Cited by 26

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Relationship Between Body Mass, Peak Power, and Power-to-Body Mass Ratio on Sprint Velocity and Momentum in High-School Football Players

Jalilvand, Farzad, Banoocy, Norbert K., Rumpf, Michael C., Lockie, Robert G.·2019·Journal of Strength and Conditioning Research

Abstract

Jalilvand, F, Banoocy, NK, Rumpf, MC, and Lockie, RG. Relationship between body mass, peak power, and power-to-body mass ratio on sprint velocity and momentum in high-school football players. J Strength Cond Res 33(7): 1871–1877, 2019—The ability to rapidly shift one's body mass horizontally or vertically is common within American football irrespective of field position, and the capacity to generate power is a favorable physical quality. This requires analysis in high-school football players, especially considering the body mass disparities that exist in this population. Sixteen high-school players (7 backs and 9 linemen) completed the vertical jump (VJ) to determine jump height, peak anaerobic power measured in watts (PAPw), and power-to-body mass ratio (P:BM), and a 36.58-m sprint (0–4.57, 0–9.14, and 0–36.58-m intervals) to determine sprint velocity and momentum. Independent-samples t -tests ( p < 0.05) determined differences in these variables between the backs and linemen. Pearson's correlations ( r ; p < 0.05) computed relationships between body mass, VJ height, PAPw, P:BM, with 36.58-m sprint velocity and momentum on the pooled data. Linemen were heavier, and slower in the 36.58-m sprint, but had greater PAPw and sprint momentum compared with backs. Body mass exhibited negative relationships to velocity across all sprint intervals ( r = −0.55 to 0.70), and positive relationships with momentum across all intervals ( r = 0.95–0.96). The VJ correlated with sprint velocity across all intervals ( r = 0.51–0.83), but not momentum. PAPw was positively correlated with body mass and momentum across all intervals ( r = 0.77–0.85), but not velocity. There were significant correlations between P:BM with velocity ( r = 0.51–0.85) and momentum ( r = −0.53–0.62) across all intervals. Heavier high-school players could focus on improving P:BM to positively influence jumping ability and sprint velocity.

Overview

Integrity signals

Registry

Crossref · 10.1519/jsc.0000000000002808

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 37

  1. Baker, 2008, Comparison of lower body strength, power, acceleration, speed, agility, and sprint momentum to describe and compare playing rank among professional rugby league players, J Strength Cond Res, 22, 153, 10.1519/JSC.0b013e31815f9519 · DOI
  2. Barr, 2014, Long-term training-induced changes in sprinting speed and sprint momentum in elite rugby union players, J Strength Cond Res, 28, 2724, 10.1519/JSC.0000000000000364 · DOI
  3. Bennett, 2009, The impact of lower extremity mass and inertia manipulation on sprint kinematics, J Strength Cond Res, 23, 2542, 10.1519/JSC.0b013e3181b86b3d · DOI
  4. Black, 1994, Comparisons of size, strength, speed, and power in NCAA Division 1-A football players, J Strength Cond Res, 8, 80
  5. Dawes, 2015, Relationship between selected measures of power and strength and linear running speed amongst Special Weapons and Tactics police officers, J Aust Strength Cond, 23, 23
  6. Dupler, 2010, Anthropometric and performance differences among high-school football players, J Strength Cond Res, 24, 1975, 10.1519/JSC.0b013e3181e4f9ec · DOI
  7. Faigenbaum, 2009, Youth resistance training: Updated position statement paper from the National Strength and Conditioning Association, J Strength Cond Res, 23, S60, 10.1519/JSC.0b013e31819df407 · DOI · Paper page
  8. Fry, 1991, Physical performance characteristics of American collegiate football players, J Strength Cond Res, 5, 126
  9. Garstecki, 2004, Comparison of selected physical fitness and performance variables between NCAA Division I and II football players, J Strength Cond Res, 18, 292
  10. Ghigiarelli, 2011, Combine performance descriptors and predictors of recruit ranking for the top high school football recruits from 2001 to 2009: Differences between position groups, J Strength Cond Res, 25, 1193, 10.1519/JSC.0b013e318215f546 · DOI
  11. Haff, 2015, Methods of developing power with special reference to football players, Strength Cond J, 37, 2, 10.1519/SSC.0000000000000153 · DOI
  12. Hoffman, 2008, The applied physiology of American football, Int J Sports Physiol Perform, 3, 387, 10.1123/ijspp.3.3.387 · DOI
  13. Kawamori, 2014, Effects of weighted sled towing on ground reaction force during the acceleration phase of sprint running, J Sports Sci, 32, 1139, 10.1080/02640414.2014.886129 · DOI
  14. Kraemer, 1997, A series of studies-The physiological basis for strength training in American football: Fact over philosophy, J Strength Cond Res, 11, 131
  15. Lockie, 2012, Relationship between absolute and relative power with linear and change-of-direction speed in junior American football players from Australia, J Aust Strength Cond, 20, 4
  16. Lockie, 2016, Profiling of junior college football players and differences between position groups, Sports, 4, 1, 10.3390/sports4030041 · DOI
  17. Lockie, 2012, Physiological profile of national-level junior American football players in Australia, Serb J Sport Sci, 6, 127
  18. Lockie, 2017, A methodological report: Adapting the 505 change-of-direction speed test specific to American football, J Strength Cond Res, 31, 539, 10.1519/JSC.0000000000001490 · DOI
  19. Lockie, 2015, Interaction between leg muscle performance and sprint acceleration kinematics, J Hum Kinet, 49, 65, 10.1515/hukin-2015-0109 · DOI
  20. Lockie, 2011, Factors that differentiate acceleration ability in field sport athletes, J Strength Cond Res, 25, 2704, 10.1519/JSC.0b013e31820d9f17 · DOI
  21. Loturco, 2015, Vertical and horizontal jump tests are strongly associated with competitive performance in 100-m dash events, J Strength Cond Res, 29, 1966, 10.1519/JSC.0000000000000849 · DOI
  22. Martínez, 2014, Relation of anthropometric profile and performance in competition for Mexican high school football players on the offensive squad, Int J Morpho, 32, 1051, 10.4067/S0717-95022014000300049 · DOI
  23. McFarland, 2016, Relationship of two vertical jumping tests to sprint and change of direction speed among male and female collegiate soccer players, Sports, 4, 11, 10.3390/sports4010011 · DOI
  24. McGee, 2003, The National Football League combine: A reliable predictor of draft status?, J Strength Cond Res, 17, 6
  25. Nuzzo, 2011, The reliability of three devices used for measuring vertical jump height, J Strength Cond Res, 25, 2580, 10.1519/JSC.0b013e3181fee650 · DOI
  26. Peterson, 2006, The contribution of maximal force production to explosive movement among young collegiate athletes, J Strength Cond Res, 20, 867
  27. Robbins, 2012, Relationships between National Football League combine performance measures, J Strength Cond Res, 26, 226, 10.1519/JSC.0b013e31821d5e1b · DOI
  28. Sayers, 1999, Cross-validation of three jump power equations, Med Sci Sports Exerc, 31, 572, 10.1097/00005768-199904000-00013 · DOI
  29. Secora, 2004, Comparison of physical and performance characteristics of NCAA Division I football players: 1987 and 2000, J Strength Cond Res, 18, 286
  30. Sekulic, 2013, Gender-specific influences of balance, speed, and power on agility performance, J Strength Cond Res, 27, 802, 10.1519/JSC.0b013e31825c2cb0 · DOI
  31. Sierer, 2008, The National Football League combine: Performance differences between drafted and nondrafted players entering the 2004 and 2005 drafts, J Strength Cond Res, 22, 6, 10.1519/JSC.0b013e31815ef90c · DOI
  32. Speranza, 2015, Muscular strength and power correlates of tackling ability in semiprofessional rugby league players, J Strength Cond Res, 29, 2071, 10.1519/JSC.0000000000000897 · DOI
  33. Stuempfle, 2003, Body composition relates poorly to performance tests in NCAA Division III football players, J Strength Cond Res, 17, 238
  34. Vallerand, 1999, An integrative analysis of intrinsic and extrinsic motivation in sport, J Appl Sport Psychol, 11, 142, 10.1080/10413209908402956 · DOI
  35. Wellman, 2017, Quantification of accelerometer derived impacts associated with competitive games in National Collegiate Athletic Association Division I college football players, J Strength Cond Res, 31, 330, 10.1519/JSC.0000000000001506 · DOI
  36. Williford, 1994, Physical and performance characteristics of successful high school football players, Am J Sports Med, 22, 859, 10.1177/036354659402200621 · DOI
  37. Xu, 2011, Physical determinants of velocity and agility in high school football players: Differences between position groups, J Strength Cond Res, 25, S36, 10.1097/01.JSC.0000395635.63229.4c · DOI

Cited by

Sorted by citations

Metadata

Authors
Jalilvand, F., Banoocy, N. K., Rumpf, M. C., & Lockie, R. G.
Affiliations
  • Department of Kinesiology, California State University, Northridge, California;
  • School of Medical and Health Sciences, Edith Cowan University, Perth, Australia;
  • Sport Performance Research Institute New Zealand, AUT University, Auckland, New Zealand;
  • Department of Kinesiology, Center for Sport Performance, California State University, Fullerton, Fullerton
Venue
Journal of Strength and Conditioning Research
Published
2019-07
Volume
33
Issue
7
Pages
1871-1877
ISSN
1064-8011
Cited by
26
References
1
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review