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Ted Polglaze and Matthias W. Hoppe

Metabolic power ( P met ) has been proposed as a tool to estimate the energetic demands of variable-speed locomotion typically seen in team sports. 1 From the outset, it should be stated that this model is not able to fully account for the physical demands of team-sport activity, 2 , 3 but nor

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Tom Kempton, Anita Claire Sirotic, Ermanno Rampinini and Aaron James Coutts

Purpose:

To describe the metabolic demands of rugby league match play for positional groups and compare match distances obtained from high-speed-running classifications with those derived from high metabolic power.

Methods:

Global positioning system (GPS) data were collected from 25 players from a team competing in the National Rugby League competition over 39 matches. Players were classified into positional groups (adjustables, outside backs, hit-up forwards, and wide-running forwards). The GPS devices provided instantaneous raw velocity data at 5 Hz, which were exported to a customized spreadsheet. The spreadsheet provided calculations for speed-based distances (eg, total distance; high-speed running, >14.4 km/h; and very-highspeed running, >18.1 km/h) and metabolic-power variables (eg, energy expenditure; average metabolic power; and high-power distance, >20 W/kg).

Results:

The data show that speed-based distances and metabolic power varied between positional groups, although this was largely related to differences in time spent on field. The distance covered at high running speed was lower than that obtained from high-power thresholds for all positional groups; however, the difference between the 2 methods was greatest for hit-up forwards and adjustables.

Conclusions:

Positional differences existed for all metabolic parameters, although these are at least partially related to time spent on the field. Higher-speed running may underestimate the demands of match play when compared with high-power distance—although the degree of difference between the measures varied by position. The analysis of metabolic power may complement traditional speed-based classifications and improve our understanding of the demands of rugby league match play.

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Alena M. Grabowski and Rodger Kram

The biomechanical and metabolic demands of human running are distinctly affected by velocity and body weight. As runners increase velocity, ground reaction forces (GRF) increase, which may increase the risk of an overuse injury, and more metabolic power is required to produce greater rates of muscular force generation. Running with weight support attenuates GRFs, but demands less metabolic power than normal weight running. We used a recently developed device (G-trainer) that uses positive air pressure around the lower body to support body weight during treadmill running. Our scientific goal was to quantify the separate and combined effects of running velocity and weight support on GRFs and metabolic power. After obtaining this basic data set, we identified velocity and weight support combinations that resulted in different peak GRFs, yet demanded the same metabolic power. Ideal combinations of velocity and weight could potentially reduce biomechanical risks by attenuating peak GRFs while maintaining aerobic and neuromuscular benefits. Indeed, we found many combinations that decreased peak vertical GRFs yet demanded the same metabolic power as running slower at normal weight. This approach of manipulating velocity and weight during running may prove effective as a training and/or rehabilitation strategy.

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Darcy M. Brown, Dan B. Dwyer, Samuel J. Robertson and Paul B. Gastin

The purpose of this study was to assess the validity of a global positioning system (GPS) tracking system to estimate energy expenditure (EE) during exercise and field-sport locomotor movements. Twenty-seven participants each completed a 90-min exercise session on an outdoor synthetic futsal pitch. During the exercise session, they wore a 5-Hz GPS unit interpolated to 15 Hz and a portable gas analyzer that acted as the criterion measure of EE. The exercise session was composed of alternating 5-minute exercise bouts of randomized walking, jogging, running, or a field-sport circuit (×3) followed by 10 min of recovery. One-way analysis of variance showed significant (P < .01) and very large underestimations between GPS metabolic power– derived EE and oxygen-consumption (VO2) -derived EE for all field-sport circuits (% difference ≈ –44%). No differences in EE were observed for the jog (7.8%) and run (4.8%), whereas very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90-min session was significantly lower (P < .01) than the VO2 EE, resulting in a moderate underestimation overall (–19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field-sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however, is it able to provide a reasonably accurate estimation of EE during continuous jogging and running.

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Andrea Nicolò, Marco Montini, Michele Girardi, Francesco Felici, Ilenia Bazzucchi and Massimo Sacchetti

, one of the most used metrics that can be obtained from GPS data is metabolic power ( P met ), which attempts to estimate the energy expenditure of the player during any activity, including activities where speed is not constant. 2 However, the assumptions underlying P met calculation may lead to

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Jason D. Vescovi and Devon H. Frayne

Purpose:

To examine locomotor demands and metabolic-power characteristics of National Collegiate Athletic Association (NCAA) field hockey matches.

Methods:

Using a cross-sectional design, global positioning system (GPS) technology tracked Division I field hockey players from 6 teams during 1 regular-season match (68 player observations). An ANOVA compared locomotor demands and metabolic-power characteristics among positions. Paired t tests compared dependent variables between halves.

Results:

Defenders played 5−6 min more than midfielders, whereas midfielders played 6−7 min more than forwards. Defenders covered less relative distance (98 m/min) than forwards and midfielders (110−111 m/min), as well as more low-intensity running than forwards and less high-intensity running than midfielders. Lower mean metabolic power (9.3 W/kg) was observed for defenders than forwards and midfielders (10.4 W/kg). There was no difference in playing time between halves; however, all 3 positions had a reduction in relative distance (7−9%) and mean metabolic power (8−9%) during the second half.

Conclusions:

Despite more playing time, defenders covered less relative distance and had lower mean metabolic power than other positions. Moderate-intensity, high-intensity, and sprint distance were similar between positions, highlighting the greater relative demands on forwards because they tended to have the least amount of playing time. The reduction of key metrics during the second half was similar among positions and warrants further investigation. These initial results can be used to design position-specific drills or create small-sided games that replicate match demands for NCAA athletes, thus helping establish strategies for developing physiological ability of players at this level.

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Carlo Castagna, Matthew Varley, Susana C.A. Póvoas and Stefano D’Ottavio

Purpose:

To test the interchangeability of 2 match-analysis approaches for external-load detection considering arbitrary selected speeds and metabolic power (MP) thresholds in male top-level soccer.

Methods:

Data analyses were performed considering match physical performance of 60 matches (1200 player cases) of randomly selected Spanish, German, and English first-division championship matches (2013–14 season). Match analysis was performed with a validated semiautomated multicamera system operating at 25 Hz.

Results:

During a match, players covered 10,673 ± 348 m, of which 1778 ± 208 m and 2759 ± 241 m were performed at high intensity, as measured using speed (≥16 km/h, HI) and metabolic power (≥20 W/kg, MPHI) notations. High-intensity notations were nearly perfectly associated (r = .93, P < .0001). A huge method bias (980.63 ± 87.82 m, d = 11.67) was found when considering MPHI and HI. Very large correlations were found between match total distance covered and MPHI (r = .84, P < .0001) and HI (r = .74, P < .0001). Player high-intensity decelerations (≥–2 m/s2) were very largely associated with MPHI (r = .73, P < .0001).

Conclusions:

The speed and MP methods are highly interchangeable at relative level (magnitude rank) but not absolute level (measure magnitude). The 2 physical match-analysis methods can be independently used to track match external load in elite-level players. However, match-analyst decisions must be based on use of a single method to avoid bias in external-load determination.

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Jace A. Delaney, Heidi R. Thornton, Grant M. Duthie and Ben J. Dascombe

Background:

Rugby league coaches adopt replacement strategies for their interchange players to maximize running intensity; however, it is important to understand the factors that may influence match performance.

Purpose:

To assess the independent factors affecting running intensity sustained by interchange players during professional rugby league.

Methods:

Global positioning system (GPS) data were collected from all interchanged players (starters and nonstarters) in a professional rugby league squad across 24 matches of a National Rugby League season. A multilevel mixed-model approach was employed to establish the effect of various technical (attacking and defensive involvements), temporal (bout duration, time in possession, etc), and situational (season phase, recovery cycle, etc) factors on the relative distance covered and average metabolic power (Pmet) during competition. Significant effects were standardized using correlation coefficients, and the likelihood of the effect was described using magnitude-based inferences.

Results:

Superior intermittent running ability resulted in very likely large increases in both relative distance and Pmet. As the length of a bout increased, both measures of running intensity exhibited a small decrease. There were at least likely small increases in running intensity for matches played after short recovery cycles and against strong opposition. During a bout, the number of collision-based involvements increased running intensity, whereas time in possession and ball time out of play decreased demands.

Conclusions:

These data demonstrate a complex interaction of individual- and match-based factors that require consideration when developing interchange strategies, and the manipulation of training loads during shorter recovery periods and against stronger opponents may be beneficial.

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Jace A. Delaney, Heidi R. Thornton, John F. Pryor, Andrew M. Stewart, Ben J. Dascombe and Grant M. Duthie

Purpose:

To quantify the duration and position-specific peak running intensities of international rugby union for the prescription and monitoring of specific training methodologies.

Methods:

Global positioning systems (GPS) were used to assess the activity profile of 67 elite-level rugby union players from 2 nations across 33 international matches. A moving-average approach was used to identify the peak relative distance (m/min), average acceleration/deceleration (AveAcc; m/s2), and average metabolic power (Pmet) for a range of durations (1–10 min). Differences between positions and durations were described using a magnitude-based network.

Results:

Peak running intensity increased as the length of the moving average decreased. There were likely small to moderate increases in relative distance and AveAcc for outside backs, halfbacks, and loose forwards compared with the tight 5 group across all moving-average durations (effect size [ES] = 0.27–1.00). Pmet demands were at least likely greater for outside backs and halfbacks than for the tight 5 (ES = 0.86–0.99). Halfbacks demonstrated the greatest relative distance and Pmet outputs but were similar to outside backs and loose forwards in AveAcc demands.

Conclusions:

The current study has presented a framework to describe the peak running intensities achieved during international rugby competition by position, which are considerably higher than previously reported whole-period averages. These data provide further knowledge of the peak activity profiles of international rugby competition, and this information can be used to assist coaches and practitioners in adequately preparing athletes for the most demanding periods of play.

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Jace A. Delaney, Grant M. Duthie, Heidi R. Thornton, Tannath J. Scott, David Gay and Ben J. Dascombe

Rugby league involves frequent periods of high-intensity running including acceleration and deceleration efforts, often occurring at low speeds.

Purpose:

To quantify the energetic cost of running and acceleration efforts during rugby league competition to aid in prescription and monitoring of training.

Methods:

Global positioning system (GPS) data were collected from 37 professional rugby league players across 2 seasons. Peak values for relative distance, average acceleration/deceleration, and metabolic power (Pmet) were calculated for 10 different moving-average durations (1–10 min) for each position. A mixed-effects model was used to assess the effect of position for each duration, and individual comparisons were made using a magnitude-based-inference network.

Results:

There were almost certainly large differences in relative distance and Pmet between the 10-min window and all moving averages <5 min in duration (ES = 1.21–1.88). Fullbacks, halves, and hookers covered greater relative distances than outside backs, edge forwards, and middle forwards for moving averages lasting 2–10 min. Acceleration/deceleration demands were greatest in hookers and halves compared with fullbacks, middle forwards, and outside backs. Pmet was greatest in hookers, halves, and fullbacks compared with middle forwards and outside backs.

Conclusions:

Competition running intensities varied by both position and moving-average duration. Hookers exhibited the greatest Pmet of all positions, due to high involvement in both attack and defense. Fullbacks also reached high Pmet, possibly due to a greater absolute volume of running. This study provides coaches with match data that can be used for the prescription and monitoring of specific training drills.