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ABSTRACT: Kamarauskas, P, Scanlan, A, Ferioli, D, and Conte, D. Weekly fluctuations in, and associations between, salivary hormone responses, load, and well-being during the pre-season in professional male basketball players. J Strength Cond Res 38(1): 128-135, 2024-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·minute-1) 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 ± 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 (p = 0.002) increased toward the end of the pre-season phase. Moreover, higher (p < 0.05) external (PL·minute-1) 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 = 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.
Assuntos
Basquetebol , Fragilidade , Condicionamento Físico Humano , Humanos , Masculino , Adulto Jovem , Adulto , Condicionamento Físico Humano/fisiologia , Basquetebol/fisiologia , Estações do Ano , Hidrocortisona , Autorrelato , Esforço Físico/fisiologiaRESUMO
The aim of this study was to compare knee extensor and flexor strength recovery following anterior cruciate ligament (ACL) reconstruction between bone-patellar tendon-bone (BPTB) and hamstring tendon (HT) grafts in international male soccer players undergoing comparable 6-month rehabilitation programmes. Seventeen players underwent ACL reconstruction with either an autogenous BPTB graft or HT graft. Knee extensor and flexor peak torques were measured at 3 months and 6 months in the injured and contralateral legs following surgery using isokinetic dynamometry. The moderate-large asymmetries in knee extensor peak torque between legs at 3 months across graft types (BPTB: p = 0.002, g = -0.94; HT: p = 0.02, g = -0.55) were reduced to trivial asymmetries at 6 months (BPTB: p = 0.30, g = -0.19; HT: p = 0.40, g = -0.16), with a non-significant difference in limb symmetry index (LSI) between grafts at 6 months (p = 0.62, g = -0.24). Similarly, moderate-large asymmetries in knee flexor peak torque between legs at 3 months across graft types (BPTB: p = 0.13, g = -0.50; HT: p = 0.01, g = -0.97) were reduced to trivial-small asymmetries at 6 months (BPTB: p = 0.25, g = 0.18; HT: p = 0.01, g = -0.47); however, a superior LSI was evident with BPTB compared to HT grafts at 6 months (p = 0.007, g = 1.43, large). Strength and conditioning professionals working with soccer players who are rehabilitating from ACL reconstruction after receiving a HT graft should give adequate attention to delivering suitable hamstring exercises that ensure optimal strength restoration.
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BACKGROUND: Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear. OBJECTIVES: The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS). METHODS: PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS. RESULTS: Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s-2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s-1) and acceleration/deceleration zones (> 2.0 m·s-2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research. CONCLUSIONS: Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.
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Activity simulation protocols offer useful applications in research and practice; however, the specificity of such protocols to basketball game-play is currently lacking. Consequently, this study aimed to develop a game-specific basketball activity simulation protocol representative of typical playing durations and assess its reliability and discriminant validity. The simulation protocol was modified from an original version (i.e., Basketball Exercise Simulation Test) to incorporate regular breaks indicative of time-outs, free-throws, and substitutions. Twelve competitive male and female adult basketball players competing in the fourth or fifth Spanish basketball division underwent repeated trials of the simulation protocol (min. 4 to max. 14 days apart) for reliability analyses. In turn, 13 competitive male (fifth division), 9 competitive female (fourth division), and 13 recreational male adult basketball players completed the simulation protocol to assess discriminant validity via comparisons between sexes (competitive players) and playing levels (males). A range of physical, technical, and perceptual-physiological variables were collected during and following the simulation protocol. Several physical and heart rate variables displayed the strongest reliability (intraclass correlation coefficient [ICC] = 0.72-0.96; coefficient of variation [CV] = 1.78-6.75%), with physical decrement, technical, blood lactate concentration, and rating of perceived exertion (RPE) variables having the weakest (ICC = 0.52-0.75; CV = 10.34-30.85%). Regarding discriminant analyses between sexes, males demonstrated significantly greater physical outputs in several variables and lower RPE compared to females (p < 0.05, moderate-to-large effects). Comparisons between playing levels revealed competitive males had significantly greater physical outputs across many variables, alongside higher mean heart rate and lower RPE than recreational males (p < 0.05, moderate-to-large effects). This study presents a novel game-specific basketball activity simulation protocol replicating actual playing durations and game configurations that might be successfully applied for both training and research purposes. Reliability statistics are provided for several variables to inform end-users on potential measurement error when implementing the simulation protocol. Discriminant validity of the simulation protocol was supported for several variables, suggesting it may hold practical utility in benchmarking or selecting players. Future research on this topic is encouraged examining wider samples of male and female basketball players at different levels as well as additional forms of validity for the protocol.
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This study aimed to (i) compare the extent of home-court advantage (HA) and home win percentage (HW) between Spanish basketball leagues across different playing levels (i.e., leagues) and (ii) analyze the influence of team ability on HA and HW within each playing level. We gathered data for game locations and results from open online sources for all games in the First Division (ACB), Second Division (LEB Gold), and Third Division (LEB Silver) Spanish male basketball leagues between 2010-2023. The dataset included 12 seasons, 635 teams (215 First Division, 203, Second Division, and 217 Third Division), and 19,539 games (7075 First Division, 6344 Second Division, and 5520 Third Division). We calculated HA [(total home wins/total wins) * 100] and HW [(total home wins/total home games) * 100] for each team across each season. We performed Kruskal Wallis tests, calculated partial eta squared (ηp2), and performed Mann-Whitney U tests with rank biserial correlation (rb) effect sizes and Dwass-Steel-Critchlow-Fligner pairwise comparisons to compare HA and HW between leagues and between team abilities (low, medium, and/or high) within each league. There was a significant effect for HA between leagues (p = .01) with post hoc comparisons revealing a higher HA for the First Division than for the Third Division (p = .01), but HW was not significantly different between leagues. In turn, variations in HA and HW between team abilities were consistent across playing levels, with HW significantly increasing in a progressive manner with higher team abilities (p < .001) and with HA significantly lower among high-level teams compared to lower-ability team clusters (p < .01). These findings emphasize the importance of considering playing level and team ability and interpreting HA and HW together to contextualize an apparent home advantage in Spanish basketball.