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The Business End of the Season: A Comparison Between Playoff and Regular-Season Workloads in Professional Basketball Players

Davide Ferioli, Aaron T. Scanlan, Daniele Conte, Emanuele Tibiletti, and Ermanno Rampinini

Purpose: To quantify and compare the internal workloads experienced during the playoffs and regular season in basketball. Methods: A total of 10 professional male basketball players competing in the Italian first division were monitored during the final 6 weeks of the regular season and the entire 6-week playoff phase. Internal workload was quantified using the session rating of perceived exertion (s-RPE) method for all training sessions and games. A 2-way repeated-measures analysis of variance (day type × period) was utilized to assess differences in daily s-RPE between game days, days within 24 hours of games, and days >24 hours from games during the playoffs and regular season. Comparisons in weekly training, game, and total workloads were made between the playoffs and regular season using paired t tests and effect sizes. Results: A significant interaction between day and competitive period for s-RPE was found (P = .003, moderate). Lower s-RPE was apparent during playoff and regular-season days within 24 hours of games than all other days (P < .001, very large). Furthermore, s-RPE across days >24 hours from playoff games was different than all other days (P ≤ .01, moderate–very large). Weekly training (P = .009, very large) and total (P < .001, moderate) s-RPE were greater during the regular season than playoffs, whereas weekly game s-RPE was greater during the playoffs than the regular season (P < .001, very large). Conclusions: This study presents an exploratory investigation of internal workload during the playoffs in professional basketball. Players experienced greater training and total weekly workloads during the regular season than during the playoffs with similar daily game workloads between periods.

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Not All About the Effort? A Comparison of Playing Intensities During Winning and Losing Game Quarters in Basketball

Jordan L. Fox, Jesse Green, and Aaron T. Scanlan

Purpose: To compare peak and average intensities encountered during winning and losing game quarters in basketball players. Methods: Eight semiprofessional male basketball players (age = 23.1 [3.8] y) were monitored during all games (N = 18) over 1 competitive season. The average intensities attained in each quarter were determined using microsensors and heart-rate monitors to derive relative values (per minute) for the following variables: PlayerLoad, frequency of high-intensity and total accelerations, decelerations, changes of direction, jumps, and total inertial movement analysis events combined, as well as modified summated-heart-rate-zones workload. The peak intensities reached in each quarter were determined using microsensors and reported as PlayerLoad per minute over 15-second, 30-second, 1-minute, 2-minute, 3-minute, 4-minute, and 5-minute sample durations. Linear mixed models and effect sizes were used to compare intensity variables between winning and losing game quarters. Results: Nonsignificant (P > .05), unclear–small differences were evident between winning and losing game quarters in all variables. Conclusions: During winning and losing game quarters, peak and average intensities were similar. Consequently, factors other than the intensity of effort applied during games may underpin team success in individual game quarters and therefore warrant further investigation.

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Effect of Match Schedule Density on Self-Reported Wellness and Sleep in Referees During the Rugby World Cup

Nathan Elsworthy, Michele Lastella, Aaron T. Scanlan, and Matthew R. Blair

Purpose : To examine the effect of match schedule on self-reported wellness and sleep in rugby union referees during the 2019 Rugby World Cup. Methods : Following an observational design, 18 international-level male referees participating in the 2019 Rugby World Cup completed a daily questionnaire to quantify wellness status (sleep quality, mood, stress, fatigue, muscle soreness, and total wellness) and sleep characteristics (bedtime, wake-up time, and time in bed) from the previous night across the tournament. Linear mixed models and effect sizes (Hedges g av) assessed differences in wellness and sleep characteristics between prematch and postmatch days surrounding single-game and 2-game congested match schedules (prematch1, postmatch1, prematch2, and postmatch2 days). Results: During regular schedules, all self-reported wellness variables except stress were reduced (g av = 0.33–1.05, mean difference −0.32 to −1.21 arbitrary units [AU]) and referees went to bed later (1.08, 1:07 h:min) and spent less time in bed (−0.78, 00:55 h:min) postmatch compared with prematch days. During congested schedules, only wellness variables differed across days, with total wellness reduced on postmatch1 (−0.88, −3.56 AU) and postmatch2 (−0.67, −2.70 AU) days, as well as mood (−1.01, −0.56 AU) and fatigue (−0.90, −1.11 AU) reduced on postmatch1 days compared with prematch days. Conclusion: Referees were susceptible to acute reductions in wellness on days following matches regardless of schedule. However, only single-game regular match schedules negatively impacted the sleep characteristics of referees. Targeted strategies to maximize wellness status and sleep opportunities in referees considering the match schedule faced should be explored during future Rugby World Cup competitions.

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Monitoring Training Load and Well-Being During the In-Season Phase in National Collegiate Athletic Association Division I Men’s Basketball

Daniele Conte, Nicholas Kolb, Aaron T. Scanlan, and Fabrizio Santolamazza

Purpose: To characterize the weekly training load (TL) and well-being of college basketball players during the in-season phase. Methods: Ten (6 guards and 4 forwards) male basketball players (age 20.9 [0.9] y, stature 195.0 [8.2] cm, and body mass 91.3 [11.3] kg) from the same Division I National Collegiate Athletic Association team were recruited to participate in this study. Individualized training and game loads were assessed using the session rating of perceived exertion at the end of each training and game session, and well-being status was collected before each session. Weekly changes (%) in TL, acute-to-chronic workload ratio, and well-being were determined. Differences in TL and well-being between starting and bench players and between 1-game and 2-game weeks were calculated using magnitude-based statistics. Results: Total weekly TL and acute-to-chronic workload ratio demonstrated high week-to-week variation, with spikes up to 226% and 220%, respectively. Starting players experienced a higher (most likely negative) total weekly TL and similar (unclear) well-being status compared with bench players. Game scheduling influenced TL, with 1-game weeks demonstrating a higher (likely negative) total weekly TL and similar (most likely trivial) well-being status compared with 2-game weeks. Conclusions: These findings provide college basketball coaches information to optimize training strategies during the in-season phase. Basketball coaches should concurrently consider the number of weekly games and player status (starting vs bench player) when creating individualized periodization plans, with increases in TL potentially needed in bench players, especially in 2-game weeks.

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The Concurrent Validity of Session-Rating of Perceived Exertion Workload Obtained Face-to-Face Versus Via an Online Application: A Team Case Study

Jordan L. Fox, Cody J. O’Grady, and Aaron T. Scanlan

Purpose: To compare the concurrent validity of session-rating of perceived exertion (sRPE) workload determined face-to-face and via an online application in basketball players. Methods: Sixteen semiprofessional, male basketball players (21.8 [4.3] y, 191.2 [9.2] cm, 85.0 [15.7] kg) were monitored during all training sessions across the 2018 (8 players) and 2019 (11 players) seasons in a state-level Australian league. Workload was reported as accumulated PlayerLoad (PL), summated-heart-rate-zones (SHRZ) workload, and sRPE. During the 2018 season, rating of perceived exertion (RPE) was determined following each session via individualized face-to-face reporting. During the 2019 season, RPE was obtained following each session via a phone-based, online application. Repeated-measures correlations with 95% confidence intervals were used to determine the relationships between sRPE collected using each method and other workload measures (PL and SHRZ) as indicators of concurrent validity. Results: Although all correlations were significant (P < .05), sRPE obtained using face-to-face reporting demonstrated stronger relationships with PL (r = .69 [.07], large) and SHRZ (r = .74 [.06], very large) compared with the online application (r = .29 [.25], small [PL] and r = .34 [.22], moderate [SHRZ]). Conclusions: Concurrent validity of sRPE workload was stronger when players reported RPE in an individualized, face-to-face manner compared with using a phone-based online application. Given the weaker relationships with other workload measures, basketball practitioners should be cautious when using player training workloads predicated on RPE obtained via online applications.

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The Relationships Between External and Internal Workloads During Basketball Training and Games

Jordan L. Fox, Cody J. O’Grady, and Aaron T. Scanlan

Purpose: To investigate the relationships between external and internal workloads using a comprehensive selection of variables during basketball training and games. Methods: Eight semiprofessional, male basketball players were monitored during training and games for an entire season. External workload was determined as PlayerLoad: total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events. Internal workload was determined using the summated-heart-rate zones and session rating of perceived exertion models. The relationships between external and internal workload variables were separately calculated for training and games using repeated-measures correlations with 95% confidence intervals. Results: PlayerLoad was more strongly related to summated-heart-rate zones (r = .88 ± .03, very large [training]; r = .69 ± .09, large [games]) and session rating of perceived exertion (r = .74 ± .06, very large [training]; r = .53 ± .12, large [games]) than other external workload variables (P < .05). Correlations between total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events and internal workloads were stronger during training (r = .44–.88) than during games (r = .15–.69). Conclusions: PlayerLoad and summated-heart-rate zones possess the strongest dose–response relationship among a comprehensive selection of external and internal workload variables in basketball, particularly during training sessions compared with games. Basketball practitioners may therefore be able to best anticipate player responses when prescribing training drills using these variables for optimal workload management across the season.

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The Association Between Sleep and In-Game Performance in Basketball Players

Jordan L. Fox, Robert Stanton, Aaron T. Scanlan, Masaru Teramoto, and Charli Sargent

Purpose: To investigate the associations between sleep and competitive performance in basketball. Methods: A total of 7 semiprofessional, male players were monitored across the in-season. On nights prior to competition, sleep duration and quality were assessed using actigraphs and sleep diaries. The data were accumulated over 1 (night 1), 2 (nights 1–2 combined), 3 (nights 1–3 combined), and 4 (nights 1–4 combined) nights prior to competition. Performance was reported as player statistics (field goal and free-throw accuracy, rebounds, assists, steals, blocks, and turnovers) and composite performance statistics (offensive rating, defensive rating, and player efficiency). Linear regression analyses with cluster-robust standard errors using bootstrapping (1000 replications) were performed to quantify the association between sleep and performance. Results: The night before competition, subjective sleep quality was positively associated with offensive rating and player efficiency (P < .05). Conclusions: Strategies to increase subjective sleep quality the night before competition should be considered to increase the likelihood of successful in-game performance, given its association with composite performance metrics.

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Defensive Strategy and Player Sex Impact Heart-Rate Responses During Games-Based Drills in Professional Basketball

David Suárez-Iglesias, Rubén Dehesa, Aaron T. Scanlan, José A. Rodríguez-Marroyo, and Alejandro Vaquera

Purpose: Games-based drills (GBD) are the predominant form of training stimulus prescribed to male and female basketball players. Despite being readily manipulated during GBD, the impact of defensive strategy on the sex-specific demands of GBD remains unknown. Therefore, the aim of this study was to quantify and compare the heart-rate (HR) responses experienced during 5v5 GBD using different defensive strategies (man-to-man defense vs zone defense [ZD] formations) according to player sex. Method: HR was recorded in 11 professional male and 10 professional female basketball players while performing 5v5 GBD with different defensive strategies (man-to-man defense or ZD). HR-based training load was also calculated using the summated heart-rate zones model. Results: During man-to-man defense, mean HR ( η p 2 = .02 ), relative time (in percentage) spent working at 90% to 100% maximal HR ( η p 2 = .03 ), and summated heart-rate zones ( η p 2 = .02 ) were greater (P < .05) in female players compared with males. During ZD, higher (P < .01) peak HR ( η p 2 = .07 ), mean HR ( η p 2 = .11 ), relative and absolute (in minutes) time spent working at 80% to 89% maximal HR ( η p 2 = .03 and .03, respectively) and 90% to 100% maximal HR ( η p 2 = .12 and .09, respectively), and summated heart-rate zones ( η p 2 = .19 ) were observed in female players compared with males. Conclusions: The defensive strategy employed during 5v5 full-court GBD influences HR responses and training load differently according to sex, where female players experience higher HR responses than males, especially when ZD are adopted. Basketball coaching staff can use these findings for the precise manipulation of team defenses during GBD to elicit desired cardiovascular stress on players.

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Caffeine Ingestion Improves Performance During Fitness Tests but Does Not Alter Activity During Simulated Games in Professional Basketball Players

Javier Raya-González, Aaron T. Scanlan, María Soto-Célix, Alejandro Rodríguez-Fernández, and Daniel Castillo

Purpose: To examine the effects of acute caffeine supplementation on physical performance during fitness testing and activity during simulated games in basketball players. Methods: A double-blind, counterbalanced, randomized, crossover study design was followed. A total of 14 professional male basketball players ingested a placebo (sucrose) and caffeine (6 mg·kg−1 of body mass) in liquid form prior to completing 2 separate testing sessions. Each testing session involved completion of a standardized 15-minute warm-up followed by various fitness tests including 20-m sprints, countermovement jumps, Lane Agility Drill trials, and a repeated-sprint-ability test. Following a 20-minute recovery, players completed 3 × 7-minute 5-vs-5 simulated periods of full-court basketball games, each separated by 2 minutes of recovery. Local positioning system technology was used to measure player activity during games. Players completed a side-effects questionnaire 12 to 14 hours after testing. Results: Players experienced significant (P < .05), moderatevery large (effect size = −2.19 to 0.89) improvements in 20-m sprint, countermovement jump, Lane Agility Drill, and repeated-sprint-ability performance with caffeine supplementation. However, external workloads completed during simulated games demonstrated nonsignificant, trivialsmall (effect size = −0.23 to 0.12) changes between conditions. In addition, players reported greater (P < .05) insomnia and urine output after caffeine ingestion. Conclusions: Acute caffeine supplementation could be effective to improve physical performance during tests stressing fitness elements important in basketball. However, acute caffeine supplementation appears to exert no meaningful effects on the activity completed during simulated basketball games and may promote sleep disturbances and exert a diuretic effect when taken at 6 mg·kg−1 of body mass in professional players.

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Aerobic Capacity According to Playing Role and Position in Elite Female Basketball Players Using Laboratory and Field Tests

Aaron T. Scanlan, Emilija Stojanović, Zoran Milanović, Masaru Teramoto, Mario Jeličić, and Vincent J. Dalbo

Purpose: To compare the aerobic capacity of elite female basketball players between playing roles and positions determined using maximal laboratory and field tests. Methods: Elite female basketball players from the National Croatian League were grouped according to playing role (starter: n = 8; bench: n = 12) and position (backcourt: n = 11; frontcourt: n = 9). All 20 players completed 2 maximal exercise tests in a crossover fashion 7 days apart. First, the players underwent a laboratory-based continuous running treadmill test with metabolic measurement to determine their peak oxygen uptake (VO2peak). The players then completed a maximal field-based 30-15 Intermittent Fitness Test (30-15 IFT) to estimate VO2peak. The VO2peak was compared using multiple linear regression analysis with bootstrap standard errors and playing role and position as predictors. Results: During both tests, starters attained a significantly higher VO2peak than bench players (continuous running treadmill: 47.4 [5.2] vs 44.7 [3.5] mL·kg−1·min−1, P = .05, moderate; 30-15 IFT: 44.9 [2.1] vs 41.9 [1.7] mL·kg−1·min−1, P < .001, large), and backcourt players attained a significantly higher VO2peak than frontcourt players (continuous running treadmill: 48.1 [3.8] vs 43.0 [3.3] mL·kg−1·min−1, P < .001, large; 30-15 IFT: 44.2 [2.2] vs 41.8 [2.0] mL·kg−1·min−1, P < .001, moderate). Conclusions: Starters (vs bench players) and guards (vs forwards and centers) possess a higher VO2peak irrespective of using laboratory or field tests. These data highlight the role- and position-specific importance of aerobic fitness to inform testing, training, and recovery practices in elite female basketball.