Monitoring Training Load in American Football
by Andrew Murray, CSCS
NSCA Coach
February 2019
Vol 5, Issue 4
Monitoring training load is essential for determining if athletes are adapting positively or negatively to their training program. This article goes over the various measurement metrics and includes recommendations to monitor training load for football athletes.
Paywall block issue
This article is not configured properly for members or paid content.
isMemberOnly: {{isMemberOnly}} | isPaidContent: {{isPaidContent}}
spc: One or more parts of the product SPC is missing.
Read the full article
View the video
Login to view more
{{discountDesc}} Valid thru {{discountEnds}}
This {{ogType == 'video.other' ? 'video':'article'}} is available with a NSCA membership
or can be purchased for {{prices}}
or can be purchased. Price range: {{prices}}
Price includes membership pricing and promotions
This {{ogType == 'video.other' ? 'video':'article'}} can be purchased for {{prices}}
Price includes membership pricing and promotions
Purchase this {{ogType == 'video.other' ? 'video':'article'}}. Price range: {{prices}}
Price range includes membership pricing and promotions
This article originally appeared in NSCA Coach, a quarterly publication for NSCA Members that provides valuable takeaways for every level of strength and conditioning coach. You can find scientifically based articles specific to a wide variety of your athletes’ needs with Nutrition, Programming, and Youth columns. Read more articles from NSCA Coach »
Related Reading
References
1. Abbiss, CR, Peiffer, JJ, Meeusen, R, and Skorski, S. Role of Ratings of Perceived Exertion during Self-Paced Exercise: What are We Actually Measuring? Sports Medicine 45: 1235–1243, 2015.
2. Banister, E, Calvert, T, Savage, M, and Al, E. A systems model of training for athletic performance. Australian Journal of Sports Medicine 7: 57–61, 1975.
3. Banister, E and Calvert, TW. Planning for future performance: implications for long term training. Canadian journal of applied sport sciences Journal canadien des sciences appliquees au sport 5: 170–176, 1980.
4. Borg, G. Borg’s perceived exertion and pain scales. Human Kinetics 104 vii, 1998.
5. Bourdon, PC, Cardinale, M, Murray, A, Gastin, P, Kellmann, M, Varley, MC, et al. Monitoring Athlete Training Loads: Consensus Statement. International Journal of Sports Physiology and Performance 12: S2-161-S2-170, 2017.
6. Bowen, L, Gross, AS, Gimpel, M, and Li, F-X. Accumulated workloads and the acute:chronic workload ratio relate to injury risk in elite youth football players. British Journal of Sports Medicine 51: 452–459, 2017.
7. Busso, T, Hakkinen, K, Pakarinen, A, Kauhanen, H, Komi, PV, and Lacour, JR. Hormonal adaptations and modelled responses in elite weightlifters during 6 weeks of training. European Journal of Applied Physiology and Occupational Physiology 64: 381–386, 1992.
8. Cardinale, M, and Varley, MC. Wearable training monitoring technology: Applications, challenges and opportunities. International Journal of Sorts Physiology and Performance, 2016.
9. Christen, J, Foster, C, Porcari, JP, and Mikat, RP. Temporal robustness of the session rating of perceived exertion. International Journal of Sports Physiology and Performance 11: 1088–1093, 2016.
10. Clarke, N, Farthing, JP, Norris, SR, Arnold, BE, and Lanovaz, JL. Quantification of Training Load in Canadian Football. Journal of Strength and Conditioning Research 27: 2198–2205, 2013.
11. Colby, MJ, Dawson, B, Heasman, J, Rogalski, B, Rosenberg, M, Lester, L, et al. Pre-season workload volume and high risk periods for non-contact injury across multiple Australian Football League (AFL) seasons. Journal of Strength and Conditioning Research, 2016.
12. Coutts, AJ. In the Age of Technology, Occam’s Razor Still Applies. International Journal of Sports Physiology and Performance 9: 741–741, 2014.
13. Cross, MJ, Williams, S, Trewartha, G, Kemp, SPT, and Stokes, KA. The influence of in-season training loads on injury risk in professional rugby union. International Journal of Sports Physiology and Performance 11: 350–355, 2016.
14. Dines, JS, Tubbs, T, Fleisig, GS, Dines, DM, Altchek, DW, Dowling, B, et al. The Relationship of Throwing Arm Mechanics and Elbow Varus Torque: Within-subject Variation for Professional Baseball Pitchers Across 81,999 Throws. Orthopaedic Journal of Sports Medicine 5: 2017.
15. Drew, M, Wallis, M, and Hughes, D. Data dictionary for the National Injury and Illness Database. In: AIS Best Practice Handbook.Canberra: Australian Sports Commission, 1-9, 2014.
16. Drew, MK, Blanch, P, Purdam, C, and Gabbett, TJ. Yes, rolling averages are a good way to assess training load for injury prevention. Is there a better way? Probably, but we have not seen the evidence. British Journal of Sports Medicine 51: 618.2-619, 2017.
17. Fanchini, M, Ghielmetti, R, Coutts, AJ, Schena, F, and Impellizzeri, FM. Effect of training-session intensity distribution on session rating of perceived exertion in soccer players. International Journal of Sports Physiology and Performance 10: 426–430, 2015.
18. Foster, C. Monitoring training in athletes with reference to overtraining syndrome. Medicine and Science in Sports and Exercise 30: 1164–1168, 1998.
19. Foster, C, Florhaug, J, Franklin, J, Gottschall, L, Hrovatin, L, Parker, S, et al. A new approach to monitoring exercise training. Journal of Strength and Conditioning Research 15: 109–115, 2001.
20. Foster, C, Snyder, A, and Welsh, R. Monitoring of training, warm up, and performance in athletes. In: Overload, Performance Incompetence, and Regeneration in Sport 43–51, 1999.
21. Gabbett, TJ. The training—injury prevention paradox: should athletes be training smarter and harder? British Journal of Sports Medicine 50: 273–280, 2016.
22. Gabbett, TJ, Nassis, GP, Oetter, E, Pretorius, J, Johnston, N, Medina, D, et al. The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data. British Journal of Sports Medicine 51: 1451–1452, 2017.
23. Halson, SL. Monitoring Training Load to Understand Fatigue in Athletes. Sports Medicine 44: 139–147, 2014.
24. Hulin, BT, Gabbett, TJ, Lawson, DW, Caputi, P, and Sampson, JA. The acute:chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players. British Journal of Sports Medicine 50: 231–236, 2016.
25. Lolli, L, Batterham, AM, Hawkins, R, Kelly, DM, Strudwick, AJ, Thorpe, R, et al. Mathematical coupling causes spurious correlation within the conventional acute-to-chronic workload ratio calculations. British Journal of Sports Medicine, 2017.
26. Lyman, S, Fleisig, GS, Andrews, JR, and Osinski, ED. Effect of Pitch Type, Pitch Count, and Pitching Mechanics on Risk of Elbow and Shoulder Pain in Youth Baseball Pitchers. The American Journal of Sports Medicine 30: 463–468, 2002.
27. Lyman, S, Fleisig, GS, Waterbor, JW, Funkhouser, EM, Pulley, L, Andrews, JR, et al. Longitudinal study of elbow and shoulder pain in youth baseball pitchers. Medicine and Science in Sports and Exercise 33: 1803–1810, 2001.
28. Malone, JJ, Lovell, R, Varley, MC, and Coutts, AJ. Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport. International Journal of Sports Physiology and Performance 32: 1–30, 2016.
29. De Martini, JK, Martschinske, JL, Casa, DJ, Lopez, RM, Ganio, MS, Walz, SM, et al. Physical Demands of National Collegiate Athletic Association Division I Football Players During Preseason Training in the Heat. Journal of Strength and Conditioning Research 25: 2935–2943, 2011.
30. Mclaren, SJ, Graham, M, Spears, IR, and Weston, M. The sensitivity of differential ratings of perceived exertion as measures of internal load. International Journal of Sports Physiology and Performance 11: 404–406, 2016.
31. Murray, NB, Gabbett, TJ, Townshend, AD, Hulin, BT, and McLellan, CP. Individual and combined effects of acute and chronic running loads on injury risk in elite Australian footballers. Scandinavian Journal of Medicine and Science in Sports 27: 990–998, 2017.
32. Noble, B, Borg, G, Jacobs, I, Ceci, R, and Kaiser, P. A categoryratio perceived exertion scale: relationship to blood and muscle lactates and heart rate. Medicine and Science in Sports Exercise 15: 523–528, 1983.
33. Raysmith, BP, and Drew, MK. Performance success or failure is influenced by weeks lost to injury and illness in elite Australian track and field athletes: A 5-year prospective study. Journal of Science and Medicine in Sport 19: 778–783, 2015.
34. Scott, BR, Duthie, GM, Thornton, HR, Dascombe, BJ, and Scott, BR. Training monitoring for resistance exercise: Theory and applications. Sports Medicine 46: 687–698, 2016.
35. Uchida, MC, Teixeira, LFM, Godoi, VJ, Marchetti, PH, Conte, M, Coutts, AJ, et al. Does the timing of measurement alter session-RPE in boxers? Journal of Sports Science and Medicine 13: 59–65, 2014.
36. Wallace, LK, Slattery, KM, and Coutts, AJ. The Ecological Validity and Application of the Session-RPE Method for Quantifying Training Loads in Swimming. Journal of Strength and Conditioning Research 23: 33–38, 2009.
37. Wellman, AD, Coad, SC, Flynn, PJ, Siam, TK, and McLellan, CP. A Comparison of Pre-Season and In-Season Practice and Game Loads in NCAA Division I Football Players. Journal of Strength and Conditioning Research, 2017.
38. Wellman, AD, Coad, SC, Goulet, GC, Coffey, VG, and McLellan, CP. Quantification of Accelerometer Derived Impacts Associated With Competitive Games in NCAA Division I College Football Players. Journal of Strength and Conditioning Research, 2016.
39. Wellman, AD, Coad, SC, Goulet, GC, and McLellan, CP. Quantification of Competitive Game Demands of NCAA Division I College Football Players Using Global Positioning Systems. Journal of Strength and Conditioning Research 30: 11–19, 2016.
40. Weston, M, Siegler, J, Bahnert, A, McBrien, J, and Lovell, R. The application of differential ratings of perceived exertion to Australian Football League matches. Journal of Science and Medicine in Sport 18: 704–708, 2015.
41. Whiteley, R, Farooq, A, and Johnson, A. Development of a data-based interval kicking program for preparation and rehabilitation purposes in professional football. Science and Medicine in Football 1: 107–116, 2017.
42. Wilkerson, GB, Gupta, A, Allen, JR, Keith, CM, and Colston, MA. Utilization of practice session average inertial load to quantify college football injury risk. Journal of Strength and Conditioning Research 30: 2369–2374, 2016.
