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Craig A. Bridge, Michelle A. Jones and Barry Drust

Purpose:

To examine the activity profiles of elite male competitors during international Taekwondo competition in relation to fn, feather, and heavy weight categories.

Methods:

Twelve male Taekwondo competitors equally representing fn, feather, and heavy weight divisions were studied during the 2005 World Taekwondo Championships using a time-motion system developed to analyze the activities and activity phases. The frequency and duration of activities were recorded and assimilated into four independent activity phases: fighting activity, preparatory activity, nonpreparatory activity and stoppage activity. The total number of exchanges and kicks were also calculated for each combat.

Results:

For all weight groupings the mean ± SD fighting time was 1.7 ± 0.3 s, preparatory time 6.4 ± 2.1 s, nonpreparatory time 3.0 ± 0.6 s, referee stoppage time 2.8 ± 0.9 s and 28 ± 6 exchanges and 31 ± 7 kicks were performed. Differences in the mean fighting time (fn: 1.4 ± 0.2 s vs heavy: 1.8 ± 0.3 s; P = .03; effect size [ES] = 1.57), preparatory time (fn: 5.3 ± 1.0 s vs feather: 8.2 ± 2.6 s; P = .03; ES = 1.47) and the total number of exchanges (feather: 24 ± 6 vs heavy: 32 ± 5; P = .03; ES = 1.44) were identified between the weight categories.

Conclusion:

The activity profile in international Taekwondo competition was modulated by competitors’ weight category. These findings suggest that conditioning sessions may need to be specialized to the requirements of specific weight categories.

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Andrew M. Murray and Matthew C. Varley

Purpose:

To investigate the influence of score line, level of opposition, and timing of substitutes on the activity profile of rugby sevens players and describe peak periods of activity.

Methods:

Velocity and distance data were measured via 10-Hz GPS from 17 international-level male rugby sevens players on 2–20 occasions over 4 tournaments (24 matches). Movement data were reported as total distance (TD), high-speed-running distance (HSR, 4.17−10.0 m/s), and the occurrence of maximal accelerations (Accel, ≥2.78 m/s2). A rolling 1-min sample period was used.

Results:

Regardless of score line or opponent ranking there was a moderate to large reduction in average and peak TD and HSR between match halves. A close halftime score line was associated with a greater HSR distance in the 1st minute of the 1st and 2nd halves compared with when winning. When playing against higher-compared with lower-ranked opposition, players covered moderately greater TD in the 1st minute of the 1st half (difference = 26%; 90% confidence limits = 6, 49). Compared with players who played a full match, substitutes who came on late in the 2nd half had a higher average HSR and Accel by a small magnitude (31%; 5, 65 vs 34%; 6, 69) and a higher average TD by a moderate magnitude (16%; 5, 28).

Conclusions:

Match score line, opposition, and substitute timing can influence the activity profile of rugby sevens players. Players are likely to perform more running against higher opponents and when the score line is close. This information may influence team selection.

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Aoife O’Neill, Kieran Dowd, Clodagh O’Gorman, Ailish Hannigan, Cathal Walsh and Helen Purtill

Purpose:

Profiling activity behaviors in young children is important to understand changes in weight status over time. The purpose of this study is to identify activity profiles from self- and parental-reported Physical Activity (PA) and Sedentary Behavior (SB) variables by gender, and determine if the identified profiles are predictive of weight change from age 9–13 years.

Methods:

Cluster analysis was used to generate activity profiles for the National Longitudinal Study of 8570 9-year-old children (Growing Up in Ireland).

Results:

5.4% of boys were found to be obese. Four cohesive activity profiles were identified for boys, with 7.3% of boys in the least active group identified as obese compared with 4.1% in the most active group. The odds of a normal weight 9-year-old boy in the least active profile becoming overweight or obese at age 13 were over twice those in most active profile (OR = 2.5, 95% CI: 1.9, 3.5). No coherent activity profiles were identified for girls.

Conclusions:

This study suggests that self- and parental-reported data can identify meaningful activity profiles for boys, which are predictive of weight changes over time. Future research should consider potential gender differences in self- and parental-reported PA and SB variables.

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Stuart J. Cormack, Renee L. Smith, Mitchell M. Mooney, Warren B. Young and Brendan J. O’Brien

Purpose:

To determine differences in load/min (AU) between standards of netball match play.

Methods:

Load/min (AU) representing accumulated accelerations measured by triaxial accelerometers was recorded during matches of 2 higher- and 2 lower-standard teams (N = 32 players). Differences in load/min (AU) were compared within and between standards for playing position and periods of play. Differences were considered meaningful if there was >75% likelihood of exceeding a small (0.2) effect size.

Results:

Mean (± SD) full-match load/min (AU) for the higher and lower standards were 9.96 ± 2.50 and 6.88 ± 1.88, respectively (100% likely lower). The higher standard had greater (mean 97% likely) load/min (AU) values in each position. The difference between 1st and 2nd halves’ load/min (AU) was unclear at the higher standard, while lower-grade centers had a lower (−7.7% ± 10.8%, 81% likely) load/min (AU) in the 2nd half and in all quarters compared with the 1st. There was little intrastandard variation in individual vector contributions to load/min (AU); however, higher-standard players accumulated a greater proportion of the total in the vertical plane (mean 93% likely).

Conclusions:

Higher-standard players produced greater load/min (AU) than their lower-standard counterparts in all positions. Playing standard influenced the pattern of load/min (AU) accumulation across a match, and individual vector analysis suggests that different-standard players have dissimilar movement characteristics. Load/min (AU) appears to be a useful method for assessing activity profile in netball.

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Alessandra de Carvalho Bastone, Bruno de Souza Moreira, Renata Alvarenga Vieira, Renata Noce Kirkwood, João Marcos Domingues Dias and Rosângela Corrêa Dias

The purpose of this study was to assess the validity of the Human Activity Profile (HAP) by comparing scores with accelerometer data and by objectively testing its cutoff points. This study included 120 older women (age 60–90 years). Average daily time spent in sedentary, moderate, and hard activity; counts; number of steps; and energy expenditure were measured using an accelerometer. Spearman rank order correlations were used to evaluate the correlation between the HAP scores and accelerometer variables. Significant relationships were detected (rho = .47−.75, p < .001), indicating that the HAP estimates physical activity at a group level well; however, scatterplots showed individual errors. Receiver operating characteristic curves were constructed to determine HAP cutoff points on the basis of physical activity level recommendations, and the cutoff points found were similar to the original HAP cutoff points. The HAP is a useful indicator of physical activity levels in older women.

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Barry S. Mason, Viola C. Altmann and Victoria L. Goosey-Tolfrey

days on the same indoor court (28 × 15 m). Physical data about players’ individual activity profiles and technical data relating to ball handling activities were monitored during all matches using player tracking technology and video analysis, respectively. Data were collected during every instance

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Billy T. Hulin, Tim J. Gabbett, Simon Kearney and Alex Corvo

Purpose:

To quantify activity profiles in approximately 5-min periods to determine if the intensity of rugby league match play changes after the most intense period of play and to determine if the intensity of activity during predefined periods of match play differ between successful and less-successful teams playing at an elite standard.

Methods:

Movement was recorded using a MinimaxX global positioning system (GPS) unit sampling at 10 Hz during 25 rugby league matches, equating to 200 GPS files. Data for each half of match play were separated into 8 equal periods. These periods represented the most intense phase of match play (peak period), the period after the most intense phase of match play (subsequent period), and the average demands of all other periods in a match (mean period). Two rugby league teams were split into a high-success and a low-success group based on their success rates throughout their season.

Results:

Compared with their less-successful counterparts, adjustables and hit-up forwards from the high-success team covered less total distance (P < .01) and less high-intensity-running distance (P < .01) and were involved in a greater number of collisions (P < .01) during the mean period of match play.

Conclusions:

Although a greater number of collisions during match play is linked with a greater rate of success, greater amounts of high-intensity running and total distance are not related to competitive success in elite rugby league. These results suggest that technical and tactical differences, rather than activity profiles, may be the distinguishing factor between successful and less-successful rugby league teams.

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Esther Morencos, Blanca Romero-Moraleda, Carlo Castagna and David Casamichana

. 13. Sunderland CD , Edwards PL . Activity profile and between-match variation in elite field hockey . J Strength Cond Res . 2017 ; 31 ( 3 ): 758 – 764 . PubMed ID: 27359206 doi:10.1519/JSC.0000000000001522 10.1519/JSC.0000000000001522 27359206 14. McGuinness A , Malone S , Petrakos

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Scott J. Strath, Ann M. Swartz and Susan E. Cashin

This study examined objectively determined walking profiles of older adults across a wide range of sociocultural backgrounds. All individuals (N = 415; 131 men age 70.5 ± 9.2 yr and 284 women age 71.5 ± 9.0 yr) underwent physiological measurements, completed pen-and-paper surveys, and wore a pedometer for 7 consecutive days. The total sample accumulated a mean of 3,987 ± 2,680 steps/day. Age (r = –.485, p < .001) and body-mass index (BMI; r = –.353, p < .001) were negatively associated with steps per day. Multivariate analysis revealed that race/ethnic category (F = 3.15, df = 3), gender (F = 2.46, df = 1), BMI (F = 6.23, df = 2), income (F = 9.86, df = 1), education (F = 43.3, df = 1), and retirement status (F = 52.3, df = 1) were significantly associated with steps per day. Collectively these categories accounted for 56% of the variance in walking activity in this independently living, community-dwelling older adult sample. Sedentary characteristics highlighted within, and step-per-day values specific to, older adults have implications for planning targeted physical activity interventions related to walking activity in this population.

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Matthias W. Hoppe, Christian Baumgart, Jutta Bornefeld, Billy Sperlich, Jürgen Freiwald and Hans-Christer Holmberg

The aims of this study were (1) to assess the running activities of adolescent tennis players during match play with respect to velocity, acceleration, and deceleration; (2) to characterize changes in these activities during the course of a match; and (3) to identify potential differences between winners and losers. Twenty well-trained adolescent male athletes (13 ± 1 y) played one simulated match each (giving a total of 10 matches), during which distances covered at different velocity categories (0 to < 1, 1 to < 2, 2 to < 3, 3 to < 4, and ≥ 4 m·s−1) and number of running activities involving high velocity (≥ 3 m·s−1), acceleration (≥ 2 m·s−2), and deceleration (≤ −2 m·s−2) were monitored using a global positioning system (10 Hz). Heart rate was also assessed. The total match time, total distance covered, peak velocity, and mean heart rate were 81.2 ± 14.6 min, 3362 ± 869 m, 4.4 ± 0.8 ms−1, and 159 ± 12 beats min−1, respectively. Running activities involving high acceleration (0.6 ± 0.2 n·min−1) or deceleration (0.6 ± 0.2 n·min−1) were three times as frequent as those involving high velocity (0.2 ± 0.1 n·min−1). No change in the pattern of running activities (P ≥ .13, d ≤ 0.39) and no differences between winners and losers (P ≥ .22, d ≤ 0.53) were evident during match play. We conclude that training of well-trained adolescent male tennis players need not focus on further development of their running abilities, since this physical component of multifactorial tennis performance does not change during the course of a match and does not differ between the winners and losers.