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Maurice R. Yeadon and Grant Trewartha

The goal of this study was to investigate the control strategy employed by gymnasts in maintaining a hand balance. It was hypothesized that a “wrist strategy” was used in which perturbations in the sagittal plane were corrected using variations in wrist flexor torque with synergistic shoulder and hip torques acting to preserve a fixed body configuration. A theoretical model of wrist strategy indicated that control could be effected using wrist torque that was a linear function of mass center displacement and velocity. Four male gymnasts executed hand balances and 2-dimensional inverse dynamics was used to determine net joint torque time histories at the wrist, shoulder, and hip joints in the sagittal plane. Wrist torque was regressed against mass center position and velocity values at progressively earlier times. It was found that all gymnasts used the wrist strategy, with time delays ranging from 160 to 240 ms. The net joint torques at the shoulder and hip joints were regressed against the torques required to maintain a fixed configuration. This fixed configuration strategy accounted for 86% of the variance in the shoulder torque and 86% of the variance in the hip torque although the actual torques exceeded the predicted torques by 7% and 30%, respectively. The estimated time delays are consistent with the use of long latency reflexes, whereas the role of vestibular and visual information in maintaining a hand balance is less certain.

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Simon Roberts, Grant Trewartha and Keith Stokes

Purpose:

To assess the validity of a digitizing time–motion-analysis method for field-based sports and compare this with a notational-analysis method using rugby-union match play.

Method:

Five calibrated video cameras were located around a rugby pitch, and 1 subject completed prescribed movements within each camera’s view. Running speeds were measured using photocell timing gates. Two experienced operators digitized video data (operator 1 on 2 occasions) to allow 2-dimensional reconstruction of the prescribed movements.

Results:

Accuracy for total distance calculated was within 2.1% of the measured distance. For intraoperator and interoperator reliability, calculated distances were within 0.5% and 0.9%, respectively. Calculated speed was within 8.0% of measured photocell speed with intraoperator and interoperator reliability of 3.4% and 6.0%, respectively. For the method comparison, two 20-minute periods of rugby match play were analyzed for 5 players using the digitizing method and a notational time–motion method. For the 20-minute periods, overall mean absolute differences between methods for percentage time spent and distances covered performing different activities were 3.5% and 198.1 ± 138.1 m, respectively. Total number of changes in activity per 20 minutes were 184 ± 24 versus 458 ± 48, and work-to-rest ratios, 10.0%:90.0% and 7.3%:92.7% for notational and digitizing methods, respectively.

Conclusion:

The digitizing method is accurate and reliable for gaining detailed information on work profiles of field-sport participants and provides applied researchers richer data output than the conventional notational method.

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Edward A. Gannon, Keith A. Stokes and Grant Trewartha

Purpose:

To investigate strength and power development in elite rugby players during the different phases of a professional season.

Methods:

Sixteen professional rugby union athletes from an English premiership team were monitored for measures of lower-body peak force, force at 50 ms, force at 100 ms (all isometric squat), and power (explosive hack squat). Athletes were assessed at the start of preseason (T1), postpreseason (T2), midway through the competitive season (T3), and at the end of the competitive season (T4). Effect-size (ES) statistics with magnitude-based inferences were calculated to interpret differences in physical performance between the different stages of the season.

Results:

Very likely beneficial increases in force at 50 ms (+16%, ES = 0.75 ± 0.4) and 100 ms (+14%, ES = 0.63 ± 0.4) were observed between T1 and T2. A likely beneficial increase in power was observed between T2 and T3 (+4%, ES = 0.31 ± 0.2). Between T3 and T4, decreases in force at 50 ms (–6%, ES = –0.39 ± 0.3) and 100 ms (–9%, ES = –0.52 ± 0.4) occurred, while peak force and power were maintained. Over the full season (T1–T4) clear beneficial increases in all measures of strength and power were identified.

Conclusions:

Meaningful increases in strength and power can be achieved in professional English premiership rugby players over a full playing season. The greatest opportunity for strength and power development occurs during pre- to midseason phases, while these measures are maintained or decrease slightly during the latter stages of a season.

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Simon P. Roberts, Keith A. Stokes, Lee Weston and Grant Trewartha

Purpose:

This study presents an exercise protocol utilizing movement patterns specific to rugby union forward and assesses the reproducibility of scores from this test.

Methods:

After habituation, eight participants (mean ± SD: age = 21 ± 3 y, height = 180 ± 4 cm, body mass = 83.9 ± 3.9 kg) performed the Bath University Rugby Shuttle Test (BURST) on two occasions, 1 wk apart. The protocol comprised 16 × 315-s cycles (4 × 21-min blocks) of 20-m shuttles of walking and cruising with 10-m jogs, with simulated scrummaging, rucking, or mauling exercises and standing rests. In the last minute of every 315-s cycle, a timed Performance Test was carried out, involving carrying a tackle bag and an agility sprint with a ball, followed by a 25-s recovery and a 15-m sprint.

Results:

Participants traveled 7078 m, spending 79.8 and 20.2% of time in low- and high-intensity activity, respectively. The coefficients of variation (CV) between trials 1 and 2 for mean time on the Performance Test (17.78 ± 0.71 vs 17.58 ± 0.79 s) and 15-m sprint (2.69 ± 0.15 vs 2.69 ± 0.15 s) were 1.3 and 0.9%, respectively. There was a CV of 2.2% between trials 1 and 2 for mean heart rate (160 ± 5 vs 158 ± 5 beats⋅min−1) and 14.4% for blood lactate (4.41 ± 1.22 vs 4.68 ± 1.68 mmol⋅L−1).

Conclusion:

Results suggest that measures of rugby union-specifc high-intensity exercise performed during the BURST were reproducible over two trials in habituated participants.

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Neil E. Bezodis, Aki I.T. Salo and Grant Trewartha

Two-dimensional analyses of sprint kinetics are commonly undertaken but often ignore the metatarsal-phalangeal (MTP) joint and model the foot as a single segment. The aim of this study was to quantify the role of the MTP joint in the early acceleration phase of a sprint and to investigate the effect of ignoring the MTP joint on the calculated joint kinetics at the other stance leg joints. High-speed video and force platform data were collected from four to five trials for each of three international athletes. Resultant joint moments, powers, and net work at the stance leg joints during the first stance phase after block clearance were calculated using three different foot models. Considerable MTP joint range of motion (>30°) and a peak net MTP plantar flexor moment of magnitude similar to the knee joint were observed, thus highlighting the need to include this joint for a more complete picture of the lower limb energetics during early acceleration. Inclusion of the MTP joint had minimal effect on the calculated joint moments, but some of the calculated joint power and work values were significantly (P < .05) and meaningfully affected, particularly at the ankle. The choice of foot model is therefore an important consideration when investigating specific aspects of sprinting technique.

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Dominic James Farris, Erica Buckeridge, Grant Trewartha and Miranda Polly McGuigan

This study assessed the effects of orthotic heel lifts on Achilles tendon (AT) force and strain during running. Ten females ran barefoot over a force plate in three conditions: no heel lifts (NHL), with 12 mm heel lifts (12HL) and with 18 mm heel lifts (18HL). Kinematics for the right lower limb were collected (200 Hz). AT force was calculated from inverse dynamics. AT strain was determined from kinematics and ultrasound images of medial gastrocnemius (50 Hz). Peak AT strain was less for 18HL (5.5 ± 4.4%) than for NHL (7.4 ± 4.2%) (p = .029, effect size [ES] = 0.44) but not for 12HL (5.8 ± 4.8%) versus NHL (ES = 0.35). Peak AT force was significantly (p = .024, ES = 0.42) less for 18HL (2382 ± 717 N) than for NHL (2710 ± 830 N) but not for 12HL (2538 ± 823 N, ES = 0.21). The 18HL reduced ankle dorsiflexion but not flexion-extension ankle moments and increased the AT moment arm compared with NHL. Thus, 18HL reduced force and strain on the AT during running via a reduction in dorsiflexion, which lengthened the AT moment arm. Therefore, heel lifts could be used to reduce AT loading and strain during the rehabilitation of AT injuries.

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Matthew J. Cross, Sean Williams, Grant Trewartha, Simon P.T. Kemp and Keith A. Stokes

Purpose:

To explore the association between in-season training-load (TL) measures and injury risk in professional rugby union players.

Methods:

This was a 1-season prospective cohort study of 173 professional rugby union players from 4 English Premiership teams. TL (duration × session-RPE) and time-loss injuries were recorded for all players for all pitch- and gym-based sessions. Generalized estimating equations were used to model the association between in-season TL measures and injury in the subsequent week.

Results:

Injury risk increased linearly with 1-wk loads and week-to-week changes in loads, with a 2-SD increase in these variables (1245 AU and 1069 AU, respectively) associated with odds ratios of 1.68 (95% CI 1.05–2.68) and 1.58 (95% CI 0.98–2.54). When compared with the reference group (<3684 AU), a significant nonlinear effect was evident for 4-wk cumulative loads, with a likely beneficial reduction in injury risk associated with intermediate loads of 5932–8651 AU (OR 0.55, 95% CI 0.22–1.38) (this range equates to around 4 wk of average in-season TL) and a likely harmful effect evident for higher loads of >8651 AU (OR 1.39, 95% CI 0.98–1.98).

Conclusions:

Players had an increased risk of injury if they had high 1-wk cumulative loads (1245 AU) or large week-to-week changes in TL (1069 AU). In addition, a U-shaped relationship was observed for 4-wk cumulative loads, with an apparent increase in risk associated with higher loads (>8651 AU). These measures should therefore be monitored to inform injury-risk-reduction strategies.

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Sean Williams, Grant Trewartha, Matthew J. Cross, Simon P.T. Kemp and Keith A. Stokes

Purpose:

Numerous derivative measures can be calculated from the simple session rating of perceived exertion (sRPE), a tool for monitoring training loads (eg, acute:chronic workload and cumulative loads). The challenge from a practitioner’s perspective is to decide which measures to calculate and monitor in athletes for injury-prevention purposes. The aim of the current study was to outline a systematic process of data reduction and variable selection for such training-load measures.

Methods:

Training loads were collected from 173 professional rugby union players during the 2013–14 English Premiership season, using the sRPE method, with injuries reported via an established surveillance system. Ten derivative measures of sRPE training load were identified from existing literature and subjected to principal-component analysis. A representative measure from each component was selected by identifying the variable that explained the largest amount of variance in injury risk from univariate generalized linear mixed-effects models.

Results:

Three principal components were extracted, explaining 57%, 24%, and 9% of the variance. The training-load measures that were highly loaded on component 1 represented measures of the cumulative load placed on players, component 2 was associated with measures of changes in load, and component 3 represented a measure of acute load. Four-week cumulative load, acute:chronic workload, and daily training load were selected as the representative measures for each component.

Conclusions:

The process outlined in the current study enables practitioners to monitor the most parsimonious set of variables while still retaining the variation and distinct aspects of “load” in the data.