This study aimed to investigate the single and combined effects of sleep restriction (SR) and mental fatigue (MF) on free-throw (FT) performance among adult male basketball players.
A total of 19 ...amateur male basketball players performed, in a randomized, counterbalanced, and crossover order, 2 identical experimental sessions separated by an interval of 1 week. The difference between the 2 sessions was in the quantity of sleep the night before the sessions, as follows: in one case, the participants followed their habitual sleep-wake routines; in the other session, they were forced to sleep not more than 5 hours. During the experimental sessions, the participants performed 60 basketball FTs on 2 occasions, separated by watching a basketball tactical video for 30 minutes designed to induce MF. As such, the FT test was completed in 4 different conditions: control, MF, SR, and SR and MF combined.
The participants registered a significantly lower total sleep time in acute SR (P < .001). The subjective rating of MF was lower in the control than in MF, SR, and SR and MF combined (P < .001). There were no differences between conditions for the subjective ratings of motivation. FT accuracy was higher in the control than in MF, SR, and SR and MF combined (P = .010), while no differences were observed between the 3 experimental conditions (all P > .05).
The results indicate that a combined effect of MF and SR induces a small reduction in basketball FT performance, similar to MF or SR alone.
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).
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.
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.
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.
This study aimed to examine the effect of a 6-day basketball tournament on the physical demands, perceptual-physiological responses, well-being, and game statistics of elite under-18 (years of age) ...players.
Physical demands (player load PL, steps, impacts, and jumps, all normalized by playing time), perceptual-physiological responses (heart rate and rating of perceived exertion), well-being (Hooper index), and game statistics of 12 basketball players were monitored during 6 consecutive games. Linear mixed models and Cohen d effect sizes were used to assess differences among games.
Significant changes were found for PL per minute, steps per minute, impacts per minute, peak heart rate, and Hooper index over the tournament. Pairwise comparisons showed that PL per minute was higher in game #1 than in games #4 (P = .011, large), #5 (P < .001, very large), and #6 (P < .001, very large). PL per minute recorded during game #5 was also lower than in games #2 (P = .041, large) and #3 (P = .035, large). The number of steps per minute was higher in game #1 than in all other games (all P < .05, large to very large). Impacts per minute were significantly higher in game #3 than in games #1 (P = .035, large) and #2 (P = .004, large). The only physiological variable that varied significantly was peak heart rate (higher in game #3 than in game #6; P = .025, large). The Hooper index gradually increased throughout the tournament, indicating poorer player well-being as the tournament advanced. Game statistics did not significantly change among games.
The average intensities of each game and the players' well-being gradually decreased throughout the tournament. Conversely, physiological responses were mostly unaffected, and game statistics were unaffected.
To assess weekly fluctuations in hormonal responses and their relationships with load and well-being during a congested in-season phase in basketball players.
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.
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.
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.
To investigate the 1) effect of the preparation period on the neuromuscular characteristics of 12 professional (PRO) and 16 semi-professional (SEMI-PRO) basketball players; 2) relationships between ...training load indices and changes in neuromuscular physical performance.
Prior to and following the preparation period, players underwent a counter-movement jump (CMJ) test, followed by a repeated change of direction (COD) test consisting of 4 levels with increasing intensities. The peripheral neuromuscular functions of the knee extensors (peak torque, PT) were measured using electrical stimulations after each level (PT1, PT2, PT3 and PT4). Furthermore, PT Max (the highest value of PT) and PT Dec (PT decrement from PT Max to PT4) were calculated.
Trivial-to-small (effect size, ES: -0.17 to 0.46) improvements were found in CMJ variables, regardless of the competitive levels. After the preparation period, peripheral fatigue induced by a COD test was similarly reduced in both PRO (PT Dec: from 27.8±21.3% to 11.4±13.7%, ES±90%CI= -0.71±0.30) and SEMI-PRO (PT Dec: from 26.1±21.9% to 10.2±8.2%, ES±90%CI= -0.69±0.32). Moderate-to-large relationships were found between session rating of perceived exertion training load and changes in PPO measured during the CMJs (r
±90%CI: PPOabs, -0.46±0.26; PPOrel, -0.53±0.23) and in some PTs measured during the COD test (PT1, -0.45±0.26; PT2, -0.44±0.26; PT3, -0.40±0.27 and PT Max, -0.38±0.28).
Preparation period induced minimal changes in the CMJ, while the ability to sustain repeated COD efforts was improved. Reaching high session rating of perceived exertion training loads might partially and negatively affect the ability to produce strength and power.
This study examined the association and predictive ability of internal load markers (based on rating of perceived exertion, RPE) with non-contact injuries in basketball. 35 basketball players (age: ...24 ± 6 years, stature: 196 ± 9 cm, body mass: 91 ± 12 kg) were prospectively followed during 1 or 2 seasons, during which non-contact injuries were recorded. Markers examined were: mean weekly RPE, weekly load, exposure, week-to-week load change, acute:chronic 1:2, 1:3, 1:4 load ratio. A generalized estimating equations analysis was used to determine association with non-contact injury in the subsequent week. Prediction was examined with receiver operating characteristic curve, area under the curve (AUC) and Youden index. No associations were found between load markers and non-contact injuries (all p > 0.05); load markers showed no injury predictive ability (AUC range: 0.468-537; Youden index range: 0.019-132). In conclusion, the load markers selected are not associated with non-contact injuries and they cannot be used to predict injuries in basketball.
To examine differences between adult male basketball players of different competitive levels (study 1) and changes over a basketball season (study 2) of knee-extensor peripheral muscle function ...during multistage change-of-direction exercise (MCODE).
In study 1, 111 players from 4 different divisions completed the MCODE during the regular season. In study 2, the MCODE was performed before (T1) and after (T2) the preparation period and during the competitive season (T3) by 32 players from divisions I, II, and III. The MCODE comprised 4 levels of increasing intensity for each player. The twitch peak torque (PT) of knee extensors was measured after each level. PT
(the highest value of PT) and fatigue were calculated.
In study 1, the authors found possibly small differences (effect size ES 90% confidence interval -0.24 0.39) in fatigue between divisions I and II. Division I was characterized by likely (ES 0.30-0.65) and very likely to almost certain (ES 0.74-1.41) better PT
and fatigue levels than divisions III and VI, respectively. In study 2, fatigue was very likely reduced (ES -0.91 to -0.51) among all divisions from T1 to T2, whereas PT
was likely to very likely reduced (ES -0.51 to -0.39) in divisions II and III.
Professional basketball players are characterized by a better peripheral muscle function during MCODE. Most of the seasonal changes in peripheral muscle function occurred after the preparation period. These findings inform practitioners on the development of training programs to enhance the ability to sustain repeated change-of-direction efforts.
Peripheral fatigue in knee extensor (KE) and plantar flexor (PF) muscles were investigated following repeated-sprint ability (RSA) cycling and running tests.
Both RSA tests involved 5x6 s sprints and ...peripheral fatigue was quantified using diverse electrical stimulations (1Hz, 10Hz, 20Hz, 50Hz and 100Hz).
RSA cycling induced higher KE decrements in peak torque (PT), maximal rate of torque development and relaxation (PT decrements at different stimulation frequencies: from -39% to -53% cycling vs. -16% to -39% running, P<0.049). The PT ratios of the KE did not highlight differences in low-frequency fatigue. No major differences were noted in PT decrements of PF (P>0.231); however, greater reductions in some PT ratios (10/100 Hz, 20/50 Hz and 20/100 Hz) confirmed the presence of low-frequency fatigue in PF following RSA cycling. Subjects reported significantly higher RPE leg values following RSA cycling (8.2 vs 7.3 respectively, P=0.018) despite no differences in blood lactate, hydrogen ions and bicarbonates (P>0.467).
Higher levels of peripheral fatigue induced by RSA cycling may be partially related to longer fractional duration of muscle contraction phases that can limit local blood flow. The discrepancies in neuromuscular fatigue between KE and PF can be explained by differences in muscle fibre composition or muscle contributions during RSA tests.
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