Identification of player position in college football from performance tests and body composition components - Mann, B.; Dawes, J.; Hunter, M.; Mayhew, J.; Brechue, W. (The Journal of Strength and Conditioning Research, 2021)
American football is an extremely dynamic game that incorporates a wide range of body sizes in various specific playing positions. One method of categorizing these groups assigns them to positions requiring a high degree of mobile playing skills (SKILL), a second group of larger players has a different skill set (MID), and final a group composed of the largest players (BIG) that have yet a different skill set. What has not be determined is the degree to which fundamental performance differ across these groups. Purpose: To determine the accuracy of fundamental motor skills and body size components to assign players to one of 3 major player categories used in football. Methods: NCAA Division I football players (n = 463, age = 20.5 ± 1.2 years, height = 185.1 ± 6.4 cm, weight = 101.1 ± 18.4 kg) were measured over multiple years for 1RM free-weight squat (SQ), 40-yd sprint time (SPR), and body composition at the conclusion of winter off-season training. SQ was predicted from a 3-5RM equation and expressed as an absolute value (SQ), relative to body mass (SQ/kg), and allometrically (SQ/kg0.51). Body composition determined via dual-energy X-ray absorptiometry estimated fat-free mass (FFM), fat mass (FM), and %fat. Players were divided into fundamental playing position (BIG, n = 112; MID, n = 196; SKILL, n = 155). A validation sample (n = 339) was selected to submit to factor analysis and discriminant analysis to categorize fundamental skills and body composition. Results: Factor analysis isolated 2 components that accounted for 81% of the total variance among positions in the validation sample. The components were size-speed (weight and SPR) and strength (SQ). Discriminant analysis produced correctly identified 80% of SKILL, 68% MID, and 90% BIG. Applying the discriminant equation to the cross-validation sample (n = 124) correctly identified 57% of SKILL, 91% of MID, and 82% of BIG categories. The 43% of MID players who were misclassified had significantly greater weight, slower run times, and greater SQ than the other MID players, placing them more in the MID category. Conclusions: Discriminant components were capable of properly categorizing a major of D-I football to one of 3 fundamental playing groups. The most difficult group to estimate was the MID group, which typically contains linebackers, tightends, and strong safeties. These are often players of larger size, above average speed, and exceptional leg strength. Practical Applications: The differentiation of the physical attributes may allow a coach to determine what position to start an athlete at when coming in to college. A common recruiting practice is to bring in an athlete and have them gain weight into a larger position. For some athletes this may work well and others it shunts their athletic performance. The results from this discriminant analysis may aid coaches in determining if an athlete should move into a larger position or not.