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Emma C. Neupert, Stewart T. Cotterill and Simon A. Jobson

An effective training-monitoring system (TMS) can positively influence performance through monitoring program effectiveness and reducing the risk of illness or injury. 1 However, successfully implementing a TMS can be problematic in elite sport, with issues relating to end-user buy-in and a

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Maria Francesca Piacentini and Romain Meeusen

Purpose:

This longitudinal case study evaluated the effectiveness of an online training-monitoring system to prevent nonfunctional overreaching (NFOR).

Methods:

A female master track and field athlete was followed by means of a daily online training diary (www.spartanova.com) and a weekly profile of mood state (POMS). The online diary consists of objective training data and subjective feelings reported on a 10-cm visual analog scale. Furthermore, parameters that quantify and summarize training and adaptation to training were calculated. The novelty consists in the inclusion of a specific measuring parameter tested to detect NFOR (OR score).

Results:

During track-season preparation, the athlete was facing some major personal changes, and extratraining stress factors increased. Despite the fact that training load (TL) did not increase, the or score showed a 222% and then a 997% increase compared with baseline. POMS showed a 167% increase in fatigue, a 38% decrease in vigor, a 32% increase in depression scores, and a total mood increase of 22%, with a 1-wk shift compared with the OR score. A 41% decrease in TL restored the OR score and POMS to baseline values within 10 d.

Conclusion:

The results demonstrate that immediate feedback obtained by “warning signals” to both athletes and coaches, based on individual baseline data, seems an optimal predictor of FOR/NFOR.

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Twan ten Haaf, Selma van Staveren, Danilo Iannetta, Bart Roelands, Romain Meeusen, Maria F. Piacentini, Carl Foster, Leo Koenderman, Hein A.M. Daanen and Jos J. de Koning

monitor performance do not fit in an athlete’s training schedule. Therefore, sport scientists search for training monitoring tools that are easy to perform in training practice and are objective, inexpensive, and not demanding. 3 Reaction time is a measurement that fits these requirements and has been

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Marco Cardinale and Matthew C. Varley

The need to quantify aspects of training to improve training prescription has been the holy grail of sport scientists and coaches for many years. Recently, there has been an increase in scientific interest, possibly due to technological advancements and better equipment to quantify training activities. Over the last few years there has been an increase in the number of studies assessing training load in various athletic cohorts with a bias toward subjective reports and/or quantifications of external load. There is an evident lack of extensive longitudinal studies employing objective internal-load measurements, possibly due to the cost-effectiveness and invasiveness of measures necessary to quantify objective internal loads. Advances in technology might help in developing better wearable tools able to ease the difficulties and costs associated with conducting longitudinal observational studies in athletic cohorts and possibly provide better information on the biological implications of specific external-load patterns. Considering the recent technological developments for monitoring training load and the extensive use of various tools for research and applied work, the aim of this work was to review applications, challenges, and opportunities of various wearable technologies.

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Kizzy Antualpa, Marcelo Saldanha Aoki and Alexandre Moreira

training monitoring during the HT of the rhythmic gymnasts, notably, for internal training load and well-being monitoring, followed by 4 weeks of IT, which, in turn, was followed by a 2-week TP. Training was intensified by the addition of 40% of the HT volume performed by rhythmic gymnasts. The training

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Andrea Nicolò, Marco Montini, Michele Girardi, Francesco Felici, Ilenia Bazzucchi and Massimo Sacchetti

Purpose:

Variables currently used in soccer training monitoring fail to represent the physiological demand of the player during movements like accelerations, decelerations and directional changes performed at high intensity. We tested the hypothesis that respiratory frequency (f R) is a marker of physical effort during soccer-related high-intensity exercise.

Methods:

Twelve male soccer players performed a preliminary intermittent incremental test and two shuttle-run high-intensity interval training (HIIT) protocols, in separate visits. The two HIIT protocols consisted of 12 repetitions over 9 min and differed in the work-recovery ratio (15:30s vs. 30:15s). Work rate was self-paced by participants to achieve the longest possible total distance in each HIIT protocol.

Results:

Work-phase average metabolic power was higher (P < 0.001) in the 15:30s (31.7 ± 3.0 W·kg-1) compared to the 30:15s (22.8 ± 2.0 W·kg-1). Unlike heart rate and V̇O2, f R showed a fast response to the work-recovery alternation during both HIIT protocols, resembling changes in metabolic power even at supramaximal intensities. Large correlations (P < 0.001) were observed between f R and rating of perceived exertion during both 15:30s (r = 0.87) and 30:15s (r = 0.85).

Conclusions:

Our findings suggest that f R is a good marker of physical effort during shuttle-run HIIT in soccer players. These findings have implications for monitoring training in soccer and other team sports.

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Andrea Fusco, Christine Knutson, Charles King, Richard P. Mikat, John P. Porcari, Cristina Cortis and Carl Foster

Purpose:

Although the Session RPE (sRPE) is primarily a marker of internal training load (TL), it may be sensitive to external TL determining factors such as duration and volume. Thus, sRPE could provide further information on accumulated fatigue not available from markers of internal TL. Therefore, the purpose of this study was to investigate sRPE during heavy training bouts at relatively constant intensity.

Methods:

Eleven university swimmers performed a high-volume training session consisting of 4x10x100-yard (4x10x91.4-m). Repetition lap time and heart rate (HR) were measured for each repetition and averaged for each set. Blood lactate concentration ([HLa]) was measured after each set. At the end of each set, a 10-minute rest period was allowed, during which sRPE values were obtained, as if the training bout had ended.

Results:

There were no differences between sets for lap time (p=.096), HR (p=.717) and [HLa] (p=.466), suggesting that the subjects were working at the same external and internal intensity. There was an increase (p=.0002) in sRPE between sets (first: 4±1.2; second: 5±1.3; third: 7±1.3; fourth: 8±1.5), suggesting that even when maintaining the same intensity, the perception of the entire workload increased with duration.

Conclusions:

Increases in duration, although performed with a consistent internal and external intensity, influences sRPE. These findings support the concept that sRPE may provide additional information on accumulated fatigue not available from other markers of TL.

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Blaine E. Arney, Reese Glover, Andrea Fusco, Cristina Cortis, Jos J. de Koning, Teun van Erp, Salvador Jaime, Richard P. Mikat, John P. Porcari and Carl Foster

Purpose: The session rating of perceived exertion (sRPE) is a well-accepted method of monitoring training load in athletes in many different sports. It is based on the category-ratio (0–10) RPE scale (BORG-CR10) developed by Borg. There is no evidence how substitution of the Borg 6–20 RPE scale (BORG-RPE) might influence the sRPE in athletes. Methods: Systematically training, recreational-level athletes from a number of sport disciplines performed 6 randomly ordered, 30-min interval-training sessions, at intensities based on peak power output (PPO) and designed to be easy (50% PPO), moderate (75% PPO), or hard (85% PPO). Ratings of sRPE were obtained 30 min postexercise using either the BORG-CR10 or BORG-RPE and compared for matched exercise conditions. Results: The average percentage of heart-rate reserve was well correlated with sRPE from both BORG-CR10 (r = .76) and BORG-RPE (r = .69). The sRPE ratings from BORG-CR10 and BORG-RPE were very strongly correlated (r = .90) at matched times. Conclusions: Although producing different absolute numbers, sRPE derived from either the BORG-CR10 or BORG-RPE provides essentially interchangeable estimates of perceived exercise training intensity.

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Shaun J. McLaren, Michael Graham, Iain R. Spears and Matthew Weston

Purpose:

To investigate the sensitivity of differential ratings of perceived exertion (dRPE) as measures of internal load.

Methods:

Twenty-two male university soccer players performed 2 maximal incremental-exercise protocols (cycle, treadmill) on separate days. Maximal oxygen uptake (V̇O2max), maximal heart rate (HRmax), peak blood lactate concentration (B[La]peak), and the preprotocol-to-postprotocol change in countermovement-jump height (ΔCMJH) were measured for each protocol. Players provided dRPE (CR100) for breathlessness (RPE-B) and leg-muscle exertion (RPE-L) immediately on exercise termination (RPE-B0, RPE-L0) and 30 min postexercise (RPE-B30, RPE-L30). Data were analyzed using magnitude-based inferences.

Results:

There were clear between-protocols differences for V̇O2max (cycle 46.5 ± 6.3 vs treadmill 51.0 ± 5.1 mL · kg−1 · min−1, mean difference –9.2%; ±90% confidence limits 3.7%), HRmax (184.7 ± 12.7 vs 196.7 ± 7.8 beats/min, –6.0%; ±1.7%), B[La]peak (9.7 ± 2.1 vs 8.5 ± 2.0 mmol/L, 15%; ±10%), and ΔCMJH (–7.1 ± 4.2 vs 0.6 ± 3.6 cm, –23.2%; ±5.4%). Clear between-protocols differences were recorded for RPE-B0 (78.0 ± 11.7 vs 94.7 ± 9.5 AU, –18.1%; ±4.5%), RPE-L0 (92.6 ± 9.7 vs 81.3 ± 14.1 AU, 15.3%; ±7.6%), RPE-B30 (70 ± 11 vs 82 ± 13 AU, –13.8%; ±7.3%), and RPE-L30 (86 ± 12 vs 65 ± 19 AU, 37%; ±17%). A substantial timing effect was observed for dRPE, with moderate to large reductions in all scores 30 min postexercise compared with scores collected on exercise termination.

Conclusion:

dRPE enhance the precision of internal-load measurement and therefore represent a worthwhile addition to training-load-monitoring procedures.

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David B. Pyne, Matt Spencer and Iñigo Mujika

One of the challenges for sports scientists working in football is to balance the needs for routine fitness testing with daily fatigue and well-being monitoring to best manage the physical preparation of players. In this commentary, the authors examine contemporary issues of fitness testing in football to identify ways of improving the value of routine testing and monitoring. A testing program must be well planned and organized to ensure that the results are useful. Different tests can be employed for younger and older players. A rigorous approach to analysis and interpretation of results is desirable, and database management must address both short- and long-term requirements of players, staff, and programs.