As a sport, field lacrosse requires seamless transitions between acceleration and deceleration. Unfortunately, linear displacement variables at a constant speed underestimate the energy demand in team sports, as they fail to account for the additional energy expended during acceleration and deceleration. In order to address these additional energy costs and offer a more precise measure of an athlete's workload, the metric called metabolic equivalent distance (MED) was developed. The purpose of the study was to assess the differences in MED across game quarters and athlete positions among female collegiate lacrosse players and determine potential relationships between MED and other workload variables. Seventeen female collegiate lacrosse players wore global positioning systems units, and data were collected over the course of 17 games. Performance variables were analyzed per minute played (min PT) and included: MED (m), total distance (m), accelerations (count), decelerations (count), total sprints (count), metabolic peak power (J), metabolic energy cost (J/kg/m), and equivalent distance index (%). No difference was found between athlete position. Performance variables did not differ between game quarters, except for playing time (p < .001). Athlete playing time was reduced in the 3rd and 4th quarters compared to quarter 1 (p < .001). MED showed a perfect correlation with total distance and metabolic energy cost (r = 1; p < .001) and a near-perfect correlation with accelerations and total sprints (r = .93; p < .001). Decelerations exhibited a strong correlation with MED (r = .86; p < .001). MED was moderately correlated with metabolic peak power (r = .34; p < .001); whereas equivalent distance index displayed a small correlation (r = .15; p = .02). Athletes exhibited a consistent output in metabolic workload variables across position and game per minute of play. MED could serve as a surrogate workload variable to better understand the athlete’s energy expenditure during high-intensity training and game play.
Published in | American Journal of Sports Science (Volume 12, Issue 2) |
DOI | 10.11648/j.ajss.20241202.12 |
Page(s) | 20-27 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Field Lacrosse, Acceleration, Deceleration, Energy Expenditure, Metabolic Power, Equivalent Distance
2.1. Study Design and Participants
2.2. Data Collection
Quarter 1 | Quarter 2 | Quarter 3 | Quarter 4 | Game | ||
---|---|---|---|---|---|---|
Playing Time (min) | Attack | 16.7 ± 8.2 | 16.2 ± 8.1 | 14.0 ± 6.8 | 14.5 ± 6.1 | |
Midfielder | 11.7 ± 6.5 | 11.2 ± 4.5 | 10.9 ± 5.4 | 10.6 ± 6.0 | ||
Defense | 22.9 ± 2.7 | 18.9 ± 6.0 | 17.6 ± 3.1 | 17.6 ± 3.3 | ||
Combined | 15.7 ± 7.7 | 14.6 ± 6.8 | 13.4 ± 6.0 † | 13.4 ± 6.0 † | 58.0 ± 26.2 * | |
Total Distance (m/min PT) | Attack | 76.4 ±15.3 | 87.0 ± 21.7 | 77.6 ± 15.7 | 90.0 ± 27.6 | |
Midfielder | 90.3 ±24.0 | 100.6 ± 27.7 | 89.5 ± 28.2 | 94.1 ± 26.5 | ||
Defense | 81.3 ±9.6 | 93.8 ± 12.2 | 85.0 ± 4.5 | 82.3 ± 14.1 | ||
Combined | 83.0 ± 18.9 | 93.8 ± 22.9 | 83.8 ± 20.6 | 90.3 ± 24.3 | 135.0 ± 65.5 | |
MED (m/min PT) | Attack | 90.9 ± 19.0 | 92.5 ± 10.9 | 90.2 ± 8.2 | 103.3 ± 23.8 | |
Midfielder | 118.5 ± 33.6 | 115.7 ± 24.1 | 112.1 ± 24.8 | 115.3 ± 27.3 | ||
Defense | 95.7 ± 11.3 | 102.4 ± 17.4 | 98.6 ± 4.0 | 105.3 ± 8.2 | ||
Combined | 103.1 ± 27.5 | 103.8 ± 20.5 | 100.7 ± 19.1 | 108.6 ± 23.1 | 142.5 ± 41.3 | |
Equivalent Distance Index (%) | Attack | 16.0 ± 0.1 | 16.0 ± 0.1 | 15.9 ± 0.1 | 15.8 ± 0.2 | |
Midfielder | 15.9 ± 0.1 | 15.9 ± 0.1 | 15.6 ± 0.7 | 15.7 ± 0.7 | ||
Defense | 16.0 ± 0.1 | 16.0 ± 0.1 | 16.0 ± 0.0 | 16.0 ± 0.1 | ||
Combined | 15.95 ± 0.18 | 15.94 ± 0.09 | 15.81 ± 0.44 | 15.79 ± 0.47 | 15.84 ± 0.30 | |
High-Intensity Acceleration (num/min PT) | Attack | 1.4 ± 0.3 | 1.6 ± 0.6 | 1.3 ± 0.4 | 1.5 ± 0.7 | |
Midfielder | 1.6 ± 0.6 | 1.7 ± 0.4 | 1.4 ± 0.5 | 1.4 ± 0.6 | ||
Defense | 1.6 ± 0.2 | 1.7 ± 0.5 | 1.4 ± 0.1 | 1.2 ± 0.1 | ||
Combined | 1.5 ± 0.4 | 1.7 ± 0.5 | 1.4 ± 0.4 | 1.4 ± 0.6 | 2.2 ± 1.3 | |
High-Intensity Deceleration (num/min PT) | Attack | 0.5 ± 0.2 | 0.5 ± 0.2 | 0.4 ± 0.1 | 0.5 ± 0.2 | |
Midfielder | 0.5 ± 0.2 | 0.5 ± 0.2 | 0.5 ± 0.2 | 0.4 ± 0.2 | ||
Defense | 0.4 ± 0.0 | 0.5 ± 0.2 | 0.4 ± 0.1 | 0.3 ± 0.1 | ||
Metabolic Cost (J/kg/m) | Attack | 6.5 ± 1.4 | 6.6 ± 1.7 | 6.5 ± 0.6 | 7.4 ± 1.2 | |
Midfielder | 7.8 ± 2.1 | 7.7 ± 1.5 | 7.4 ± 1.5 | 7.6 ± 1.7 | ||
Defense | 7.4 ± 1.2 | 7.2 ± 0.6 | 7.6 ± 0.7 | 8.2 ± 1.6 | ||
Combined | 7.2 ± 1.8 | 7.2 ± 1.2 | 7.0 ± 1.1 | 7.6 ± 1.8 | 10.0 ± 3.0 | |
Metabolic Power Peak (W/kg) | Attack | 2.1 ± 1.1 | 2.3 ± 1.2 | 2.5 ± 1.1 | 2.8 ± 1.5 | |
Midfielder | 2.8 ± 1.2 | 3.2 ± 0.7 | 3.3 ± 0.6 | 3.3 ± 1.1 | ||
Defense | 1.6 ± 0.1 | 2.3 ± 0.9 | 2.2 ± 0.2 | 2.4 ± 0.5 | ||
Combined | 2.3 ± 1.1 | 2.7 ± 1.0 | 2.8 ± 0.9 | 2.9 ± 1.2 | 1.2 ± 0.9 | |
High-Intensity Sprints (num/min pt) | Attack | 0.24 ± 0.21 | 0.20 ± 0.14 | 0.19 ± 0.13 | 0.20 ± 0.14 | |
Midfielder | 0.17 ± 0.10 | 0.16 ± 0.05 | 0.18 ± 0.08 | 0.15 ± 0.08 | ||
Defense | 0.10 ± 0.02 | 0.13 ± 0.04 | 0.10 ± 0.07 | 0.08 ± 0.06 | ||
Combined | 0.18 ± 0.15 | 0.17 ± 0.10 | 0.17 ± 0.10 | 0.16 ± 0.11 | 0.24 ± 0.18 |
[1] |
C. S. W. Lacrosse, "Historic World Lacrosse Women's Championship concludes after 11 days". Available from:
https://worldlacrosse.sport/article/historic-world-lacrosse-championship-concludes/ [Accessed March 17, 2022]. |
[2] |
I. N. F. o. S. H. S. Associations, "2021-22 High School Athletics Participation Survey". Available from:
https://www.nfhs.org/media/5989280/2021-22_participation_survey.pdf no. [Accessed March 17, 2024]. |
[3] |
National Collegiate Athletic Association, "NCAA Sports Sponsorship and Participation Rates Database" Available from:
https://www.ncaa.org/sports/2018/10/10/ncaa-sports-sponsorship-and-participation-rates-database.aspx [Accessed March 17,2024]. |
[4] | E. A. Enemark-Miller, J. G. Seegmiller, and S. R. Rana, "Physiological profile of women's Lacrosse players," The Journal of Strength & Conditioning Research, vol. 23, no. 1, pp. 39-43, 2009, |
[5] | M. Hamlet, M. Frick, and J. Bunn, "High-speed running density in collegiate women’s lacrosse," Res. Sports Med., vol. 29, no. 4, pp. 386-394, 2021, |
[6] | N. F. Devine, E. J. Hegedus, A.-D. Nguyen, K. R. Ford, and J. B. Taylor, "External match load in women's collegiate lacrosse," The Journal of Strength & Conditioning Research, vol. 36, no. 2, pp. 503-507, 2022, |
[7] | R. C. Rosenberg, B. J. Myers, and J. A. Bunn, "Sprint and distance zone analysis by position of Division I women’s lacrosse," Journal of Sport and Human Performance, vol. 9, no. 2, pp. 51-57, 2021. |
[8] | T. Polglaze, B. Dawson, and P. Peeling, "Gold standard or fool’s gold? The efficacy of displacement variables as indicators of energy expenditure in team sports," Sports Med., vol. 46, no. pp. 657-670, 2016, |
[9] | L. Bynum, R. L. Snarr, B. J. Myers, and J. A. Bunn, "Assessment of relationships between external load metrics and game performance in women’s lacrosse," International Journal of Exercise Science, vol. 15, no. 6, pp. 488, 2022 |
[10] | P. Di Prampero, S. Fusi, L. Sepulcri, J.-B. Morin, A. Belli, and G. Antonutto, "Sprint running: a new energetic approach," J. Exp. Biol., vol. 208, no. 14, pp. 2809-2816, 2005, |
[11] | J. D. Vescovi, and D. H. Frayne, "Motion characteristics of division I college field hockey: Female Athletes in Motion (FAiM) study," International Journal of Sports Physiology and Performance, vol. 10, no. 4, pp. 476-481, 2015, |
[12] | T. Polglaze, B. Dawson, A. Buttfield, and P. Peeling, "Metabolic power and energy expenditure in an international men’s hockey tournament," J. Sports Sci., vol. 36, no. 2, pp. 140-148, 2018, |
[13] | A. Thornton, B. J. Myers, and J. A. Bunn, "Comparison of in vs. out of conference game demands in collegiate division I women’s lacrosse," J Athl Enhanc, vol. 10, no. 5, pp. 1-4, 2021. |
[14] | K. L. Alphin, O. M. Sisson, B. L. Hudgins, C. D. Noonan, and J. A. Bunn, "Accuracy assessment of a GPS device for maximum sprint speed," International Journal of Exercise Science, vol. 13, no. 4, pp. 273, 2020. |
[15] | S. Malone, D. Collins, A. McRobert, J. Morton, and D. Doran. Accuracy and reliability of VXsport global positioning system in intermittent activity. In Proceedings of the Proceedings of the 19th Annual Congress of the European College of Sport Science, 2014. |
[16] | J. A. Bunn, B. J. Myers, and M. K. Reagor, "An evaluation of training load measures for drills in women’s collegiate lacrosse," International Journal of Sports Physiology and Performance, vol. 16, no. 6, pp. 841-848, 2021, |
[17] | J. A. Bunn, M. Reago, and B. J. Myers, "An evaluation of internal and external workload metrics in games in women’s collegiate lacrosse," The Journal of Sport and Exercise Science, vol. 6, no. 1, pp. 9-15, 2018, |
[18] | J. Cohen. Statistical Power Analysis for the Behavioral Sciences. Second Edition. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. |
[19] | J. M. Bland, and D. G. Altman, "Calculating correlation coefficients with repeated observations: Part 2—Correlation between subjects," Bmj, vol. 310, no. 6980, pp. 633, 1995, |
[20] | S. P. Hills, and D. J. Rogerson, "Associatons between self-reported well-being and neuromuscular performance during a professional rugby union season," The Journal of Strength & Conditioning Research, vol. 32, no. 9, pp. 2498-2509, 2018, |
[21] | D. M. Kelly, A. J. Strudwick, G. Atkinson, B. Drust, and W. Gregson, "The within-participant correlation between perception of effort and heart rate-based estimations of training load in elite soccer players," J. Sports Sci., vol. 34, no. 14, pp. 1328-1332, 2016, |
[22] | W. Hopkins, S. Marshall, A. Batterham, and J. Hanin, "Progressive statistics for studies in sports medicine and exercise science," Medicine+ Science in Sports+ Exercise, vol. 41, no. 1, pp. 3, 2009, |
[23] | A. Thornton, B. Neville, and J. Bunn, "Evaluation of athlete load and relationship between equation variables in division I women’s lacrosse: Athlete Load," Journal of Sport and Human Performance, vol. 12, no. 1, pp. 1-7, 2024. |
APA Style
Symons, B., Bunn, J. (2024). Metabolic Equivalent Distance Across Game Quarters and Athlete Position in Female Collegiate Lacrosse Players. American Journal of Sports Science, 12(2), 20-27. https://doi.org/10.11648/j.ajss.20241202.12
ACS Style
Symons, B.; Bunn, J. Metabolic Equivalent Distance Across Game Quarters and Athlete Position in Female Collegiate Lacrosse Players. Am. J. Sports Sci. 2024, 12(2), 20-27. doi: 10.11648/j.ajss.20241202.12
AMA Style
Symons B, Bunn J. Metabolic Equivalent Distance Across Game Quarters and Athlete Position in Female Collegiate Lacrosse Players. Am J Sports Sci. 2024;12(2):20-27. doi: 10.11648/j.ajss.20241202.12
@article{10.11648/j.ajss.20241202.12, author = {Brock Symons and Jennifer Bunn}, title = {Metabolic Equivalent Distance Across Game Quarters and Athlete Position in Female Collegiate Lacrosse Players }, journal = {American Journal of Sports Science}, volume = {12}, number = {2}, pages = {20-27}, doi = {10.11648/j.ajss.20241202.12}, url = {https://doi.org/10.11648/j.ajss.20241202.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajss.20241202.12}, abstract = {As a sport, field lacrosse requires seamless transitions between acceleration and deceleration. Unfortunately, linear displacement variables at a constant speed underestimate the energy demand in team sports, as they fail to account for the additional energy expended during acceleration and deceleration. In order to address these additional energy costs and offer a more precise measure of an athlete's workload, the metric called metabolic equivalent distance (MED) was developed. The purpose of the study was to assess the differences in MED across game quarters and athlete positions among female collegiate lacrosse players and determine potential relationships between MED and other workload variables. Seventeen female collegiate lacrosse players wore global positioning systems units, and data were collected over the course of 17 games. Performance variables were analyzed per minute played (min PT) and included: MED (m), total distance (m), accelerations (count), decelerations (count), total sprints (count), metabolic peak power (J), metabolic energy cost (J/kg/m), and equivalent distance index (%). No difference was found between athlete position. Performance variables did not differ between game quarters, except for playing time (p rd and 4th quarters compared to quarter 1 (p < .001). MED showed a perfect correlation with total distance and metabolic energy cost (r = 1; p < .001) and a near-perfect correlation with accelerations and total sprints (r = .93; p < .001). Decelerations exhibited a strong correlation with MED (r = .86; p < .001). MED was moderately correlated with metabolic peak power (r = .34; p < .001); whereas equivalent distance index displayed a small correlation (r = .15; p = .02). Athletes exhibited a consistent output in metabolic workload variables across position and game per minute of play. MED could serve as a surrogate workload variable to better understand the athlete’s energy expenditure during high-intensity training and game play. }, year = {2024} }
TY - JOUR T1 - Metabolic Equivalent Distance Across Game Quarters and Athlete Position in Female Collegiate Lacrosse Players AU - Brock Symons AU - Jennifer Bunn Y1 - 2024/04/29 PY - 2024 N1 - https://doi.org/10.11648/j.ajss.20241202.12 DO - 10.11648/j.ajss.20241202.12 T2 - American Journal of Sports Science JF - American Journal of Sports Science JO - American Journal of Sports Science SP - 20 EP - 27 PB - Science Publishing Group SN - 2330-8540 UR - https://doi.org/10.11648/j.ajss.20241202.12 AB - As a sport, field lacrosse requires seamless transitions between acceleration and deceleration. Unfortunately, linear displacement variables at a constant speed underestimate the energy demand in team sports, as they fail to account for the additional energy expended during acceleration and deceleration. In order to address these additional energy costs and offer a more precise measure of an athlete's workload, the metric called metabolic equivalent distance (MED) was developed. The purpose of the study was to assess the differences in MED across game quarters and athlete positions among female collegiate lacrosse players and determine potential relationships between MED and other workload variables. Seventeen female collegiate lacrosse players wore global positioning systems units, and data were collected over the course of 17 games. Performance variables were analyzed per minute played (min PT) and included: MED (m), total distance (m), accelerations (count), decelerations (count), total sprints (count), metabolic peak power (J), metabolic energy cost (J/kg/m), and equivalent distance index (%). No difference was found between athlete position. Performance variables did not differ between game quarters, except for playing time (p rd and 4th quarters compared to quarter 1 (p < .001). MED showed a perfect correlation with total distance and metabolic energy cost (r = 1; p < .001) and a near-perfect correlation with accelerations and total sprints (r = .93; p < .001). Decelerations exhibited a strong correlation with MED (r = .86; p < .001). MED was moderately correlated with metabolic peak power (r = .34; p < .001); whereas equivalent distance index displayed a small correlation (r = .15; p = .02). Athletes exhibited a consistent output in metabolic workload variables across position and game per minute of play. MED could serve as a surrogate workload variable to better understand the athlete’s energy expenditure during high-intensity training and game play. VL - 12 IS - 2 ER -