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Purpose: This study aimed at evaluating the effect of level of competition and drill typology on loads during the preseason period in male volleyball players. Methods: Internal (percentage of peak heart rate [HR] and summated HR zone) and external (PlayerLoad per minute, total and high accelerations per minute [tACCmin and hACCmin], decelerations per minute [tDECmin and hDECmin], and jumps per minute [tJUMPmin and hJUMPmin]) loads were monitored across a 5-week preseason period in 12 Division 1 (age: 22.5 [3.9] y; stature: 188 [6.2] cm; body mass: 85 [11.6] kg; training experience: 9.4 [4.2] y) and 12 Division 2 (age: 20.7 [2.9] y; stature: 186 [6.2] cm; body mass: 77.8 [9.6] kg; training experience: 5.6 [2.3] y) male volleyball players. Furthermore, differences in load were assessed for each drill typology (warm-up, conditioning, technical, tactical, and integral). Results: No effects (P >.05) of level of competition on the internal (except for summated HR zone, P =.05) and external loads (except for tJUMPmin, P =.002) were found. Differently, drill typologies showed an effect (P <.001) on all the investigated internal- and external-load measures. The main post hoc results revealed higher (P <.05) percentage of peak HR, summated HR zone, PlayerLoad per minute, and tACCmin in warm-up and conditioning drills, while higher (P <.05) hDECmin and hJUMPmin were found in tactical and integral drills. Conclusions: These results suggest that volleyball coaches use warm-up and conditioning drills when aiming at increasing the internal loads, PlayerLoad per minute, and tACCmin, while tactical and integral drills should be preferred to enhance the number of hDECmin and hJUMPmin. [ABSTRACT FROM AUTHOR]

Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect. Results: The lowest significant (P <.05) relationship was for high jumps with objective (ρ =.56) and subjective (ρ =.49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ =.9) and subjective (ρ =.84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75–33.31); SE = 5.26, and R2 =.47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00–7330.6); SE = 21.87; and R2 =.71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study. [ABSTRACT FROM AUTHOR]

Purpose: To assess weekly fluctuations in hormonal responses and their relationships with load and well-being during a congested in-season phase in basketball players. Methods: Ten semiprofessional, male basketball players were monitored during 4 congested in-season phase weeks consisting of 3 weekly matches. Salivary hormone variables (testosterone [T], cortisol [C], and T:C ratio) were measured weekly, and external load (PlayerLoad™ and PlayerLoad per minute), internal load session rating of perceived exertion, percentage of maximum heart rate (HR), summated HR zones, and well-being were assessed for each training session and match. Results: Significant (P <.05) moderate to large decreases in T were found in the third and fourth weeks compared with the first week. Nonsignificant moderate to large decreases in C were apparent in the last 2 weeks compared with previous weeks. Summated HR zones and perceived sleep significantly (P <.05) decreased in the fourth week compared with the first week; whereas, percentage of maximum HR significantly (P <.05) decreased in the fourth week compared with the second week. No significant relationships were found between weekly changes in hormonal responses and weekly changes in load and overall wellness. Conclusions: A congested schedule during the in-season negatively impacted the hormonal responses of players, suggesting that T and C measurements may be useful to detect fluctuations in hormone balance in such scenarios. The nonsignificant relationships between weekly changes in hormonal responses and changes in load and well-being indicate that other factors might induce hormonal changes across congested periods in basketball players. [ABSTRACT FROM AUTHOR]

This study aimed to (a) quantify weekly fluctuations in hormonal responses (testosterone [T], cortisol [C], and their ratio [T:C]), external (PlayerLoad [PL] and PL·minute21) and internal (session rating of perceived exertion load [sRPE-load], summated heart rate zones [SHRZs], and percentage of maximal heart rate [%HRmax]) load measures, and well-being measured using a self-reported questionnaire and (b) determine the associations between weekly changes in hormonal responses and load measures with weekly changes in well-being during the pre-season phase in basketball players. Twenty-one professional male basketball players (age: 26.2 6 4.9 years) were monitored during a 5-week pre-season phase. Linear mixed models were used to determine weekly differences in each variable and associations between weekly changes in hormonal and load variables with weekly changes in well-being. Findings revealed that T (p < 0.001) and T:C (p50.002) increased toward the end of the pre-season phase. Moreover, higher (p, 0.05) external (PL·minute21) and internal (%HRmax) load intensities were evident during the first 3 weeks of the pre-season, with no significant fluctuations in other load variables. Weekly changes in PL and sRPE-load were negatively associated (p, 0.05) with weekly changes in well-being, albeit weak in magnitudes (R2 5 0.061-0.105). These results highlight that a periodized approach was undertaken across the pre-season predominantly predicated on altering weekly load intensities, which coincided with positive hormonal responses toward the end of the pre-season. In addition, weak relationships were evident between weekly changes in hormonal responses and load measures with well-being, emphasizing that a low commonality may be present between these constructs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Games-based drills are the predominant form of training adopted during basketball practice. As such, researchers have begun to quantify the physical, physiological, and perceptual demands of different games-based drill formats. However, study methodology has not been systematically reported across studies, limiting the ability to form conclusions from existing research. The authors developed this call to action to draw attention to the current standard of methodological reporting in basketball games-based drill research and establish a systematic reporting standard the authors hope will be utilized in future research. The Basketball Games-Based Drill Methodical Reporting Checklist (BGBDMRC) was developed to encourage the systematic reporting of games-based drill methodology. The authors used the BGBDMRC to evaluate the current methodological reporting standard of studies included in their review published in the International Journal of Sports Physiology and Performance, "A Systematic Review of the External and Internal Workloads Experienced During Games-Based Drills in Basketball Players" (2020), which highlighted this issue. Of the 17 studies included in their review, only 38% (±18%) of applicable checklist items were addressed across included studies, which is problematic as checklist items are essential for study replication. Conclusions: The current standard of methodological reporting in basketball games-based drill research is insufficient to allow for replication of examined drills in future research or the application of research outcomes to practice. The authors implore researchers to adopt the BGBDMRC to improve the quality and reproducibility of games-based drill research and increase the translation of research findings to practice. [ABSTRACT FROM AUTHOR]

Purpose: To describe and identify individual trends and changes in training load, neuromuscular readiness, and perceptual fatigue measures in 2 youth elite long jumpers, finalists at the European Athletics U18 (Under 18) Championships (athlete A, female, age 16.5 y, long-jump record 6.25 m; athlete B, male, age 16.0 y, long-jump record 7.28 m). Methods: Data were collected from both training sessions and athletics competitions during a 16-week period, divided into a preparation (weeks 1–8) and a competitive phase (weeks 9–16). Training load was computed through training diaries (training time, sprint, jumping, and weights volume). The countermovement jump and the 10-to-5 repeated-jump test were executed on a weekly basis to assess neuromuscular readiness, and perceptual fatigue measures were collected through a wellness questionnaire. Statistical analysis was conducted using a magnitude-based decisions approach. Results: The results highlighted a decrease in training load during the competitive period with moderate to large differences for training time, sprint, and jump volume. Moreover, data showed an upward trend and very likely higher scores in vertical-jump performance across the competitive phase together with a very likely lower perceptual fatigue. Conclusions: This scenario seemed to be favorable to achieve competition performance very close to the personal record during the competitive season. This study provided an example of application of a comprehensive monitoring system with young athletes involved in track-and-field jumping events. [ABSTRACT FROM AUTHOR]

Purpose: To examine the physiological, physical, and technical demands of game-based drills (GBDs) with regular dribble (RD) or no dribble (ND) involving a different number of players (3 vs 3, 4 vs 4, and 5 vs 5). Methods: Ten regional-level male basketball players performed 6 full-court GBD formats (each consisting of 3 bouts of 4 min and 2 min rest) on multiple occasions. The physiological and perceptual responses were measured through heart rate and rating of perceived exertion. Video-based time–motion analysis was performed to assess the GBD physical demands. The frequencies of occurrence and the duration were calculated for high-intensity, moderate-intensity, low-intensity, and recovery activities. Technical demands were assessed with a notional-analysis technique. A 2-way repeated-measures analysis of variance was used to assess statistical differences between GBD formats. Results: A greater perceptual response (rating of perceived exertion) was recorded during 3 versus 3 than 5 versus 5 formats (P =.005). Significant interactions were observed for the number of recovery (P =.021), low-intensity activity (P =.007), and all movements (P =.001) completed. Greater time was spent performing low-intensity and high-intensity activities during RD than ND format. Greater technical demands were observed for several variables during 3 versus 3 than 4 versus 4 or 5 versus 5. A greater number of turnovers (P =.027), total (P ≤.001), and correct passes (P ≤.001) were recorded during ND than RD format. Conclusions: The number of players predominantly affected the perceptual response to GBD, while both the number of players and rule modification (RD vs ND) affected activities performed during GBD. Reducing the number of players increases the GBD technical elements, while ND format promotes a greater number of turnovers and passes. [ABSTRACT FROM AUTHOR]

Purpose: The purposes of this study were to (1) analyze the variations of acute and chronic training load and well-being measures during 3 periods of the season (early, mid, and end) and (2) test the associations between weekly training load and well-being measures during different periods of the season. Methods: Thirteen professional volleyball players from a team competing in the Portuguese Volleyball First Division (age 31.0 [5.0] y) were monitored during an entire season. Weekly acute (wAL) and chronic load (wCL), acute to chronic workload ratio (wACWL), and training monotony (wTM) were calculated during all weeks of the season. The weekly values of muscle soreness (wDOMS), stress (wStress), fatigue (wFatigue), sleep (wSleep), and Hooper index (wHI) were also obtained across the season. Results: The midseason had meaningfully low values of wAL (−26.9%; effect size [ES]: −1.12) and wCL (−28.0%; ES: −2.81), and greater values of wACWL (+38.9%; ES: 2.81) compared with early season. The wCL (+10.6%; ES: 0.99), wStress (44.6%; ES: 0.87), and wHI (29.0%; ES: 0.62) were meaningfully greater during the end of season than in midseason. Overall, wAL presented very large correlations with wDOMS (r =.80), wSleep (r =.72), and wFatigue (r =.82). Conclusions: The results of this study suggest that the load was meaningfully higher during early season; however, stress was higher during the final stages of the season. Overall, it was also found that the acute load is more highly correlated with well-being status and its variations than chronic load or training monotony. [ABSTRACT FROM AUTHOR]

Purpose: To assess the weekly fluctuations in workload and differences in workload according to playing time in elite female basketball players. Methods: A total of 29 female basketball players (mean [SD] age 21 [5] y, stature 181 [7] cm, body mass 71 [7] kg. playing experience 12 [5] y) belonging to the 7 women's basketball teams competing in the first-division Lithuanian Women's Basketball League were recruited. Individualized training loads (TLs) and game loads (GLs) were assessed using the session rating of perceived exertion after each training session and game during the entire in-season phase (24 wk). Percentage changes in total weekly TL (weekly TL + GL), weekly TL, weekly GL, chronic workload, acutexhronic workload ratio, training monotony, and training strain were calculated. Mixed linear models were used to assess differences for each dependent variable, with playing time (low vs high) used as fixed factor and subject, week, and team as random factors. Results: The highest changes in total weekly TL, weekly TL, and acutexhronic workload ratio were evident in week 13 (47%, 120%, and 49%, respectively). Chronic workload showed weekly changes <10%, whereas monotony and training strain registered highest fluctuations in weeks 17 (34%) and 15 (59%), respectively. A statistically significant difference in GL was evident between players completing low and high playing times (P = .026, moderate), whereas no significant differences (P > .05) were found for all other dependent variables. Conclusions: Coaches of elite women's basketball teams should monitor weekly changes in workload during the in-season phase to identify weeks that may predispose players to unwanted spikes and adjust player workload according to playing time. [ABSTRACT FROM AUTHOR]

Purpose: To assess the technical and tactical demands of elite karate athletes in relation to 3 match sequences (ie, advantage, disadvantage, and drawing) and match outcome (ie, win/defeat).Methods: One hundred twenty elite seniors' (60 men and 60 women) World Karate Federation combats were analyzed during 2 World Championships (2012 and 2014). Specific karate attributes (strategy, technique, tactic, target, and effectiveness) were evaluated and classified into 3 sequences: advantage, disadvantage, and drawing. Results: Karatekas performed more combination techniques in disadvantage sequences than in drawing sequences (P =.011). A higher number of timed-attack actions were reported during advantage sequences than during drawing sequences (P =.048). Winners of the whole combat had higher lower-limb technique rate (1.0 [0.9] vs 0.1 [0.3]; P =.044) and less rate of timed attack (0.3 [0.5] vs 0.6 [1.0]; P =.030) than defeated karatekas during advantage and drawing sequences, respectively. Conclusions: Winners used higher lower-limb technique and less timed-attack rates than defeated karatekas in advantage and drawing sequences, respectively. Indeed, using lower-limb technique during advantageous situations could be a powerful strategy to increase the lead. Therefore, it seems fundamental for coaches of top elite karatekas to put their athletes in simulated situations and push them to increase their use of lower-limb techniques. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Fox, JL, Conte, D, Stanton, R, McLean, B, and Scanlan, AT. The application of accelerometer-derived moving averages to quantify peak demands in basketball: A comparison of sample duration, playing role, and session type. J Strength Cond Res 35(12S): S58–S63, 2021—The purpose of this was to study compare peak external workload intensities in basketball using accelerometer-derived moving averages between different sample durations (0.5–5 minutes), session types (training vs. game-play), and playing roles (starting vs. bench players). Five starting and 3 bench players were monitored over a 15-week competitive season using accelerometers. For all training sessions and games, peak external workload intensities were determined using accelerometer-derived moving averages for PlayerLoad per minute (PL·min−1) across sample durations of 0.5, 1, 2, 3, 4, and 5 minutes. Linear mixed-models and effect sizes (ESs) were used to compare peak PL·min−1 between sample durations, session type, and playing role. Peak PL·min−1 was significantly different between all sample durations (p < 0.05; ES = 0.88–5.45), with higher intensities evident across shorter sample durations. In starting players, peak intensities were significantly higher during games compared with training for all sample durations (p < 0.05; ES = 0.69–0.93). Peak game intensities were higher in starting players using all sample durations (p > 0.05; ES = 0.69–1.43) compared with bench players. Shorter sample durations produced higher peak PL·min−1. Peak intensities were higher during games than training in starting players, indicating training may not adequately prepare players for the most demanding passages of game-play. [ABSTRACT FROM AUTHOR]

This study aimed to investigate between- and within-team changes in workload [PlayerLoad (PL), training impulse (TRIMP) and session rate of perceived exertion training load (sRPE-TL)], readiness [heart rate variability (HRV)], and physical performance [20-m sprint test (including 10-m split time), countermovement jump (CMJ) and yo-yo intermittent recovery test level 1 (YYIR1)] during 3-week intensified preparation periods in female, national Under18 (n = 12, age = 18.0 ± 0.5y, stature = 180.4 ± 7.5 cm, body mass = 72.7 ± 9.3 kg) and Under20 (n = 12, age = 19.6 ± 0.8y, stature = 178.6 ± 6.4 cm, body mass = 68.0 ± 5.9 kg) basketball teams. Under18 team revealed small-to-moderate statistically significantly higher values in workload [PL: p = 0.010; ES = Small; TRIMP: p = 0.004; ES = Moderate; sRPE-TL: p < 0.001; ES = Moderate] and moderately lower readiness values (p = 0.023; ES = Moderate) compared to Under20. Within-team analysis showed no differences in workload in Under20 and statistically significant reduction (p < 0.05) in Week3 (taper period) in Under18. Pre- and post-preparation changes showed Under18 increasing only YYIR1 performance (p < 0.001; ES = Very large). Differently, Under20 statistically improved in 10-m split time (p = 0.003; ES = Moderate), CMJ (p = 0.025; ES = Moderate) and YYIR1 (p < 0.001; ES = Large). A constant adequate workload positively benefits players' readiness and physical performances during short intensified preparation periods. Conversely, using high workload with periodization strategies encompassing short overload and taper phases induced positive changes on players' aerobic performance, lower readiness values and no changes in anaerobic performances. [ABSTRACT FROM AUTHOR]

This study aimed to analyse the effects of two factors (number of players and training regimes) on players’ physiological and technical demands in basketball ball-drills. Twenty-one young basketball players performed four different ball-drills (two levels for each factor). The number of players involved was 2vs2 and 4vs4, while ball-drill regimes were continuous and intermittent. Physiological demand was assessed using the percentage of maximal heart rate (%HRmax), Edwards’ training load and rating of perceived exertion (RPE). Furthermore, the following technical actions were collected: dribbles, steals, rebounds, turnovers, passes (total, correct, wrong and % of correct pass) and shots (total, scored, missed and % of made shot). A 2 × 2 (number of players × regime) two-way ANOVA with repeated measures was applied for physiological parameters and technical actions. The 2vs2 condition showed higher %HRmax(P < 0.001), Edwards’ training load (P < 0.001), RPE (P < 0.001), number of dribbles (P < 0.001), rebounds (P < 0.001), passes [total (P = 0.005) and correct (P = 0.005)] and shots [total (P < 0.001) scored (P < 0.001) and missed (P < 0.001)] than 4vs4. Moreover, the continuous regime revealed higher %HRmax(P < 0.001), Edwards’ training load (P < 0.001), RPE (P = 0.006) and dribbles (P < 0.001) than the intermittent regime. This study showed that both number of players and regime are useful variables able to modify basketball ball-drills workload. [ABSTRACT FROM PUBLISHER]

This study aimed to examine the scoring strategies differentiating between winning and losing teams during FIBA EuroBasket Women 2017 in relation to different game scores. Data were gathered for all games of FIBA EuroBasket Women 2017 from the official website. The investigated scoring strategies were fast break points (FBP); points in the paint (PP); points from turnover (PT); second chance points (SCP); and points from the bench (PB). Games were classified with cluster analysis based on their score difference as close, balanced, and unbalanced and the differences in the scoring strategies between winning and losing teams were assessed using magnitude-based statistics. Results revealed no substantial differences in FBP in any investigated cluster. Furthermore, winning teams showed a substantially higher number of PP and PT (in close and unbalanced games) and SCP (in balanced and unbalanced games) compared to losing teams. Finally, winning teams scored substantially lower and higher number of BPs in close games and unbalanced games, respectively, compared to losing teams. In conclusion, all the investigated scoring strategies discriminate between winning and losing teams in elite women’s basketball except for FBP. These results provide useful information for basketball coaches to optimize their training sessions and game strategies. [ABSTRACT FROM AUTHOR]