Physical Demands of Women s Rugby Sevens Matches: Female Athletes in Motion (FAiM) Study

Training & Testing 887 Physical Demands of Women s Rugby Sevens Matches: Female Athletes in Motion (FAiM) Study Authors J. D. Vescovi 1, T. Goodale 2 Affiliations 1 University of Toronto, Kinesiology and Physical Education, Toronto, Canada 2 Canadian Sport Institute Pacific, Strength & Conditioning, Victoria, Canada Key words female athlete motion analysis metabolic power training impulse standard of play the daily training environment is useful for optimizing performance outcomes. Indeed, identifying and developing players to specialize in sevens is a trend that will likely persist and require specific physical preparation for the sport. A distinction in locomotor demands across standards has been reported for other field sports such as soccer [1, 17] and field hockey [24], highlighting the need to achieve the functional requirements at a given level before progressing to higher standards. Initial research into the demands of rugby sevens has been dominated by examining men s teams [15, 19, 35, 38, 40]; however some researchers have reported on women s sevens matches [34, 39]. Elite female players cover 1 500 1 600 m per match, which is 15 20 % greater than lower standards; moreover sprint distances are 2 2.5 times higher for elite female squads [34, 39]. The cardiovascular demand is also substantial, regardless of standard, evidenced by a majority of match time spent above 80 % heart rate maximum. Thus aerobic fitness as well as the ability to sustain moveaccepted after revision March 15, 2015 Bibliography DOI http://dx.doi.org/ 10.1055/s-0035-1548940 Published online: July 3, 2015 Int J Sports Med 2015; 36: 887 892 Georg Thieme Verlag KG Stuttgart New York ISSN 0172-4622 Correspondence Jason D. Vescovi, PhD University of Toronto Kinesiology and Physical Education 55 Harbord Street Toronto Canada M3J 2S5 Tel.: + /1/703/477 4600 Fax: + 1/703/477 4600 vescovij@aol.com Abstract This cross-sectional study characterized the locomotor, heart rate and metabolic power characteristics of women s rugby sevens matches. 4 Canadian teams were monitored during the USA Rugby Sevens event using global positioning system technology with players classified as International (n = 16) or Developmental (n = 13). Dependent variables were compared between these 2 groups using an ANOVA with duration played as a covariate. International players covered greater distances (1 468 ± 88 m) than Developmental (1 252 ± 135 m); mostly from more high-intensity (224 ± 55 m vs. 131 ± 44 m) and sprint distances (128 ± 67 m vs. 57 ± 44 m). International players also had more distance in high (264 ± 36 m vs. 210 ± 54 m), elevated (118 ± 17 m Introduction Rugby sevens has grown rapidly since the announcement of its inclusion in the 2016 Olympic Games. Countries historically participating in various rugby codes have launched and are developing sevens squads. In addition to the Olympics the top teams compete annually in the World Rugby Men s and Women s Sevens World Series (October to June). This competition series has expedited the development process, especially for women s squads, by enabling countries to play against high-level opposition. Sevens matches are played on a full-sized rugby field and consist of two 7-min halves with a brief, 2-min, half time. These parameters, along with teams having only 7 players on the field, results in altered demands when compared against other rugby codes (i. e., Union, League) [2, 40, 46]. The physical preparation of players at any standard requires knowledge about competition demands since a game-centered approach within vs. 76 ± 20 m) and maximal (69 ± 17 m vs. 30 ± 15 m) metabolic power categories. Time in various heart rate zones was similar between standards; however peak (187 ± 6 bpm vs. 194 ± 5 bpm) and mean (172 ± 7 bpm vs. 180 ± 9 bpm) heart rate values were lower for International players. International players had greater fitness scores (YoYo IRT1-1 160 ± 191 m vs. 781 ± 129 m) and maximal sprint speed (27.3 ± 0.7 vs. 26.0 ± 1.5 km h 1 ). The current findings highlight developmental gaps in match demands between standards and show that field-based fitness tests discriminate among levels of play. The external and internal loads should be used by sport organizations to assist in forming appropriate training plans and utilize the performance tests to help monitor player development.

888 Training & Testing ment at higher velocities are important characteristics of women s sevens. Recent research has investigated the importance of physical qualities to performance for various men s rugby codes (i. e., sevens and League) [10 12, 20], thus there is a need to further elucidate the demands of women s sevens matches and better understand the relationship with physical performance characteristics. In addition to the locomotor and cardiovascular demands, a new method to assess metabolic loads was recently described [8, 32] and shows promise for rugby codes [6, 25]. Therefore, the primary purpose of this study was to examine the locomotor, metabolic power and heart rate demands for several standards of women s sevens matches. A secondary aim was to determine the association between match demands and physical performance characteristics. Materials & Methods Participants This was a cross-sectional study designed to determine the external and internal demands of women s sevens matches across different standards. Study procedures were approved by the Office of Research Ethics and the investigation was conducted in accordance with the Declaration of Helsinki. Experimental procedures were provided and written informed consent was obtained by participants prior to volunteering in the study. This study meets the ethical standards of the International Journal of Sports Medicine [18]. Female rugby sevens players from the Canadian National Team (n = 22) and a university squad (n = 25) volunteered for this study and were monitored during all matches at the 2012 USA Sevens Rugby Invitational Tournament (Las Vegas, NV, USA). The Canadian National Team had 2 squads (A and B) that participated in the International Division whereas university players had one team compete in the Elite Division and another in the College Division. Only data from participants completing at least 6 min in each half of at least one match were included in the current analysis (n = 29 players). This approach was taken to minimize the potential for increased variability introduced by substitutes who played a small fraction of match duration and to maintain the focus on overall competitive demands of full (or nearly full) length participation in rugby sevens matches. Match configuration and analysis All matches had 7 min halves and were played on standardsized, outdoor grass fields with 7 players a side. Matches were played in accordance with standard rules from World Rugby and refereed by qualified officials. The match schedule was customary for rugby sevens with 2 3 matches played each day on consecutive days (total of 5 matches for each division). Before each match participants were outfitted with a non-differential Global Positioning System (GPS) unit (SPI Pro 5 Hz, GPSports, Canberra, Australia) worn in a special-made vest between the shoulder blades. Reliability and validity of nondifferential GPS have been previously reported [16, 23, 27]. The GPS brand and model used in this study is valid and reliable for measuring sprint distance and speed [33, 47]. An optimal number of satellites (7 12) were available for signal transmission [23] and any horizontal dilution of precision (HDOP) values in excess of 4 were automatically rejected by the software (personal communication from manufacturer) [49]. A heart rate monitor (Polar Electro Oy, Kempele, Finland) was worn around the chest during all matches. A digital watch that received satellite time identified the start and end of each half, as signaled by the referee s whistle. These times were used, in conjunction with substitutions, to delineate the raw GPS and heart rate data so that only time on the pitch during each match was included for analysis. This approach was used to determine accurate relative locomotor distances while playing in the match [48]. After each match the data were extracted using proprietary software (GPSports, Team AMS R1 2013.21) for analysis. Locomotor activities were operationally defined as: low-intensity (0 8.0 km h 1 ), moderate-intensity (8.1 16.0 km h 1 ), highintensity (16.1 20.0 km h 1 ) and sprinting (20.1 32.0 km h 1 ). High-intensity and sprint velocity bands were based on previously published reports describing these characteristics for women s team sports [4, 9, 42, 43]. Heart rate data were classified as < 80 %, 80 90 % and > 90 % of each participant s individual peak heart rate (see below testing) since these zones are associated with the first (VT1) and second (VT2) ventilatory thresholds [36]. The duration accumulated within each heart rate zone is reported as well as the training impulse (TRIMP) by applying weighting factors to specific heart rate zones [37]. The TRIMP provides a method to quantify the total cardiovascular effort (dose) by combining the heart rate response with the duration of effort [3] and is useful especially during intermittent activities like rugby. Metabolic power was automatically derived within Team AMS and reported as the distances covered in the following metabolic power categories [32]: low ( < 10 W kg 1 ), intermediate (10 20 W kg 1 ), high (20 35 W kg 1 ), elevated (35 55 W kg 1 ) and maximal ( > 55 W kg 1 ). Metrics related to metabolic power may provide additional insight into match demands beyond traditional velocity-dependent parameters because accelerations are taken into account. No studies have determined the validity of metabolic power derived from GPS technology. DiPrampero et al. [8] and Osgnach et al. [32] used sampling frequencies of 35 Hz and 25 Hz, respectively; however in both studies the data were low-pass filtered during post-processing (exact frequency not specified) and is likely near the 5 Hz collection frequency of the GPS system used in the current study. Performance testing Testing was performed indoors 2 3 weeks prior to competition. A linear sprint and the Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IRT1) assessed maximum sprint speed and intermittent fitness, respectively. All athletes performed a standardized warm-up of approximately 15 min that included general exercises such as jogging, shuffling, sprinting, multi-directional movements, and dynamic stretching exercises. Participants wore shorts, t-shirt and running shoes during testing. Maximum sprint speed for the Canadian National team players was defined by the final 10 m during a 40-m sprint (i. e., 30 40 m); whereas it was defined by the final 5 or 10 m during a 35-m sprint for the university participants (i. e., 25 35 m or 30 35 m). This was done to maintain standard testing procedures within the respective groups. Unpublished data from the author s laboratory revealed no difference in maximum speed when using 35 or 40 m for sprint testing. Other than this subtle difference in distances the procedures for testing were the same between groups. Infrared timing gates (Brower Timing, Utah) were positioned along the course at a height of approximately 1.0 m. Participants stood upright, with their lead foot positioned

Training & Testing 889 International (n = 16) Developmental (n = 13) p-value (d) Performance testing sprint speed (km h 1 ) 27.3 ± 0.7 (26.8 27.7) 26.0 ± 1.5 (25.2 26.8) 0.003 (1.16) Yo-Yo IRT1 (m) 1 160 ± 191 (1 022 1 239) 781 ± 129 (710 853) < 0.001 (2.28) peak heart rate (bpm) 192 ± 6 (190 196) 193 ± 6 (190 196) 0.804 (0.09) Locomotor demands * duration (min) 15.5 ± 0.9 (15.0 16.0) 13.8 ± 0.6 (13.5 14.2) < 0.001 (0.09) total distance (m) 1 468 ± 88 (1415 1521) 1 252 ± 135 (1170 1333) 0.016 (1.95) total distance (m min 1 ) 95 ± 5 (92 98) 91 ± 11 (84 97) 0.169 (0.53) low-intensity (m) 564 ± 40 (542 585) 541 ± 86 (489 583) 0.274 (0.35) low-intensity (m min 1 ) 36 ± 2 (35 38) 39 ± 6 (36 42) 0.094 (0.64) moderate-intensity (m) 552 ± 76 (512 592) 523 ± 153 (430 615) 0.362 (0.25) moderate-intensity (m min 1 ) 36 ± 5 (33 39) 38 ± 12 (31 45) 0.499 (0.25) high-intensity (m) 224 ± 55 (195 253) 131 ± 44 (104 157) 0.012 (1.85) high-intensity (m min 1 ) 14 ± 3 (13 16) 10 ± 4 (7 12) 0.001 (1.47) sprinting (m) 128 ± 67 (92 164) 57 ± 44 (31 84) 0.090 (1.22) sprinting (m min 1 ) 8 ± 4 (6 11) 4 ± 3 (2 6) 0.007 (1.09) peak speed (km h 1 ) 26.5 ± 1.9 (25.5 27.5) 24.6 ± 2.7 (22.9 26.2) 0.027 (0.83) Metabolic power demands * low (m) 641 ± 34 (623 659) 602 ± 77 (555 648) 0.781 (0.69) intermediate (m) 353 ± 36 (334 372) 314 ± 91 (259 369) 0.288 (0.58) high (m) 264 ± 36 (245 283) 210 ± 54 (177 242) 0.021 (1.20) elevated (m) 118 ± 17 (109 128) 76 ± 20 (64 88) 0.004 (2.29) maximal (m) 69 ± 17 (60 78) 30 ± 15 (21 40) 0.002 (2.34) mean power (W kg 1 ) 8.8 ± 0.7 (8.4 9.1) 8.5 ± 1.1 (7.8 9.1) 0.088 (0.22) energy cost (kj kg 1 ) 7.8 ± 1.0 (7.3 8.3) 6.9 ± 0.8 (6.5 7.4) 0.241 (0.94) Heart rate demands < 80 % (min) 2.0 ± 2.9 (0.4 3.6) 0.9 ± 0.8 (0.3 1.4) 0.203 (0.51) 80 90 % (min) 4.8 ± 2.6 (3.4 6.3) 3.8 ± 2.5 (2.2 5.4) 0.302 (0.41) > 90 % (min) 8.2 ± 4.7 (5.6 10.8) 9.0 ± 3.1 (7.0 11.0) 0.617 (0.20) mean heart rate (bpm) 172 ± 7 (167 178) 180 ± 9 (174 186) 0.023 (0.94) peak heart rate (bpm) 187 ± 6 (184 190) 194 ± 5 (191 198) 0.004 (1.24) training Impulse (AU) 118 ± 20 (107 129) 124 ± 9 (118 130) 0.359 (0.36) Means ± SD (95 % CI). * All absolute distances (m) adjusted for duration played approximately 5 cm behind the initial infrared beam (i. e., start line) and began when ready. Two trials were completed with 3 min between trials. The assessment of linear sprints using infrared timing gates is highly reliable and does not require familiarization [28, 30, 31]. The Yo-Yo IRT1 is regarded as a good measure of aerobic-anaerobic indices for intermittent team sports, has high reliability [5, 26], and can discriminate between standards [41] and age groups [7]. Peak heart rate values with Yo-Yo IRT1 are also comparable to those observed during maximal treadmill tests [26]. The test was implemented according to standard procedures (e. g., running back and forth on a 20-m course with 10 s recovery between each 40-m lap) [26] and the total distance covered was used as the outcome. Heart rate was continuously recorded with automated telemetry monitors (Polar) placed around the chest, collecting at 5-s epochs. Peak heart rate at test termination was recorded and subsequently used to delineate individual zones for match analysis. Statistical analysis Initial analysis across the 4 groups revealed no differences between the 2 Canadian National teams as well as between the 2 university teams for all reported dependent variables; thus the teams were collapsed into 2 groups: International and Developmental. A repeated measures ANOVA was used to compare the dependent variables for players who competed in at least 3 matches (n = 11). There were no differences observed for any Table 1 Testing performance and physical demands of matches. dependent variable, thus data were subsequently collapsed across the matches and comparisons between groups were made with an ANCOVA using duration played as a covariate. Pearson correlations were used to examine the relationship between Yo-Yo IRT1 scores as well as TRIMP with the locomotor and metabolic power variables. Statistical significance was accepted at p < 0.05 and data are presented as mean ± SD (95 % confidence intervals). The effect size (Cohen s d) was calculated from the ratio of the mean difference to the pooled standard deviation and were considered trivial (< 0.2), small (0.2 0.6), moderate (0.61 1.20), large (1.21 2.0), and very large (2.1 4.0) [21, 45]. Results Table 1 shows outcomes from the field-based performance assessments as well as the locomotor (absolute and relative), metabolic power and heart rate demands during matches. Performance testing: Maximum sprint speed and performance on the Yo-Yo IRT1 test was greater for the International players than Developmental athletes; however no differences were found for peak heart rate between groups. Fig. 1 shows the relationship between Yo-Yo IRT1 performance and high-intensity running as well as distances in elevated and maximal metabolic power categories, illustrating that 29.9 39.8 % of the

890 Training & Testing Distance (m) 350 300 250 200 150 High-intensity running=0.139x+49.96 R 2 =0.299; SEE=56.5 Elevated MP=0.058x+44.43 R 2 =0.398; SEE=18.9 100 50 Maximal MP=0.48x+5.77 R 2 =0.310; SEE=18.8 0 500 800 1100 1400 1700 Yo-Yo IRT1(m) Fig. 1 Scatterplot between Yo-Yo IRT1 with high-intensity running (filled diamonds), elevated metabolic power distance (open squares) and maximal metabolic power distance (grey triangles). variance of these locomotor and metabolic power metrics are accounted for by Yo-Yo IRT1 distance (p 0.007). Locomotor demands: The absolute total and high-intensity distances were greater for the International players than Developmental players. The relative distances for high-intensity and sprinting were also greater for International players. There were no differences for the absolute or relative amounts of low- or moderate-intensity distance between groups. Peak speed achieved was also lower in Developmental players. Metabolic power demands: Distances in high, elevated and maximal metabolic power categories were greater during International matches, whereas the low and intermediate categories were similar between groups. No group differences were observed for mean power or energy cost. Heart rate demands: Duration within the 3 heart rate categories, and consequently TRIMP, was similar between groups. However, mean and peak heart rate were lower for International players than Developmental players. Discussion The current data supports and expands upon previous findings that indicate elite female sevens players cover more total and highintensity distance than lower standard players [34]. The relative duration spent within various heart rate zones is also in alignment with elite players [34]. We uniquely provide an initial description of the metabolic power characteristics, revealing a sizeable developmental gap especially for elevated and maximal efforts. Metabolic power is a relatively new application to motion analysis research and has received attention in other field sports [13, 14]. To our knowledge this is the first study to describe the metabolic power demands for women s sevens matches. No differences were observed for distances in low and intermediate metabolic power categories; however considerable gaps were identified for high, elevated and maximal intensity efforts between standards and are reflective of the differences for highintensity running and sprint distances. The mean metabolic power values are comparable to men s rugby league matches (8.2 9.0 W kg 1 ) [25] yet substantially lower than Australian Rules Football (9.2 10.9 W kg 1 ) [6]. These preliminary findings suggest that match demands vary across different rugby codes. The differences are possibly dependent on the size of the field, which consequently impacts the ability to perform longer, uninterrupted runs or by having more events with rapid acceleration/deceleration. The energetic cost was nearly 1.0 kj kg 1 higher in the International group; however the overall energetic demand was substantially lower than reports from other sports and a direct result of the short match duration in sevens. The benefit of metabolic-power-derived metrics beyond velocitydependent parameters is the integration of acceleration and deceleration events, thus providing sport scientists an additional layer of information that could potentially be used to improve daily training plans (e. g., volume and intensity of agility drills to mimic match demands). However, the validity and reliability of metabolic power from microtechnology has not yet been investigated and so caution is warranted regarding the true impact these parameters might possess for practitioners and coaches. Total distance was 17 % greater (~215 m) for International players than the Developmental group and was largely accounted for by more high-intensity (71 %) and sprinting distances (125 %). Our findings are in agreement with Portillo et al. [34] who reported 20 % greater total distance (~280 m) as well as more distances above 14 k h 1 (38 %), 18 k h 1 (124 %) and 20 k h 1 (153 %) from the Spanish women s national team than a group of amateur players during sevens matches. Taken together, these findings indicate that 75 77 % of the difference in total distance is the result of higher intensity movement demands. The general lack of distinction for low and moderate-intensity distances between standards highlights the need for practitioners to focus on improving the physiological capacity to perform movements above 14 16 k h 1 for elite level players. Yo-Yo IRT1 performance accounted for nearly 30 % of the variance of high-intensity running (16 20 k h 1 ) suggesting that improving IRT1 distance might have a beneficial impact on this particular metric during women s sevens matches. However, longitudinal intervention studies with this population are needed to determine the impact of targeted training regimens designed to improve aerobic capabilities and subsequent changes to moderate- and high-intensity running in matches for developmental as well as elite female rugby players. Sprinting ability is often considered an important performance characteristic and routinely assessed in team sports. Maximum sprint velocity in the International players was similar to values reported in high-level female soccer players [43] and greater than the Development group. Peak match velocity for International players exceeded the Developmental group by nearly 2 k h 1 and supports the findings from Portillo et al. [34] who reported greater peak match velocity in national team players (24 25 k h 1 ) than an amateur team (21 22 k h 1 ). Whether these developmental differences for maximum and peak sprint speed are the result of superior training or selection bias within female squads is unknown. Both groups in the current study had peak sprint velocities during matches that were slightly lower (3 5 %) than maximum testing values. This is inconsistent with youth female field hockey players whose peak sprint velocity was 12 15 % lower than maximum sprint velocity [44]. These discrepant observations are likely due to the biomechanical limitations of carrying a stick and the lack of opportunity to cover longer distances (e. g., > 25 30 m) while sprinting in field hockey matches. Collectively the evidence indicates high-level women s sevens players are required to perform a small number of sprints

Training & Testing 891 during matches (~5 6 per match) [34, 39] but those events are likely to require near maximum effort. Quantification of heart rate demands is common in team sports; however no single technique is universally agreed upon. An alternative TRIMP has been specifically developed for use with team sports and incorporates physiological anchors with exponential weighting factors [37]. Using this approach revealed similar TRIMP scores between standards a result of both groups spending a large proportion of match time (87 93 %) above 80 % maximal heart rate. Indeed sevens matches will tax the aerobic system as evidenced by mean heart rate values of 89 % and 93 % of maximum for the International and Developmental players, respectively. The absolute and relative heart rate values observed in the current cohort of athletes is similar to previous reports in women s sevens [34, 39]. However Portillo et al. [34] demonstrated greater mean and maximal heart rate in Spanish national team players than amateur athletes the distances and demands seem similar to our findings so the contrasting results are not fully understood. Despite the similar duration of time spent in each heart rate zone, the International players had lower peak and mean heart rate values than Developmental players. This is likely attributable to the greater YoYo IRT1 scores observed in the International players since Mohr and Krustrup [29] demonstrated a lower proportion of heart rate maximum achieved during a submaximal (6 min) YoYo IRT1 test for higher ranking soccer teams. Rugby sevens tournaments have teams compete in 2 3 matches per day over 2 days; thus consideration of the cumulative demands performed during these scenarios is valuable for the preparation to optimize physical readiness. There are several limitations to this study that should be recognized. First, the use of GPS technology for the determination of metabolic power has not yet been validated. DiPrampero et al. [8] and Osgnach et al. [32] used sampling frequencies of 35 Hz and 25 Hz, respectively; however both studies used low-pass filtering during post-processing (specific frequency not indicated) that is likely similar to the GPS sampling frequency. Thus the metabolicpower-derived outcomes from GPS technology could be considered reasonably accurate but certainly require validation studies to be performed before definitive conclusions are reached. Second, collisions have been quantified in men s Rugby sevens [38] and distinguish between successful and less successful rugby league teams [22]. To the authors knowledge no study has quantified the energetic cost of collisions but this could elevate the demands of matches, so the overall energetic demands presented in this study might be underestimated. Third, limitations of GPS technology to assess sprinting have been reported [16, 27]; however greater collection frequency (5 Hz vs. 1 Hz) enhances reliability and validity [23]. Waldron et al. [47] reported coefficients of variation < 10 %, along with good reliability ( < 2.5 %), for distance and velocity during 10-, 20-, and 30-m sprints when using the same 5-Hz SPI-Pro technology (GPSports, Canberra, Australia) that was used in the current study. Nonetheless, the systemic underestimation of high-speed and sprint distance and velocity for 5-Hz GPS [47] suggests that the outcomes from the current study are the minimum for what female rugby sevens players would perform during matches. Finally, despite the growing popularity of Rugby Sevens because of its inclusion in the 2016 Olympic Games, a specific developmental pathway for this rugby code has not yet been fully established. This notable gap in player development could have an impact on the magnitude of observed differences between the standards in the current study. Conclusions Developmental distinctions were observed for locomotor, heart rate and metabolic power demands. High-intensity running accounted only for 15 25 % of total distance covered, however the majority of time was spent above 80 % maximum heart rate. The outcomes from this study support previous findings and can be collectively utilized by sport organizations and sport scientists to help establish appropriate training plans across standards as well as determine player readiness to handle the physical demands of higher standards of play. Specifically, the developmental differences highlight that lower-standard players need improved intermittent fitness and sprint speed in order to play at a higher standard. Training designed to improve Yo-Yo IRT1 could allow more external work to be performed while simultaneously attenuating internal (heart rate) demands. Acknowledgements This study was supported in part by a grant from the Research Program in Applied Sport Sciences from the Ministry of Tourism, Culture and Sport (Ontario, Canada) and funding from Own The Podium (Canada). Thanks are extended to the athletes for their participation as well as Rugby Canada and the coaches for their support. Thanks to Devon Frayne for his helpful comments to the manuscript. Conflict of interest: The authors have no conflicts of interest to declare. References 1 Andersson HA, Randers MB, Heiner-Moller A, Krustrup P, Mohr M. Elite female soccer players perform more high-intensity running when playing in international games compared with domestic league games. J Strength Cond Res 2010; 24: 912 919 2 Austin D, Gabbett T, Jenkins D. The physical demands of Super 14 rugby union. J Sci Med Sport 2011; 14: 259 263 3 Banister EW. Modeling elite athletic performance. In: MacDougall JD, Wenger HA, Green HJ (eds.). Physiological testing of the high-performance athlete. 2 nd ed. Champaign: Human Kinetics, 1991; 403 422 4 Bradley PS, Vescovi JD. Velocity thresholds for women s soccer matches: sex specificity dictates high-speed running and sprinting thresholds Female Athletes in Motion (FAiM). Int J Sports Physiol Perf 2014 5 Castagna C, Impellizzeri FM, Chamari K, Carlomagno D, Rampinini E. Aerobic fitness and yo-yo continuous and intermittent tests performances in soccer players: a correlation study. J Strength Cond Res 2006; 20: 320 325 6 Coutts AJ, Kempton T, Sullivan C, Bilsborough J. Metabolic power and energetic costs of professional Australian Football match-play. J Sci Med Sport 2014 7 Deprez D, Vaeyens R, Coutts AJ, Lenoir M, Philippaerts R. Relative age effect and Yo-Yo IR1 in youth soccer. Int J Sports Med 2012; 33: 987 993 8 di Prampero PE, Fusi S, Sepulcri L, Morin JB, Belli A, Antonutto G. Sprint running: a new energetic approach. J Exp Biol 2005; 208: 2809 2816 9 Dwyer DB, Gabbett TJ. Global positioning system data analysis: velocity ranges and a new definition of sprinting for field sport athletes. J Strength Cond Res 2012; 26: 818 824 10 Gabbett T, Kelly J, Pezet T. Relationship between physical fitness and playing ability in rugby league players. J Strength Cond Res 2007; 21: 1126 1133 11 Gabbett TJ, Seibold AJ. Relationship between tests of physical qualities, team selection, and physical match performance in semiprofessional rugby league players. J Strength Cond Res 2013; 27: 3259 3265 12 Gabbett TJ, Stein JG, Kemp JG, Lorenzen C. Relationship between tests of physical qualities and physical match performance in elite rugby league players. Strength Cond Res 2013; 27: 1539 1545

892 Training & Testing 13 Gaudino P, Iaia FM, Alberti G, Hawkins RD, Strudwick AJ, Gregson W. Systematic bias between running speed and metabolic power data in elite soccer players: influence of drill type. Int J Sports Med 2014; 35: 489 493 14 Gaudino P, Iaia FM, Alberti G, Strudwick AJ, Atkinson G, Gregson W. Monitoring training in elite soccer players: systematic bias between running speed and metabolic power data. Int J Sports Med 2013; 34: 963 968 15 Granatelli G, Gabbett TJ, Briotti G, Padulo J, Buglione A, D Ottavio S, Ruscello BM. Match analysis and temporal patterns of fatigue in rugby sevens. J Strength Cond Res 2014; 28: 728 734 16 Gray AJ, Jenkins D, Andrews MH, Taaffe DR, Glover ML. Validity and reliability of GPS for measuring distance travelled in field-based team sports. J Sports Sci 2010; 28: 1319 1325 17 Harley JA, Barnes CA, Portas M, Lovell R, Barrett S, Paul D, Weston M. Motion analysis of match-play in elite U12 to U16 age-group soccer players. J Sports Sci 2010; 28: 1391 1397 18 Harriss DJ, Atkinson G. Ethical standards in sport and exercise science research: 2014 update. Int J Sports Med 2013; 34: 1025 1028 19 Higham DG, Pyne DB, Anson JM, Eddy A. Movement patterns in rugby sevens: effects of tournament level, fatigue and substitute players. J Sci Med Sport 2012; 15: 277 282 20 Higham DG, Pyne DB, Anson JM, Eddy A. Physiological, anthropometric, and performance characteristics of rugby sevens players. Int J Sports Physiol Perf 2013; 8: 19 27 21 Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 2009; 41: 3 13 22 Hulin BT, Gabbett TJ, Kearney S, Corvo A. Physical demands of matchplay in successful and less-successful elite rugby league teams. Int J Sports Physiol Perf 2014 23 Jennings D, Cormack S, Coutts AJ, Boyd L, Aughey RJ. The validity and reliability of GPS units for measuring distance in team sport specific running patterns. Int J Sports Physiol Perform 2010; 5: 328 341 24 Jennings DH, Cormack SJ, Coutts AJ, Aughey RJ. International field hockey players perform more high-speed running than national-level counterparts. J Strength Cond Res 2012; 26: 947 952 25 Kempton T, Sirotic AC, Rampinini E, Coutts AJ. Metabolic Power Demands of Rugby League Match-Play. Int J Sports Physiol Perf 2014 26 Krustrup P, Mohr M, Amstrup T, Rysgaard T, Johansen J, Steensberg A, Pedersen PK, Bangsbo J. The yo-yo intermittent recovery test: physiological response, reliability, and validity. Med Sci Sports Exerc 2003; 35: 697 705 27 Macleod H, Morris J, Nevill A, Sunderland C. The validity of a nondifferential global positioning system for assessing player movement patterns in field hockey. J Sports Sci 2009; 27: 121 128 28 Markovic G, Dizdar D, Jukic I, Cardinale M. Reliability and factorial validity of squat and countermovement jump tests. J Strength Cond Res 2004; 18: 551 555 29 Mohr M, Krustrup P. Yo-Yo intermittent recovery test performances within an entire football league during a full season. J Sports Sci 2014; 32: 315 327 30 Moir G, Button C, Glaister M, Stone MH. Influence of familiarization on the reliability of vertical jump and acceleration sprinting performance in physically active men. J Strength Cond Res 2004; 18: 276 280 31 Moir G, Shastri P, Connaboy C. Intersession reliability of vertical jump height in women and men. J Strength Cond Res 2008; 22: 1779 1784 32 Osgnach C, Poser S, Bernardini R, Rinaldo R, di Prampero PE. Energy cost and metabolic power in elite soccer: a new match analysis approach. Med Sci Sports Exerc 2010; 42: 170 178 33 Petersen C, Pyne D, Portus M, Dawson B. Validity and reliability of GPS units to monitor cricket-specific movement patterns. Int J Sports Physiol Perf 2009; 4: 381 393 34 Portillo J, Gonzalez-Rave JM, Juarez D, Garcia JM, Suarez-Arrones L, Newton RU. Comparison of running characteristics and heart rate response of international and national female rugby sevens players during competitive matches. J Strength Cond Res 2014; 28: 2281 2289 35 Ross A, Gill N, Cronin J. Match analysis and player characteristics in rugby sevens. Sports Med 2014; 44: 357 367 36 Seiler KS, Kjerland GO. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an optimal distribution? Scand J Med Sci Sports 2006; 16: 49 56 37 Stagno KM, Thatcher R, van Someren KA. A modified TRIMP to quantify the in-season training load of team sport players. J Sports Sci 2007; 25: 629 634 38 Suarez-Arrones L, Arenas C, Lopez G, Requena B, Terrill O, Mendez- Villanueva A. Positional differences in match running performance and physical collisions in men rugby sevens. Int J Sports Physiol Perf 2014; 9: 316 323 39 Suarez-Arrones L, Nunez FJ, Portillo J, Mendez-Villanueva A. Match running performance and exercise intensity in elite female rugby sevens. J Strength Cond Res 2012; 26: 1858 1862 40 Suarez-Arrones LJ, Nunez FJ, Portillo J, Mendez-Villanueva A. Running demands and heart rate responses in men rugby sevens. J Strength Cond Res 2012; 26: 3155 3159 41 Veale JP, Pearce AJ, Carlson JS. The Yo-Yo Intermittent Recovery Test (Level 1) to discriminate elite junior Australian football players. J Sci Med Sport 2010; 13: 329 331 42 Vescovi JD. Sprint profile of professional female soccer players during competitive matches: Female Athletes in Motion (FAiM) study. J Sports Sci 2012; 30: 1259 1265 43 Vescovi JD. Sprint speed characteristics of high-level American female soccer players: Female Athletes in Motion (FAiM) study. J Sci Med Sport 2012; 15: 474 478 44 Vescovi JD. Impact of maximum speed on sprint performance during high-level youth female field hockey matches: Female Athletes in Motion (FAiM) Study. Int J Sports Physiol Perf 2014; 9: 621 626 45 Vincent WJ. Statistics in kinesiology. 2 nd ed. Champaign: Human Kinetics, 1999 46 Waldron M, Twist C, Highton J, Worsfold P, Daniels M. Movement and physiological match demands of elite rugby league using portable global positioning systems. J Sports Sci 2011; 29: 1223 1230 47 Waldron M, Worsfold P, Twist C, Lamb K. Concurrent validity and test-retest reliability of a global positioning system (GPS) and timing gates to assess sprint performance variables. J Sports Sci 2011; 29: 1613 1619 48 White AD, MacFarlane N. Time-on-pitch or full-game GPS analysis procedures for elite field hockey? Int J Sports Physiol Perf 2013; 8: 549 555 49 Witte TH, Wilson AM. Accuracy of non-differential GPS for the determination of speed over ground. J Biomech 2004; 37: 1891 1898