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Georgia M. Black and Tim J. Gabbett

Purpose:

No study has investigated the frequency and nature of repeated high-intensity-effort (RHIE) bouts across elite and semielite rugby league competitions. This study examined RHIE activity in rugby league match play across playing standards.

Participants:

36 elite and 64 semielite rugby league players.

Methods:

Global positioning system analysis was completed during 17 elite and 14 semielite matches.

Results:

The most commonly occurring RHIE bouts involved 2 efforts (2-RHIE) for both elite and semielite players. Only small differences were found in 2-RHIE activity between elite and semielite match play (effect size [ES] ≥0.31 ± 0.15, ≥88%, likely). RHIE bouts were more likely to involve contact as the number of efforts in a bout increased (ES ≥0.40 ± 0.15, 100%, almost certainly). Semielite players performed a greater proportion of 2-contact-effort RHIE bouts than their elite counterparts (68.2% vs 60.6%, ES 0.33 ± 0.15, 92%, likely), while elite players performed a greater proportion of 3-effort bouts (26.9% vs 21.1%, ES 0.31 ± 0.15, 88%, likely). Elite players also had a shorter recovery (1.00−3.99 vs ≥4.00 min) between RHIE bouts (ES ≥1.60 ± 0.71, ≥94%, likely).

Conclusion:

These findings highlight the RHIE demands of elite and semielite rugby league match play. Elite players are more likely to perform RHIE bouts consisting of 3 efforts and to have a shorter recovery time between bouts. Exposing players to these RHIE demands in training is likely to improve their ability to tolerate the most demanding passages of match play.

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Georgia M. Black, Tim J. Gabbett, Richard D. Johnston, Geraldine Naughton, Michael H. Cole and Brian Dawson

Purpose: With female Australian football (AF) gaining popularity, understanding match demands is becoming increasingly important. The aim of this study was to compare running performances of rotated and whole-quarter state-level female AF players during match quarters. Methods : Twenty-two state-level female AF midfielders wore Global Positioning System units during 14 games to evaluate activity profiles. The Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) was used as a measure of high-intensity running ability. Data were categorized into whole quarter, rotation bout 1, and rotation bout 2 before being further divided into quartiles. Players were separated into high- or low-Yo-Yo IR1 groups using a median split based on their Yo-Yo IR1 performance. Short (4–6 min), moderate (6–12 min), and long (12–18 min) on-field bout activity profiles were compared with whole-quarter players. Results: High Yo-Yo IR1 performance allowed players to cover greater relative distances (ES = 0.57–0.88) and high-speed distances (ES = 0.57–0.86) during rotations. No differences were reported between Yo-Yo IR1 groups when players were required to play whole quarters (ES ≤ 0.26, likelihood ≤64%). Players who were on field for short to moderate durations exhibited greater activity profiles than whole-quarter players. Conclusions: Superior high-speed running ability results in a greater activity profile than for players who possess lower high-speed running ability. The findings also highlight the importance of short to moderate (4–12 min) rotation periods and may be used to increase high-intensity running performance within quarters in female AF players.

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Georgia M. Black, Tim J. Gabbett, Rich D. Johnston, Michael H. Cole, Geraldine Naughton and Brian Dawson

Purpose: The transition of female Australian football (AF) players from amateur to semielite competitions has the potential for athletes to be underprepared for match play. To gain an understanding of the match demands of female football, the aims of this study were to highlight the physical qualities that discriminate selected and nonselected female AF players, investigate activity profiles of female AF players, and gain an understanding of the influence of physical qualities on performance in female AF Methods: Twenty-two female AF state academy players (mean [SD]: age = 23.2 [4.5] y) and 27 nonselected players (mean [SD]: age = 23.4 [4.9] y) completed a Yo-Yo intermittent recovery test level 1, countermovement jump, and 30-m sprint tests were completed prior to the competitive season. During 14 matches, players wore global positioning system units to describe the running demands of match play. Results: Selected players were faster over 30 m (ES = 0.57; P = .04) and covered greater distances on the Yo-Yo IR1 (ES = 1.09; P < .001). Selected midfielders spent greater time on the field and covered greater total distances (ES = 0.73–0.85; P < .01). Players faster over 5 m (r = −.612) and 30 m (r = −.807) and who performed better on the Yo-Yo IR1 (r = .489) covered greater high-speed distances during match play. Conclusions: An emphasis should be placed on the development of physical fitness in this playing group to ensure optimal preparation for the national competition.

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Nick B. Murray, Georgia M. Black, Rod J. Whiteley, Peter Gahan, Michael H. Cole, Andy Utting and Tim J. Gabbett

Purpose:

Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit.

Methods:

Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts).

Results:

The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%).

Conclusions:

These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.