The Unsuitability of Energy Expenditure Derived From Microtechnology for Assessing Internal Load in Collision-Based Activities

Abstract

This aim of this study was to examine the validity of energy expenditure derived from microtechnology when measured during a repeated-effort rugby protocol. Sixteen male rugby players completed a repeated-effort protocol comprising 3 sets of 6 collisions during which movement activity and energy expenditure (EE) were measured using microtechnology. In addition, energy expenditure was estimated from open-circuit spirometry (EE). While related (r = .63, 90%CI .08-.89), there was a systematic underestimation of energy expenditure during the protocol (-5.94 ± 0.67 kcal/min) for EE (7.2 ± 1.0 kcal/min) compared with EE (13.2 ± 2.3 kcal/min). High-speed-running distance (r = .50, 95%CI -.66 to .84) was related to EE, while PlayerLoad was not (r = .37, 95%CI -.81 to .68). While metabolic power might provide a different measure of external load than other typically used microtechnology metrics (eg, high-speed running, PlayerLoad), it underestimates energy expenditure during intermittent team sports that involve collisions.

Estimates of Energy Intake and Expenditure in Elite Female Touch Players During an International Tournament

“…While a metabolic power approach has been used previously in other sports (Polglaze et al, 2017;Coutts et al, 2015), we acknowledge the possible underestimation of EE during match play by employing this method (Highton et al, 2016;Buchheit et al, 2015). Furthermore, data were gathered from a small sample size from one female International Touch squad during a single tournament.…”

“…7.2 ± 1.0 cf. 13.2 ± 3.2 Kcal•min -1 ; Highton et al, 2016), it possesses a stronger association with EE (r = 0.63) than other measures such as high-speed distance (r = 0.50) or Player Load™ (r = 0.37; Highton et al, 2016). Given this method has been employed with other non-contact team sports (Polglaze et al, 2017), the metabolic power model offers a useful approach to understand the energy demands of Touch.…”

Player-Tracking Technology: Half-Full or Half-Empty Glass?

“…Considering that the agreement between P GPS and P VO2 has only been shown to be acceptable during continuous and linear jog and runs (but neither during walking nor intermittent changes of direction runs), 27 the metabolic underestimation consistently reported [26][27][28][29] may be related to the fact that the current equation initially developed for maximal and linear sprint acceleration 21 may not be well suited for team-sport-specific running patterns (eg, including . The shorter the window, the greater the acceleration value.…”

“…P GPS was actually reported to be very largely greater than P VO2 during walking 27 but very largely lower during shuttle runs at low speed 28 and during soccer-, 26 rugby-, 29 or team-sport-specific 27 circuits. While some may see the consistency of such conclusions as a kind of consensus, Osgnach et al 30 suggested that some methodological errors may explain the underestimation of P GPS reported.…”

“…While some may see the consistency of such conclusions as a kind of consensus, Osgnach et al 30 suggested that some methodological errors may explain the underestimation of P GPS reported. [26][27][28][29] Among others, they attributed our discordant results to the inclusion of resting VO 2 when calculating P VO2 (while we have in fact used net VO 2 , as clearly written in Buchheit et al, 26 p. 1151, second paragraph), the impact of nonlocomotor actions on P VO2 (while team sports often include intense but static movements that logically increase systemic energy expenditure [P VO2 ] independently of locomotor movements [P GPS ]) 31 ), an underestimation of the anaerobic contribution to P VO2 (while if we had better accounted for the entire anaerobic contribution to P VO2 , the P GPS underestimation that we reported would have been even greater, not smaller 31 ), and our 4-Hz GPS sampling frequency (while the other researchers have all reported the same underestimation using higher sampling frequencies ie, 500, 28 10, 29 and 5 27 Hz). Note also that we have shown that sampling frequency per se was not the most important factor when it comes to precision and validity.…”