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Pierpaolo Sansone, Alessandro Ceravolo, and Antonio Tessitore

Purpose: To quantify external, internal, and perceived training loads and their relationships in youth basketball players across different playing positions. Methods: Fourteen regional-level youth male players (age: 15.2 [0.3] y) were monitored during team-based training sessions across 10 in-season weeks. The players were monitored with BioHarness-3 devices, to measure external (Impulse Load, in Newtons per second) and internal (summated-heart-rate zones [SHRZ], in arbitrary units [AU]) loads, and with the session rating of perceived exertion (sRPE, in AU) method to quantify perceived training load. Multiple linear mixed models were performed to compare training loads between playing positions (backcourt and frontcourt). Repeated-measures correlations were performed to assess the relationships between the load models, for all players and within playing positions. Results: External load (backcourt: 13,599 [2260] N·s; frontcourt: 14,934 [2173] N·s) and sRPE (backcourt: 345 [132] AU; frontcourt: 505 [158] AU) were higher in the frontcourt (P < .05, effect size: moderate), while SHRZ was similar between positions (backcourt: 239 [45] AU; frontcourt: 247 [43] AU) (P > .05; effect size: trivial). The correlations were as follows: large between the external load and SHRZ (r = .57, P < .001), moderate between SHRZ and sRPE (r = .45, P < .001), and small between the external load and sRPE (r = .26, P = .02). The correlation magnitudes were equivalent for external load–SHRZ (large) and SHRZ–sRPE (moderate) across positions, but different for the external load–sRPE correlation (small in backcourt; moderate in frontcourt). Conclusions: In youth basketball, small–large commonalities were found between the training dose (external load) and players’ responses (internal and perceived loads). Practitioners should carefully manage frontcourt players’ training loads because they accumulate greater external and perceived loads than backcourt  players do.

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Suzanna Russell, David G. Jenkins, Shona L. Halson, Laura E. Juliff, Mark J. Connick, and Vincent G. Kelly

Purpose: Mental fatigue is emerging as an important consideration for elite sporting performance, yet it is rarely monitored. The present study assessed changes in mental fatigue in professional team-sport athletes across 2 seasons and examined the relationship between mental fatigue and other athlete self-report measures of well-being. Methods: Elite netballers contracted to all teams competing in Australia’s premier professional netball competition during the 2018 and 2019 seasons (N = 154) participated. Using 5-point Likert scales, mental fatigue, fatigue (physical), tiredness, sleep quality, stress, mood, and motivation were assessed daily across 2 seasons composed of 14 round and finals series. Results: The ratings of mental fatigue significantly changed during both seasons. In 2018, lower ratings of mental fatigue were reported in round 1 versus 3, 4, 6, 8, and 14; round 7 versus 6; and round 6 versus 10 (P < .05). In 2019, lower ratings of mental fatigue were identified for round 1 versus 3, 9, 10 to 14, and semifinal; round 2 versus 10 to 13; and 5 versus 10 to 12 (P < .05). Ordinal regression revealed significant differences between mental fatigue and physical fatigue (P < .001), tiredness (P < .001), stress (P < .001), mood (P < .001), and motivation (P < .05). Conclusions: The present study found mental fatigue to significantly fluctuate across a season in elite netballers. Moreover, perceived mental fatigue differed from physical fatigue, tiredness, stress, mood, and motivation. The data impress the need for mental fatigue to be included as an independent measure of athlete well-being. Monitoring of mental fatigue can allow practitioners to implement strategies to manage its influence on performance.

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K. Andrew R. Richards and James D. Ressler

Purpose: Scholars, including those in physical education, have investigated the socialization of higher education faculty members. Informed by self-study of teacher education practices and occupational socialization theory, we aimed to understand Kevin’s experiences during a transition from one institution to another with the help of his critical friend, Jim. Methodology/Methods: Data were collected through prolonged journaling and critical friend discussions. Resulting text files were analyzed thematically with a focus on identifying turning points. Findings: Themes developed through qualitative analysis included: (a) readjusting scholarly targets and embracing grantspersonship, (b) giving up control and facilitating research, and (c) balancing being a team player with self-advocacy. Discussion/Conclusions: Kevin’s transition was supported by recognizing shifting norms of his new faculty role and influence of self-study of teacher education practices for ongoing, career professional development. Prior and current socialization influences framed this development.

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Fernando G. Beltrami, Christian Froyd, Alexis R. Mauger, Alan J. Metcalfe, and Timothy D. Noakes

Objective: To investigate whether a cycling test based on decremental loads (DEC) could elicit higher maximal oxygen uptake (V˙O2max) values compared with an incremental test (INC). Design: Nineteen well-trained individuals performed an INC and a DEC test on a single day, in randomized order. Methods: During INC, the load was increased by 20 W·min−1 until task failure. During DEC, the load started at 20 W higher than the peak load achieved during INC (familiarization trial) and was progressively decreased. Gas exchange and electromyography (EMG) activity (n = 11) from 4 lower-limb muscles were monitored throughout the tests. Physiological and EMG data measured at V˙O2max were compared between the 2 protocols using paired t tests. Results: V˙O2max during the DEC was 3.0% (5.9%) higher than during INC (range 94%–116%; P = .01), in spite of a lower power output (−21 [20] W, P < .001) at V˙O2max. Pulmonary ventilation (P = .036) and breathing rate (P = .023) were also higher during DEC. EMG activity measured at V˙O2max was not different between tests, despite the lower output during DEC. Conclusions: A DEC exercise test produces higher V˙O2max in cycling compared with an INC test, which was accompanied by higher pulmonary ventilation and similar EMG activity. The additional O2 uptake during DEC might be related to extra work performed either by the respiratory muscles and/or the less oxidatively efficient leg muscles.

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Jan Gajdošík, Jirˇí Baláš, Dominika Krupková, Lukáš Psohlavec, and Nick Draper

Purpose: Although sport climbing is a self-paced whole-body activity, speed varies with climbing style, and the effect of this on systemic and localized oxygen responses is not well understood. Therefore, the aim of the present study was to determine muscle and pulmonary oxygen responses during submaximal climbing at differing speeds of ascent. Methods: Thirty-two intermediate and advanced sport climbers completed three 4-minute-long ascents of the same route at 4, 6, and 9 m·min−1 on a motorized climbing ergometer (treadwall) on separate laboratory visits. Gas analysis and near-infrared spectroscopy were used to determine systemic oxygen uptake (V˙O2) and muscle oxygen saturation (StO2) of the flexor digitorum profundus. Results: Increases in ascent speed of 1 m·min−1 led to increases of V˙O2 by 2.4 mL·kg−1·min−1 (95% CI, 2.1 to 2.8 mL·kg−1·min−1) and decreases in StO2 by −1.3% (95% CI, 1.9% to −0.7%). There was a significant interaction of climbing ability and speed for StO2 (P < .001, ηp2=.224). The results revealed that the decrease of StO2 was present for intermediate but not advanced climbers. Conclusions: In this study, the results suggest that V˙O2 demand during climbing was largely determined by climbing speed; however, the ability level of the climber appeared to mitigate StO2 at a cellular level. Coaches and instructors may prescribe climbing ascents with elevated speed to improve generalized cardiorespiratory fitness. To stimulate localized aerobic capacity, however, climbers should perhaps increase the intensity of training ascents through the manipulation of wall angle or reduction of hold size.

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Geoffrey M. Minett, Valentin Fels-Camilleri, Joshua J. Bon, Franco M. Impellizzeri, and David N. Borg

Purpose: This study aimed to examine the effect of peer presence on session rating of perceived exertion (RPE) responses. Method: Fourteen males, with mean (SD) age 22.4 (3.9) years, peak oxygen uptake 48.0 (6.6) mL·kg−1·min−1, and peak power output 330 (44) W, completed an incremental cycling test and 3 identical experimental sessions, in groups of 4 or 5. Experimental sessions involved 24 minutes of cycling, whereby the work rate alternated between 40% and 70% peak power output every 3 minutes. During cycling, heart rate was collected every 3 minutes, and session-RPE was recorded 10 minutes after cycling, in 3 communication contexts: in written form unaccompanied (intrapersonal communication), verbally by the researcher only (interpersonal communication), and in the presence of the training group. Session-RPE was analyzed using ordinal regression and heart rate using a linear mixed-effects model, with models fit in a Bayesian framework. Results: Session-RPE was voted higher when collected in the group’s presence compared with when written (odds ratio = 4.26, 95% credible interval = 1.27–14.73). On average, the posterior probability that session-RPE was higher in the group setting than when written was .53. Session-RPE was not different between the group and verbal, or verbal and written collection contexts. Conclusions: This study suggests that contextual psychosocial inputs influence session-RPE and highlights the importance of session-RPE users controlling the measurement environment when collecting votes.

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Teun van Erp, Robert P. Lamberts, and Dajo Sanders

Purpose: This study evaluated the power profile of a top 5 result achieved in World Tour cycling races of varying types, namely: flat sprint finish, semi-mountain race with a sprint finish, semi-mountain race with uphill finish, and mountain races (MT). Methods: Power output data from 33 professional cyclists were collected between 2012 and 2019. This large data set was filtered so that it only included top 5 finishes in World Tour races (18 participants and 177 races). Each of these top 5 finishes were subsequently classified as flat sprint finish, semi-mountain race with uphill finish, semi-mountain race with a sprint finish, and MT based on set criteria. Maximal mean power output (MMP) for a wide range of durations (5 s to 60 min), expressed in both absolute (in Watts) and relative terms (in Watts per kilogram), were assessed for each race type. Result: Short-duration power outputs (<60 s), both in relative and in absolute terms, are of higher importance to be successful in flat sprint finish and semi-mountain race with a sprint finish. Longer-duration power outputs (≥3 min) are of higher importance to be successful in semi-mountain race with uphill finish and MT. In addition, relative power outputs of >10 minutes seem to be a key determining factor for success in MT. These race-type specific MMPs of importance (ie, short-duration MMPs for sprint finishes, longer-duration MMPs for races with more elevation gain) are performed at a wide range (80%–97%) of the cyclist’s personal best MMP. Conclusions: This study shows that the relative importance of certain points on the power–duration spectrum varies with different race types and provides insight into benchmarks for achieving a result in a World Tour cycling race.

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Jonathon R. Lever, Dina C. Janse van Rensburg, Audrey Jansen van Rensburg, Peter Fowler, and Hugh H.K. Fullagar

Purpose: To assess the impact of long-haul transmeridian travel on subjective sleep patterns and jet lag symptoms in youth athletes around an international tournament. Methods: An observational descriptive design was used. Subjective sleep diaries and perceived responses to jet lag were collected and analyzed for a national junior netball team competing in an international tournament. Sleep diaries and questionnaires were completed daily prior to and during travel, and throughout the tournament. Results were categorized into pretravel, travel, training, and match nights. Means were compared performing a paired Student t test with significance set at P < .05. Data are presented as mean (SD) and median (minimum, maximum). Results: Athletes reported significantly greater time in bed on match days compared with training (P < .001) and travel (P = .002) days, and on pretravel days compared with travel (P < .001) and training (P = .028) days. Sleep ratings were significantly better on pretravel days compared with match (P = .013) days. Perceived jet lag was worse on match (P = .043) days compared with pretravel days. Significant differences were also observed between a number of conditions for meals, mood, bowel activity, and fatigue. Conclusion: Youth athletes experience significantly less opportunity for sleep during long-haul transmeridian travel and face disruptions to daily routines during travel which impact food intake. Young athletes also experience disturbed sleep prior to and during competition. These results highlight the need for practices to alleviate jet lag symptoms and improve the sleep of young athletes traveling for tournaments in an effort to optimize recovery and performance.

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Jason C. Bartram, Dominic Thewlis, David T. Martin, and Kevin I. Norton

Purpose: Modeling intermittent work capacity is an exciting development to the critical power model with many possible applications across elite sport. With the Skiba 2 model validated using subelite participants, an adjustment to the model’s recovery rate has been proposed for use in elite cyclists (Bartram adjustment). The team pursuit provides an intermittent supramaximal event with which to validate the modeling of W′ in this population. Methods: Team pursuit data of 6 elite cyclists competing for Australia at a Track World Cup were solved for end W′ values using both the Skiba 2 model and the Bartram adjustment. Each model’s success was evaluated by its ability to approximate end W′ values of 0 kJ, as well as a count of races modeled to within a predetermined error threshold of ±1.840 kJ. Results: On average, using the Skiba 2 model found end W′ values different from zero (P = .007; mean ± 95% confidence limit, –2.7 ± 2.0 kJ), with 3 out of 8 cases ending within the predetermined error threshold. Using the Bartram adjustment on average resulted in end W′ values that were not different from zero (P = .626; mean ± 95% confidence limit, 0.5 ± 2.5 kJ), with 4 out of 8 cases falling within the predetermined error threshold. Conclusions: On average, the Bartram adjustment was an improvement to modeling intermittent work capacity in elite cyclists, with the Skiba 2 model underestimating the rate of W′ recovery. In the specific context of modeling team pursuit races, all models were too variable for effective use; hence, individual recovery rates should be explored beyond population-specific rates.

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Rachel A. Van Woezik, Colin D. McLaren, Jean Côté, Karl Erickson, Barbi Law, Denyse Lafrance Horning, Bettina Callary, and Mark W. Bruner

In an ever-evolving society, sport coaches are presented with a number of avenues through which they can acquire and refine their coaching knowledge. The purpose of this research was to replicate and extend past research to gain an up-to-date understanding of how coaches are presently gaining knowledge. This was done through a constructive replication using a sequential explanatory mixed-method design. Study 1 included 798 coaches who completed an online questionnaire detailing their use of 16 sources of coaching knowledge. Coaches’ top three most used sources were interacting with coaches, learning by doing, and observing others. In contrast, the top three most preferred sources were observing others, interacting with coaches, and having a mentor. To contextualize these findings, Study 2 used a qualitative design in which 14 coaches were interviewed to understand their experiences with different knowledge sources. Five distinct narrative types were identified: recent elite athletes, parent coaches, coach developers, teacher coaches, and experienced coaches. Coaches reported engaging in more social and unstructured learning experiences, and the reasons for their preferences appeared to differ based on lifestyle and perceived barriers. Collectively, these findings highlight how coaches gain knowledge and why they prefer certain sources over others.