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This study examines differences in weekly load between the first (FT) and the under 19 team (U19) within a professional football setting. Data were collected in 11 FT and 9 U19 players (2016-2017 season). FT data was divided into weeks with (FT-M1) or without (FT-M0) a mid-week match. Indicators were total distance (TD) and TD at 12-15, 15-20, 20-25 and >25 km‧h-1 and were analysed as external load (m), intensity (m‧min-1) and load monotony (a.u.). TD-based load was higher for U19 compared to FT-M0 (very likely moderate) and FT-M1 (likely large). Differences at higher velocities were substantially less (trivial to possibly small), with TD >25 km‧h-1 being lower than FT-M0 (very likely moderate) and FT-M1 (likely small). All intensity indicators were lower for U19 (likely small to almost certainly large). Load monotony was higher compared to FT-M1 (possibly small to almost certainly very large). Compared to FT-M0, monotony was higher for TD (possibly very large) and TD >25 km‧h‑1 (possibly moderate) but lower for TD 12-15 (possibly small) and 15-20 km‧h‑1 (likely moderate). So, despite higher weekly external loads at low velocity for elite youth players, external intensity and load variation increases when these players may transition to professional football. ispartof: Science and Medicine in Football vol:5 issue:1 ispartof: location:England status: published

Purpose: Using elite youth soccer players’ maximal sprinting speeds collected from a criterion and non-criterion measure, we demonstrate how expert practitioner opinion can be used to determine measurement validity. Methods: Expert soccer practitioners (n = 50) from around the world were surveyed on issues relating to the measurement of maximal sprinting speed and 12 elite youth soccer players performed two maximal 40 m sprints, measured by 10-Hz GPS units (non-criterion) and a 100-Hz Laser (criterion). Setting statistical equivalence bounds as practitioner opinion of the practically acceptable amount of measurement error for maximal sprinting speed, we assessed agreement between GPS and Laser. Results: Survey respondents reported a combination of methods for deriving maximal sprinting speed (tests, training, match) but most did not assess system validity. Median value of the practically acceptable amount of measurement error for maximal sprinting speed was 0.20 m/s. Maximal sprinting speed was 8.79 ± 0.33 m/s (Laser) and 8.75 ± 0.32 m/s (GPS), and the mean difference was 0.04 (90% confidence interval −0.03 to 0.11) m/s. Using the median acceptable amount of measurement error, we set our lower and upper equivalence bounds to −0.10 m/s and +0.10 m/s, respectively. Equivalence testing showed Laser and GPS as likely equivalent measures (probability 93.7%). Conclusion: Using expert-informed equivalence thresholds represents a novel way to assess validity in sports performance research. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

© 2017 Human Kinetics, Inc. Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on "Monitoring Athlete Training Loads-The Hows and the Whys" was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and-medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.

Objectives To investigate the impact of physical efforts performed in the period preceding activity as a potential risk factor of muscle injury during match-play within a sample of professional soccer players. Design Observational cohort study. Methods Match load (running [>14.4–19.8 km/h], high-speed running [>19.8–25.2 km/h], sprinting [>25.2 km/h], leading and explosive sprint type) averaged in 1-min and 5-min periods prior to an event or non event for 29 professional outfield soccer players. Conditional logistic and Poisson regression models estimated the relationship between load and injury for a 2 within-subject standard deviation in match load or 1-action increment in the number of sprinting activities, respectively. Associations were deemed beneficial or harmful based on non-overlap of the 95% confidence intervals against thresholds of 0.90 and 1.11, respectively. Results An increment in sprinting distance [+2-SDs = 11 m] covered over a 1-min period (odds ratio [OR]: 1.22, 95%CI, 1.12 to 1.33) increased the odds of muscle injury. Conclusions Our study provides novel exploratory evidence that the volume of sprinting during competitive soccer match-play has a harmful association with muscle injury occurrence.

This study investigated the effects of successive matches on match-running in elite under-23 soccer players during an international tournament. Match-running data was collected using a semi-automated multi-camera tracking system during an international under-23 tournament from all participating outfield players. Players who played 100% of all group stage matches were included (3 matches separated by 72 h, n = 44). Differences in match-running performance between matches were identified using a generalised linear mixed model. There were no clear effects for total, walking, jogging, running, high-speed running and sprinting distance between matches 1 and 3 (effect size (ES); -0.32 to 0.05). Positional analysis found that sprint distance was largely maintained from matches 1 to 3 across all positions. Attackers had a moderate decrease in total, jogging and running distance between matches 1 and 3 (ES; -0.72 to -0.66). Classifying players as increasers or decreasers in match-running revealed that match-running changes are susceptible to individual differences. Sprint performance appears to be maintained over successive matches regardless of playing position. However, reductions in other match-running categories vary between positions. Changes in match-running over successive matches affect individuals differently; thus, players should be monitored on an individual basis.

© 2017 Human Kinetics, Inc. Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance.

Introduction: Afferent information from exercising muscle contributes to the sensation of exercise-induced muscle pain. Transcutaneous electrical nerve stimulation (TENS) delivers low–voltage electrical currents to the skin, inhibiting nociceptive afferent information. The use of TENS in reducing perceptions of exercise-induced pain has not yet been fully explored. This study aimed to investigate the effect of TENS on exercise-induced muscle pain, pacing strategy, and performance during a 5-km cycling time trial (TT). Methods: On three separate occasions, in a single-blind, randomized, and cross-over design, 13 recreationally active participants underwent a 30-min TENS protocol, before performing a 5-km cycling TT. TENS was applied to the quadriceps prior to exercise under the following conditions; control (CONT), placebo with sham TENS application (PLAC), and an experimental condition with TENS application (TENS). Quadriceps fatigue was assessed with magnetic femoral nerve stimulation assessing changes in potentiated quadriceps twitch force at baseline, pre and post exercise. Subjective scores of exertion, affect and pain were taken every 1-km. Results: During TTs, application of TENS did not influence pain perceptions (P = 0.68, ηp2 = 0.03). There was no significant change in mean power (P = 0.16, ηp2 = 0.16) or TT duration (P = 0.17, ηp2 = 0.14), although effect sizes were large for these two variables. Changes in power output were not significant but showed moderate effect sizes at 500-m (ηp2 = 0.10) and 750-m (ηp2 = 0.10). Muscle recruitment as inferred by electromyography data was not significant, but showed large effect sizes at 250-m (ηp2 = 0.16), 500-m (ηp2 = 0.15), and 750-m (ηp2 = 0.14). This indicates a possible effect for TENS influencing performance up to 1-km. Discussion: These findings do not support the use of TENS to improve 5-km TT performance.

Purpose: To quantify the effect of acute hypoxia on muscle oxygenation and power during simulated team-sport running. Methods: Seven individuals performed repeated and single sprint efforts, embedded in a simulated team-sport running protocol, on a non-motorized treadmill in normoxia (sea-level), and acute normobaric hypoxia (simulated altitudes of 2,000 and 3,000 m). Mean and peak power was quantified during all sprints and repeated sprints. Mean total work, heart rate, blood oxygen saturation, and quadriceps muscle deoxyhaemoglobin concentration (assessed via near-infrared spectroscopy) were measured over the entire protocol. A linear mixed model was used to estimate performance and physiological effects across each half of the protocol. Changes were expressed in standardized units for assessment of magnitude. Uncertainty in the changes was expressed as a 90% confidence interval and interpreted via non-clinical magnitude-based inference. Results: Mean total work was reduced at 2,000 m (−10%, 90% confidence limits ±6%) and 3,000 m (−15%, ±5%) compared with sea-level. Mean heart rate was reduced at 3,000 m compared with 2,000 m (−3, ±3 min−1) and sea-level (−3, ±3 min−1). Blood oxygen saturation was lower at 2,000 m (−8, ±3%) and 3,000 m (−15, ±2%) compared with sea-level. Sprint mean power across the entire protocol was reduced at 3,000 m compared with 2,000 m (−12%, ±3%) and sea-level (−14%, ±4%). In the second half of the protocol, sprint mean power was reduced at 3,000 m compared to 2,000 m (−6%, ±4%). Sprint mean peak power across the entire protocol was lowered at 2,000 m (−10%, ±6%) and 3,000 m (−16%, ±6%) compared with sea-level. During repeated sprints, mean peak power was lower at 2,000 m (−8%, ±7%) and 3,000 m (−8%, ±7%) compared with sea-level. In the second half of the protocol, repeated sprint mean power was reduced at 3,000 m compared to 2,000 m (−7%, ±5%) and sea-level (−9%, ±5%). Quadriceps muscle deoxyhaemoglobin concentration was lowered at 3,000 m compared to 2,000 m (−10, ±12%) and sea-level (−11, ±12%). Conclusions: Simulated team-sport running is impaired at 3,000 m compared to 2,000 m and sea-level, likely due to a higher muscle deoxygenation.

The question of whether altitude training can enhance subsequent sea-level performance has been well investigated over many decades. However, research on this topic has focused on athletes from individual or endurance sports, with scant number of studies on team-sport athletes. Questions that need to be answered include whether this type of training may enhance team-sport athlete performance, when success in team-sport is often more based on technical and tactical ability rather than physical capacity per se. This review will contrast and compare athletes from two sports representative of endurance (cycling) and team-sports (soccer). Specifically, we draw on the respective competition schedules, physiological capacities, activity profiles and energetics of each sport to compare the similarities between athletes from these sports and discuss the relative merits of altitude training for these athletes. The application of conventional live-high, train-high; live-high, train-low; and intermittent hypoxic training for team-sport athletes in the context of the above will be presented. When the above points are considered, we will conclude that dependent on resources and training objectives, altitude training can be seen as an attractive proposition to enhance the physical performance of team-sport athletes without the need for an obvious increase in training load.

Objectives We investigated the effect of high altitude on the match activity profile of elite youth high altitude and sea level residents. Methods Twenty Sea Level (Australian) and 19 Altitude-resident (Bolivian) soccer players played five games, two near sea level (430 m) and three in La Paz (3600 m). Match activity profile was quantified via global positioning system with the peak 5 min period for distance ((D5peak)) and high velocity running (>4.17 m/s, HIVR5peak); as well as the 5 min period immediately subsequent to the peak for both distance (D5sub) and high-velocity running (HIVR5sub) identified using a rolling 5 min epoch. The games at 3600 m were compared with the average of the two near sea-level games. Results The total distance per minute was reduced by a small magnitude in the first match at altitude in both teams, without any change in low-velocity running. There were variable changes in HiVR, D5peak and HiVR5peak from match to match for each team. There were within-team reductions in D5peak in each game at altitude compared with those at near sea level, and this reduction was greater by a small magnitude in Australians than Bolivians in game 4. The effect of altitude on HiVR5peak was moderately lower in Australians compared with Bolivians in game 3. There was no clear difference in the effect of altitude on maximal accelerations between teams. Conclusions High altitude reduces the distance covered by elite youth soccer players during matches. Neither 13 days of acclimatisation nor lifelong residence at high altitude protects against detrimental effects of altitude on match activity profile. Refereed/Peer-reviewed