Influence of Forefoot Bending Stiffness on Metatarsophalangeal Joint Kinematics, Kinetics and Performance of American Football Players
Bibliographic record
Abstract
Hyperextension of the metatarsophalangeal (MTP) joint results in a commonAmerican football injury known as ’turf-toe’; the tearing of the plantar capsuleligament1.One variable that is possibly related to turf-toe is the longitudinal bendingstiffness of the forefoot of football cleats2. It is speculated that cleats with low forefootbending stiffness allow the MTP joint to extend too much during play, resulting indangerous strain on the plantar capsule-ligament. The purpose of this study wastherefore to investigate if increasing forefoot bending stiffness of American footballcleats can help protect the MTP joint from hyperextension without negatively affectingperformance. Ten football players performed four maximal effort football movements(5-10-5 agility drill, 5 m sprint, broad and vertical jumps) on artificial turf installedin the laboratory. Each movement was performed three times in three different cleatconditions that varied only in forefoot bending stiffness; low (12.7 N/mm), moderate(23.8 N/mm), and high (42.4 N/mm). The artificial turf installation allowed for thecollection of 3-D kinetic and kinematic data necessary to analyze MTP joint angles andmoments. The performance of each movement was quantified. The sprint start andthe broad jump were associated with the largest MTP extension angles (approximately33 deg and 43 deg, respectively). For both of these movements, peak MTP extensionangle was decreased with the stiffer shoes. This was not true for the agility drill orvertical jump; however, the peak MTP joint extension angles for these movements wererelatively small (<18 deg). The MTP moment data are currently being analyzed. For allfour movements, increasing forefoot stiffness did not negatively affect performance.The results of this study thus far indicate that increasing forefoot bending stiffness inAmerican football cleats may be a viable way to help protect the foot from turf-toewithout compromising performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".