhurst University


The use of motion capture technology (MCT) by athletic programs is becoming more popular, but understanding of the athlete outcomes is still under studied.  With advancements in technology and screening protocols, the evaluation of test scores (novel biometrics) for determining an athletes’ ability can be rapidly performed. However, little is known about the spectrum of test performances for different types of athletes.  PURPOSE: This study examined novel biometrics produced from a MCT and profiled those results for different sports in a collegiate setting. This would give us better insight on what to expect from a specific type of athlete when using these novel biometrics.  METHODS: 1,212 division 1 athletes (±SD; Male - n=692, age=20.2±1.7 yrs., hgt.=189.5±31.3 cm, wgt.=97.2±30.6 kg; Female - n=520, age=19.6±2.1 yrs., hgt.=172.5±26.3 cm, wgt.=97.2±21.2 kg ) were screened using the Performance Motion Analysis (PMA) protocol, consisting of 19 motions.  A total of 23,028 movement files were collected.  The protocol included shoulder ranges of motions (i.e., shoulder abduction and adduction, horizonal abduction and adduction, internal and external rotation, flexion and extension). Also assessed were trunk rotation, bilateral overhead squat, unilateral squats, forward lunges, single leg balance, bilateral counter-movement vertical jump (CMVJ), unilateral CMVJs, concentric-only VJ, multiple unilateral CMVJs, and depth VJ.  A three-dimensional markerless motion capture system (MCS; DARI, Overland Park, KS) was used to analyze the kinetic and kinematic data from which 192 variables were calculated and reported in PMA Scores (Composite Score, Power Score, Functional Strength Score, and Dysfunction Score).  An overall novel biometric composite score was calculated for the athlete’s protocol (Composite Score).  Subcategories that compose the Composite Score are also represented (Power + Functional Strength – Dysfunction = Composite Score).  Descriptive statistical analysis was used to report novel biometric composition score median and 95% confidence intervals (CI) for gender-specific sports populations.  RESULTS: The composite score median and 95% CI indicates the novel biometric profile for male and female sport-specific populations (figure 1).  CONCLUSION: The sport-specific profile the composite score showcases allows for a stratification or athletic classification to better understand how MCT can be utilized in collegiate athletics settings.  PRACTICAL APPLICATION:  MCT has demonstrated application for better understanding of specific athletic movements, but lacked cross sport application.  The current investigation allows the application of MCT across multi-sport applications with better understanding and expectations for training utilization.  Further research is needed to focus on position specific traits inside a specific sport.


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