Periodization for success—in-season external training loads relative to competition load in American football
Bibliographic Data
| ID | 13130367 |
|---|---|
| Authors | Quincy Johnson (University of Kansas, corresponding author), Yang Yang (0000-0002-3705-7612, University of Kansas), Dimitrije Cabarkapa (0000-0001-9912-3251, University of Novi Sad), Dayton Sealey (University of Nebraska at Kearney), Shane Stock (University of Nebraska at Kearney), Dalton Gleason (University of Nebraska at Kearney), Clay Frels (University of Nebraska at Kearney), Maximilian Rink (0009-0000-8778-0182, University of Kansas), Andrew C Fry (0000-0001-8171-7684, University of Kansas) |
| Year | 2025 |
| Volume | 7 |
| Pages | 1662240-1662240 |
| Publication date | 2025-09-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Sports and Active Living (JOURNAL) |
| Journal identifiers | ISSN: 2624-9367 • E-ISSN: 2624-9367 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fspor.2025.1662240 |
| PMID | 41048626 |
| OpenAlex | W4414330095 |
| Language | EN |
| References cited | 26 |
Introduction Despite an exponential development in performance monitoring technologies, the physical performance demands of sport remain an understudied topic in scientific literature. Thus, the primary purpose of this study was to quantify and compare the training loads (TL) of a collegiate American football team between in-season practices and official games by general position group, event type, and to assess the interaction between the two. Methods Twenty-seven NCAA Division-II athletes volunteered to participate in this investigation. In-season TL during 32 practices (categorized as days before game day; GD minus) and 11 conference games were recorded using global positioning system technology. Collected data included total duration, total distance, yards traveled per minute, hard running distance, hard running efforts, 2-dimensional (2D) load, and 3-dimensional (3D) load. Results A factorial analysis of variance revealed significant main effects in TL for event type ( p < 0.001) and position groups ( p < 0.001), and an interaction effect between the two ( p < 0.001). Unique microcyclic characteristics were observed for each measure of interest. Relative to game values (100%), values for training duration (+25% to −12%; GD-4 to GD-1), yards per minute (+15% to −11%), total distance (+37% to −3%), hard running distance (+33% to −7%), hard running efforts (+33% to −12%), 2D-load (+40% to −7%), and 3D-load (+44% to −3%) were significantly greater than game values on distinct days during the week. Discussion These findings can improve the current understanding of practice demands relative to games, which may support more optimal sport-specific periodization approaches within American football
Sports Analytics and Performance · Sports injuries and prevention · Sports Performance and Training
| Citation velocity | historical |
|---|---|
| Highly cited | No |