The aim of this study was to investigate the effectiveness of a caffeinated energy drink to enhance physical performance in elite junior tennis players. In 2 different sessions separated by 1 wk, 14 young (16 ± 1 y) elite-level tennis players ingested 3 mg caffeine per kg body mass in the form of an energy drink or the same drink without caffeine (placebo). After 60 min, participants performed a handgrip-strength test, a maximal-velocity serving test, and an 8 × 15-m sprint test and then played a simulated singles match (best of 3 sets). Instantaneous running speed during the matches was assessed using global positioning (GPS) devices. Furthermore, the matches were videotaped and notated afterward. In comparison with the placebo drink, the ingestion of the caffeinated energy drink increased handgrip force by ~4.2% ± 7.2% (P = .03) in both hands, the running pace at high intensity (46.7 ± 28.5 vs 63.3 ± 27.7 m/h, P = .02), and the number of sprints (12.1 ± 1.7 vs 13.2 ± 1.7, P = .05) during the simulated match. There was a tendency for increased maximal running velocity during the sprint test (22.3 ± 2.0 vs 22.9 ± 2.1 km/h, P = .07) and higher percentage of points won on service with the caffeinated energy drink (49.7% ± 9.8% vs 56.4% ± 10.0%, P = .07) in comparison with the placebo drink. The energy drink did not improve ball velocity during the serving test (42.6 ± 4.8 vs 42.7 ± 5.0 m/s, P = .49). The preexercise ingestion of caffeinated energy drinks was effective to enhance some aspects of physical performance of elite junior tennis players.
César Gallo-Salazar, Francisco Areces, Javier Abián-Vicén, Beatriz Lara, Juan José Salinero, Cristina Gonzalez-Millán, Javier Portillo, Victor Muñoz, Daniel Juarez and Juan Del Coso
Luis Suarez-Arrones, Javier Núñez, Diego Munguía-Izquierdo, Javier Portillo and Alberto Mendez-Villanueva
To examine the effects of several matches per day on running performance and cardiovascular stress in referees during a national Rugby Sevens championship.
Seven referees, who refereed 3 matches/day, were monitored by GPS during 21 matches.
Referees’ movement patterns were relatively stable from the 1st to the 2nd match, although a substantial decrease was observed in the 2nd match for maximal and average sprint distance. A substantial decrease in the number of sprints, maximal speed, walking, distance covered at medium intensity, total and >14 km/h distance covered per minute was observed in the 3rd match in comparison with the 2nd. Compared with the 1st match, in the 3rd game referees showed a substantial decrease in maximal and average sprint distance, total walking at medium intensity, distance covered >14 km/h, and high-intensity running distance. Referees exhibited a substantial decrease in average heart rate (HR), percentage of time at >70%HRmax, and percentage of time at >90%HRmax in the 2nd match compared with the 1st. Referees’ HR responses were relatively stable from the 2nd to the 3rd match except for the HR zones of 71–80%HRmax and 81–90%HRmax and performance-efficiency index (Effindex). Substantial differences were observed in the 3rd match compared with the 1st in average HR, 81–90%HRmax, >90%HRmax, and Effindex.
This study provides evidence of reduced overall running performance and pronounced reduction in high-intensity running performance during the last match in Rugby Sevens referees refereeing 3 matches in the same day.
Dean Ritchie, Will G. Hopkins, Martin Buchheit, Justin Cordy and Jonathan D. Bartlett
Training volume, intensity, and distribution are important factors during periods of return to play.
To quantify the effect of injury on training load (TL) before and after return to play (RTP) in professional Australian Rules football.
Perceived training load (RPE-TL) for 44 players was obtained for all indoor and outdoor training sessions, while field-based training was monitored via GPS (total distance, high-speed running, mean speed). When a player sustained a competition time-loss injury, weekly TL was quantified for 3 wk before and after RTP. General linear mixed models, with inference about magnitudes standardized by between-players SDs, were used to quantify effects of lower- and upper-body injury on TL compared with the team.
While total RPE-TL was similar to the team 2 wk before RTP, training distribution was different, whereby skills RPE-TL was likely and most likely lower for upper- and lower-body injury, respectively, and most likely replaced with small to very large increases in running and other conditioning load. Weekly total distance and high-speed running were most likely moderately to largely reduced for lower- and upper-body injury until after RTP, at which point total RPE-TL, training distribution, total distance, and high-speed running were similar to the team. Mean speed of field-based training was similar before and after RTP compared with the team.
Despite injured athletes’ obtaining comparable TLs to uninjured players, training distribution is different until after RTP, indicating the importance of monitoring all types of training that athletes complete.
Juan Del Coso, Javier Portillo, Juan José Salinero, Beatriz Lara, Javier Abian-Vicen and Francisco Areces
The aim of this investigation was to determine the efficacy of a caffeine-containing energy drink to improve physical performance of elite field hockey players during a game. On 2 days separated by a week, 13 elite field hockey players (age and body mass = 23.2 ± 3.9 years and 76.1 ± 6.1 kg) ingested 3 mg of caffeine per kg of body mass in the form of an energy drink or the same drink without caffeine (placebo drink). After 60 min for caffeine absorption, participants played a simulated field hockey game (2 × 25 min). Individual running pace and instantaneous speed during the game were assessed using GPS devices. The total number of accelerations and decelerations was determined by accelerometry. Compared with the placebo drink, the caffeinated energy drink did not modify the total distance covered during the game (6,035 ± 451 m and 6,055 ± 499 m, respectively; p = .87), average heart rate (155 ± 13 beats per min and 158 ± 18 beats per min, respectively; p = .46), or the number of accelerations and decelerations (697 ± 285 and 618 ± 221, respectively; p = .15). However, the caffeinated energy drink reduced the distance covered at moderate-intensity running (793 ± 135 and 712 ± 116, respectively; p = .03) and increased the distance covered at high-intensity running (303 ± 67 m and 358 ± 117 m; p = .05) and sprinting (85 ± 41 m and 117 ± 55 m, respectively; p = .02). Elite field hockey players can benefit from ingesting caffeinated energy drinks because they increase the running distance covered at high-intensity running and sprinting. Increased running distance at high speed might represent a meaningful advantage for field hockey performance.
Martin Buchheit, Yannick Cholley and Philippe Lambert
To examine in elite soccer players after traveling across 6 time zones some psychometric and physiological responses to a competitive camp in the heat.
Data from 12 elite professional players (24.6 ± 5.3 y) were analyzed. They participated in an 8-d preseason summer training camp in Asia (heat index 34.9°C ± 2.4°C). Players’ activity was collected during all training sessions and the friendly game using 15-Hz GPS. Perceived training/playing load was estimated using session rating of perceived exertion (RPE) and training/match duration. Psychometric measures of wellness were collected on awakening before, during, and after the camp using simple questionnaires. Heart-rate (HR) response to a submaximal 4-min run (12 km/h) and the ratio between velocity and force-load (accelerometer-derived measure, a marker of neuromuscular efficiency) response to four ~60-m runs (22–24 km/h) were collected before, at the end of, and after the camp.
After a large increase, the RPE:m/min ratio decreased substantially throughout the camp. There were possible small increases in perceived fatigue and small decreases in subjective sleep quality on the 6th day. There were also likely moderate (~3%) decreases in HR response to the submaximal run, both at the end of and after the camp, which were contemporary to possible small (~8%) and most likely moderate (~19%) improvements in neuromuscular efficiency, respectively.
Despite transient increases in fatigue and reduced subjective sleep quality by the end of the camp, these elite players showed clear signs of heat acclimatization that were associated with improved cardiovascular fitness and neuromuscular running efficiency.
Robert J. Aughey
Australian football (AF) is a highly intermittent sport, requiring athletes to accelerate hundreds of times with repeated bouts of high-intensity running (HIR). Players aim to be in peak physical condition for finals, with anecdotal evidence of increased speed and pressure of these games.
However, no data exists on the running demands of finals games, and therefore the aim of this study was to compare the running demands of finals to regular season games with matched players and opponents.
Player movement was recorded by GPS at 5 Hz and expressed per period of the match (rotation), for total distance, high-intensity running (HIR, 4.17-10.00 m·s-1) and maximal accelerations (2.78-10.00 m·s–2). All data was compared for regular season and finals games and the magnitude of effects was analyzed with the effect size (ES) statistic and expressed with confidence intervals.
Each of the total distance (11%; ES: 0.78 ± 0.30), high-intensity running distance (9%; ES: 0.29 ± 0.25) and number of maximal accelerations (97%; ES: 1.30 ± 0.20) increased in finals games. The largest percentage increases in maximal accelerations occurred from a commencement velocity of between 3–4 (47%; ES: 0.56 ± 0.21) and 4–5 m·s-1 (51%; ES: 0.72 ± 0.26), and with <19 s between accelerations (53%; ES: 0.63 ± 0.27).
Elite AF players nearly double the number of maximal accelerations in finals compared with regular season games. This large increase is superimposed on requirements to cover a greater total distance and spend more time at high velocity during finals games. Players can be effectively conditioned to cope with these increased demands, even during a long competitive season.
Jamie Stanley, Shaun D’Auria and Martin Buchheit
The authors examined whether changes in heart-rate (HR) variability (HRV) could consistently track adaptation to training and race performance during a 32-wk competitive season. An elite male long-course triathlete recorded resting HR (RHR) each morning, and vagal-related indices of HRV (natural logarithm of the square root of mean squared differences of successive R−R intervals [ln rMSSD] and the ratio of ln rMSSD to R−R interval length [ln rMSSD:RR]) were assessed. Daily training load was quantified using a power meter and wrist-top GPS device. Trends in HRV indices and training load were examined by calculating standardized differences (ES). The following trends in week-to-week changes were consistently observed: (1) When the triathlete was coping with a training block, RHR decreased (ES −0.38 [90% confidence limits −0.05;−0.72]) and ln rMSSD increased (+0.36 [0.71;0.00]). (2) When the triathlete was not coping, RHR increased (+0.65 [1.29;0.00]) and ln rMSSD decreased (−0.60 [0.00;−1.20]). (3) Optimal competition performance was associated with moderate decreases in ln rMSSD (−0.86 [−0.76;−0.95]) and ln rMSSD:RR (−0.90 [−0.60;−1.20]) in the week before competition. (4) Suboptimal competition performance was associated with small decreases in ln rMSSD (−0.25 [−0.76;−0.95]) and trivial changes in ln rMSSD:RR (−0.04 [0.50;−0.57]) in the week before competition. To conclude, in this triathlete, a decrease in RHR concurrent with increased ln rMSSD compared with the previous week consistently appears indicative of positive training adaptation during a training block. A simultaneous reduction in ln rMSSD and ln rMSSD:RR during the final week preceding competition appears consistently indicative of optimal performance.
Mitchell Mooney, Stuart Cormack, Brendan O’Brien and Aaron J Coutts
The purpose of this study was to determine if Yo-Yo Intermittent Recovery level 2 (Yo-Yo IR2) and the number of interchange rotations affected the match activity profile of elite Australian footballers.
Fifteen elite Australian footballers completed the Yo-Yo IR2 before the beginning of the season and played across 22 matches in which match activity profiles were measured via microtechnology devices containing a global positioning system (GPS) and accelerometer. An interchange rotation was counted when a player left the field and was replaced with another player. Yo-Yo IR2 results were further split into high and low groups.
Players match speed decreased from 1st to 4th quarter, while average-speed (m/min: P = .05) and low-speed activity (LSA, <15 km/h) per minute (LSA m/min; P = .06) significantly decreased in the 2nd half. Yo-Yo IR2 influenced the amount of m/min, high-speed running (HSR, >15 km/h) per minute (HSR m/min) and accelerometer load/min throughout the entire match. The number of interchanges significantly influenced the HSR m/min and m/min throughout the match except in the 2nd quarter. Furthermore, the low Yo-Yo IR2 group had significantly less LSA m/min in the 4th quarter than the high Yo-Yo IR2 group (92.2 vs 96.7 m/min, P = .06).
Both the Yo-Yo IR2 and number of interchanges contribute to m/min and HSR m/min produced by elite Australian footballers, affecting their match activity. However, while it appears that improved Yo-Yo IR2 performance prevents reductions in LSA m/min during a match, higher-speed activities (HSR m/min) and overall physical activity (m/min and load/min) are still reduced in the 4th quarter compared with the 1st quarter.
Courtney Sullivan, Johann C. Bilsborough, Michael Cianciosi, Joel Hocking, Justin T. Cordy and Aaron J. Coutts
To determine the physical activity measures and skill-performance characteristics that contribute to coaches’ perception of performance and player performance rank in professional Australian Football (AF).
Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill-performance measure and player-rank scores (Champion Data Rank) were provided by a commercial statistical provider. The physical-performance variables, skill involvements, and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches’ perception of performance and player rank in AF.
Stepwise multiple-regression analysis revealed that 42.2% of the variance in coaches’ perception of a player’s performance could be explained by the skill-performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min, and running bounces/min), with a small contribution from physical activity measures (accelerations/min) (adjusted R 2 = .422, F 6,282 = 36.054, P < .001). Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m/min), and peak speed (adjusted R 2 = .664, F 7,281 = 82.289, P < .001). Increased physical activity throughout a match (speed [m/min] β – 0.097 and peak speed β – 0.116) negatively affects player rank in AF.
Skill performance rather than increased physical activity is more important to coaches’ perception of performance and player rank in professional AF.
Richard Akenhead and George P. Nassis
Training load (TL) is monitored with the aim of making evidence-based decisions on appropriate loading schemes to reduce injuries and enhance team performance. However, little is known in detail about the variables of load and methods of analysis used in high-level football. Therefore, the aim of this study was to provide information on the practices and practitioners’ perceptions of monitoring in professional clubs. Eighty-two high-level football clubs from Europe, the United States, and Australia were invited to answer questions relating to how TL is quantified, how players’ responses are monitored, and their perceptions of the effectiveness of monitoring. Forty-one responses were received. All teams used GPS and heart-rate monitors during all training sessions, and 28 used rating of perceived exertion. The top-5-ranking TL variables were acceleration (various thresholds), total distance, distance covered above 5.5 m/s, estimated metabolic power, and heart-rate exertion. Players’ responses to training are monitored using questionnaires (68% of clubs) and submaximal exercise protocols (41%). Differences in expected vs actual effectiveness of monitoring were 23% and 20% for injury prevention and performance enhancement, respectively (P < .001 d = 1.0−1.4). Of the perceived barriers to effectiveness, limited human resources scored highest, followed by coach buy-in. The discrepancy between expected and actual effectiveness appears to be due to suboptimal integration with coaches, insufficient human resources, and concerns over the reliability of assessment tools. Future approaches should critically evaluate the usefulness of current monitoring tools and explore methods of reducing the identified barriers to effectiveness.