Relationship of body mass status with running and jumping performances in young basketball players

Basketball talent identification: a systematic review and meta-analysis of the anthropometric, physiological and physical performance factors

Background

The purpose of this study was to do a systematic review and meta-analysis about the anthropometric, physiological, and physical performance that discriminate the physical talent in basketball.

Methods

The search was conducted using the most relevant databases as Web of Science, PubMed, SPORTDiscus and Scopus, according to the PRISMA (2020) guideline. Keywords such as "basketball", "talented identification", "anthropometric", "physiology" and "physical performance" were used for the search, in English and following the "PICOS" question model. Eighteen articles' overall methodological quality was assessed using the Critical Review Forms.

Results

The study found in basketball, height, body mass, Yo-Yo test, T-test, 20 m sprint, and jump performance had statistical significance between elite and non-elite groups, including different positions and levels.

Conclusions

The reviewed literature highlighted a complicated relationship between anthropometric, physiological, and physical performance. Based on the results of the study, it's possible that height, body mass, agility, speed, endurance capacity, and lower lamb power could affect the early development of basketball.

Relations between specific athleticism and morphology in young basketball players

Introduction

Basketball is a fast-paced intermittent team sport, wherein the players must exhibit different morphologies and fitness levels depending on their position. The aim of this study was to assess the differences in the athleticism of basketball players by playing positions and in its relations with body composition and anthropometric measures. It was hypothesized that calculated athleticism has stronger and better predictive relations with morphology compared to motoric tests alone.

Methods

47 basketball players were divided into three groups according to playing position [guards (n = 14), forwards (n = 22), centers (n = 11)]. Body composition and anthropometrical measurements were done for all players. Athleticism was presented in terms of overall (OFS), jumping (JFS) and sprinting (SFS) fitness scores.

Results

Fitness scores were found to be more strongly related to body composition and anthropometry measurements than motoric tests alone. All three fitness scores were moderate to strongly correlated with skinfold thickness and fat percentage, while body height, fat-free mass, and lean body mass were positively correlated. Significant differences in athleticism fitness scores were found between guards and other groups. Forwards displayed superior athleticism in power and sprint abilities when compared to guards and centers. Multivariate logistic regression revealed that fat percentage, lean muscle mass, skinfold thickness, and arm span exhibited strong predictive capabilities in relation to athleticism scores.

Conclusions

Coaches and practitioners should be aware that athleticism includes a multitude of components, and they should use athleticism assessments before designing training regimens that are tailored to each position's unique needs.

Effects of Soluble Dietary Fibre on Exercise Performance and Perception of Fatigue in Young Basketball Players

Research background

In this study, we investigated the effects of soluble dietary fibre on improving neuromuscular and cardiovascular endurance and perception of fatigue in a closely monitored group of basketball players. Prebiotics have been sidelined in sports nutrition and their effect on performance remains poorly investigated and understood.

Experimental approach

Eighteen healthy male basketball players were divided into two groups; one received 17 g/day of soluble dietary fibre (Nutriose®) for four weeks and the other group received placebo. Their morphological characteristics, neuromuscular and cardiovascular endurance, and rating of perceived exertion according to the rating of perceived exertion (RPE) scale were assessed. Measurements were taken before supplementation and after four weeks of supplementation. Faecal samples were collected from all participants immediately before and after the supplementation period, their total DNA extracted and sent for amplicon sequencing.

Results and conclusions

In this study, fibre had no statistically significant effect on the vertical-type explosive power, no statistically significant effect on sprint-type explosive power, nor on aerobic and anaerobic endurance in the experimental group. Soluble fibre had a statistically significant effect on reducing the rating of perceived exertion of basketball players during the competitive part of the season (RPE 7.27±0.04 versus 8.82±0.81). This was confirmed by two-way ANOVA with replication, which showed that within-group interaction (p=0.0193), before and after dietary intake (p=0.0049), and between-group interaction before and after dietary intake (p=0.0313) had a significant effect on the result. The overall conclusion of the study is that soluble dietary fibre supplementation does not improve neuromuscular and cardiovascular endurance over a 4-week period. However, fibre supplementation could have a significant effect on reducing the rating of perceived exertion, as shown by the statistics. Both amplicon sequencing and subsequent bioinformatics results suggest that this could be the result of the beneficial effect on the intestinal microbiota and its metabolites.

Novelty and scientific contribution

This work highlights the importance of prebiotics in sports nutrition. Dietary fibre has been a neglected component of sports nutrition. This study demonstrated a statistically significant positive effect on the perception of fatigue, highlighting the need for further studies in this direction.

Clustering Performances in Elite Basketball Matches According to the Anthropometric Features of the Line-ups Based on Big Data Technology

The aims of this study were: 1) to conduct a descriptive analysis of the anthropometric features of the line-ups of strong teams (top 16) in the 2019 FIBA Basketball World Cup; 2) to group the line-ups mentioned above into different clusters based on their average height, weight, and body mass index (BMI); and 3) to explore the performance variables that discriminate between various line-up clusters. The play-by-play statistics were collected from 104 team objects in 67 games and 525 line-ups were analyzed using two-step cluster and discriminant analysis. Line-ups were classified into four groups: low average height and weight with middle BMI (LowH–LowW–MiddleBMI); high average height and low average weight with low BMI (HighH–LowW–LowBMI); low average height and high average weight with high BMI (LowH–HighW–HighBMI); high average height and weight with middle BMI (HighH–HighW–MiddleBMI). The results of the discriminant analysis demonstrated that LowH–LowW–MiddleBMI line-ups had the least time played and the lowest offensive rating, but the best offensive rebounds, turnovers, and fastest game pace performance; HighH–LowW–LowBMI line-ups demonstrated the best defensive rating but performed poorly with a low value of assists and a high value of turnovers; the LowH–HighW–HighBMI group achieved the best time played statistics but had the lowest number of free throws made; the HighH–HighW–MiddleBMI group had a higher number of assists and a higher offensive rating and 2-point field goal performance, while also achieving the lowest number of offensive rebounds and ball possessions. These results provide novel insights for coaches and performance analysts to better understand the technical characteristics of different line-ups in elite basketball competitions.

Effect of maturity timing on the physical performance of male Polish basketball players aged 13 to 15 years

The aims of this study were (i) to identify the motor potential and basic anthropometric characteristics of Polish basketball players aged 13 to 15 years, (ii) to demonstrate the effect of maturity timing on the results achieved in motor tests and basic body composition parameters, and (iii) to determine which index contributes most to the prediction of performance in the individual tests of speed, jumping ability, agility, and endurance. The sample included 818 male Polish players. Analysis of values related to age-adjusted characteristics showed that in the under 13-year-old group, early maturers had significantly better results (except for stage 1 in the agility test) than average maturers. However, in the endurance test in the under 14- and 15-year-old groups (both distance covered and VO_2max), the average maturers obtained higher values. Furthermore, maturity differentiation in the under 14- and 15-year-old groups significantly affected body size, 20-m sprinting time (under 14-year-old group only), and the results of all jumping tests. ANCOVA results (age, body height, and body mass as covariates) showed better results of early maturers in the under 13-year-old group. The opposite trend was observed in the under 14- to 15-year-old groups, where early maturing individuals performed worse in the running vertical jump (VJ) and endurance tests (both distances covered and VO_2max). Maturity timing (VJ and VO₂max), chronological age (5 m, 10 m, 20 m, agility, and VO_2max tests), body height (all tests), body mass (5 m), and the interaction between body mass and height (10 m, 20 m, agility, standing vertical jump, vertical jump) were significant (adjusted R² = 0.08–0.25; p < 0.001) predictors of motor skills. These findings can be helpful in quantifying and controlling the results of youth sports programs adjusted to biological requirements used in the training process.

Player Profiling and Monitoring in Basketball: A Delphi Study of the Most Important Non-Game Performance Indicators from the Perspective of Elite Athlete Coaches

BACKGROUND

Little is known about which indicators of performance elite athlete coaches (i.e., professional coaches who coach at the national or international levels) consider to be important for basketball.

OBJECTIVE

Using a Delphi procedure, the aim of this study was to identify the non-game performance indicators elite athlete coaches consider to be important for the recruitment/selection of basketball players.

METHODS

Ninety elite athlete coaches (basketball coaches (n = 71) and strength/conditioning coaches (n = 19) who coached men (n = 60), women (n = 23), or both (n = 7)), employed in 23 countries across six continents, participated in a three-round online Delphi survey. Round 1 asked coaches to identify the non-game performance indicators (i.e., measures other than game statistics) they currently used (or would like to use) for player recruitment/selection, with common indicators combined into single indicators. Round 2 asked coaches to rate the importance of each performance indicator using a Likert scale (range: 0 = no importance whatsoever to 10 = extremely important). Round 3 asked coaches to identify the single best test measure for each indicator rated ≥ 6 (i.e., important to extremely important) in Round 2. Results were reported descriptively.

RESULTS

A total of 608 responses (344 after removal of duplicates) were reported in Round 1, which were collapsed into 35 indicators, all of which were rated as 'important' in Round 2. Psychological and game intelligence indicators were typically rated as very important to extremely important (i.e., median = 9), with physical fitness and movement skills typically rated as very important (i.e., median = 8). For most indicators, coach observation was identified as the best test measure, with unique objective performance/anthropometric tests identified for all physical fitness indicators.

CONCLUSION

This study identified a range of psychological, game intelligence, physical fitness, and movement skill indicators that were considered by elite athlete coaches to be important to extremely important for the recruitment/selection of basketball players. These findings may inform the development of a basketball-specific test battery for recruiting/selecting and monitoring players.

Physiological and Anthropometric Determinants of Performance Levels in Professional Futsal

There is an evident lack of studies examining the pursuit of excellence in futsal. The aims of this study were to evaluate anthropometric and physiological variables that may contribute to distinguishing among performance levels in professional futsal players and to evaluate correlates of those variables. The participants were 75 male professionals (age = 25.1 ± 5.1 years, body height = 182.3 ± 6.2 cm, body mass = 80.8 ± 10.4 kg), who were divided into performance levels using two criteria: (i) starters (first teams) vs. non-starters (substitutes) and (ii) top-level players (members of the national team and players who participated in top-level team competition in Europe) vs. high-level players (team players competing at the highest national competitive rank). Variables included anthropometrics (body height and mass, BMI, body fat percentage), generic tests of physiological capacities [5- and 10-m sprints, countermovement jump, broad jump, 20-yard test, reactive strength index (RSI)], and futsal-specific fitness tests [kicking speed by dominant and non-dominant leg, futsal-specific tests of change of direction speed, and reactive agility (FSRAG) involving/not involving dribbling the ball]. Top-level players outperformed high-level players in RSI, broad jump, kicking speed, and FSRAG involving dribbling. Starters achieved better results than non-starters in fewer variables, including kicking speed and RSI. Body fat percentage negatively influenced FSRAG involving dribbling, and RSI. FSRAG, RSI, and kicking speed were significantly correlated, indicating the similar physiological background of these capacities. The findings suggest that enhanced reactive strength and the ability to rapidly change direction speed in response to external stimulus while executing futsal-specific motor tasks (e.g., dribbling), along with players' ability to kick the ball speedily, can be considered essential qualities required for advanced performance in futsal. Consequently, futsal strength and conditioning training should be targeted toward lowering relative body fat, maximizing lower-body reactive strength and including futsal-specific skills (e.g., dribbling, shooting) in reactive agility drills.

Associations of Body Composition, Maximum Strength, Power Characteristics with Sprinting, Jumping, and Intermittent Endurance Performance in Male Intercollegiate Soccer Players

The purpose of this study was to determine the relationships between body composition, strength, power characteristics, sprinting, jumping, and intermittent endurance performance in collegiate male players. Twenty-three players participated (19.7 ± 1.6 yrs; 71.8 ± 7.1 kg; 176.5 ± 5.1 cm). Measurements of interest in body composition included body fat percentage (BF%), lean body mass (LBM), and body mass (BM). Power characteristics were measured with an unloaded squat jump (SJ0) and loaded SJ at 20 kg (SJ20) and 40 kg (SJ40), and unloaded countermovement jump (CMJ0). Power assessments included peak power (PP) and PP allometrically scaled (PPa). Strength characteristics were assessed using isometric mid-thigh pull. Strength assessment included isometric peak force (IPF) and IPF allometrically scaled (IPFa). Performance measures included 10m and 20 m sprint time, CMJ0 jump-height, and Yo-Yo intermittent endurance test level 1 distance. Significant correlations ranging from moderate to very large were found for LBM and CMJ jump height (CM0 JH) (p = 0.01, r = 0.50); BF% and sprint times at 10 m (p = 0.03, r = 0.44) and 20 m (p = 0.02, r = 0.50). PP and PPa from SJ0 and CMJ0 were significantly correlated to 10m sprint time (p < 0.05, r = -0.45 to -0.53) and 20 m sprint time (p < 0.05, r = -0.40 to -0.49). Our findings agree with previous literature in that body composition and power characteristics are directly related to soccer-related performance.

Body Fat Is a Predictor of Physical Fitness in Obese Adolescent Handball Athletes

We examined the relationships between body fat (BF) and field measures of physical fitness in adolescent handball players. Twenty nine players (age: 16.6 ± 1.72 years; body mass: 79.8 ± 17.0 kg; height: 1.70 ± 0.12 m; body fat: 27.7 ± 8.67%) from Qatar handball first league performed a series of anthropometric and fitness tests related to their performance in sprinting (i.e., 15 m and 30 m sprint), jumping (i.e., countermovement and squat jumps), throwing (i.e., 3 kg medicine ball seated front throw) and running (i.e., agility T-Half and Yo-Yo intermittent recovery level 1 tests). Significant differences between obese and non-obese groups, classified based on age-stratified %BF norms, were found, with the largest difference being attributed to aerobic performance on the Yo-Yo test. Results indicated no significant relationships between anthropometric variables and sprinting or jumping abilities. %BF predicted a significant 8–15% portion in running performances of agility and aerobic capacity, while the latter were mainly explained by body height and mass. %BF was the only and strongest predictor of throwing performance, being an important determinant of performance in handball. Optimizing %BF should be considered as a training and nutrition goal in order to improve sport performance.

Fitness profiles of professional futsal players: identifying age-related differences

Study aim: The aim of this study was to determine the fitness profiles of senior and junior futsal players and to identify potential differences between the studied age groups.

Materials and methods: 44 male futsal players from 5 professional futsal teams participated in this study. Subjects were divided into two age groups (seniors [>18 years; n = 26] vs juniors [<18 years of age; n = 18]). Players were tested for anthropometrics (body mass, body height and body fat percentage), jumping capacity (countermovement jump and standing broad jump), kicking speed (for dominant and non-dominant leg), sprinting capacity (5- and 10-meter sprints), 20-yard test, futsal-specific reactive agility, and futsal-specific change-of-direction speed tests.

Results: No significant differences between age groups were apparent for anthropometrics. Seniors achieved better results than juniors in tests of kicking speed, for both the dominant (106.81 ± 6.94 km/h and 100.94 ± 5.33 km/h, respectively, t-test: 3.02 [p < 0.001], Cohen’s d: 1.02) and nondominant leg (95.54 ± 8.57 km/h and 85.28 ± 8.71 km/h, respectively, t-test: 3.88 [p < 0.001], Cohen’s d: 1.25).

Conclusions: Seniors did not achieve significantly better results than juniors in most of the observed variables. Since the maximum biological maturity occurs up to 18 years, and studied juniors were in their late adolescence, we can assume that differences between groups are related to other indices (i.e. technical skills, tactical knowledge).

The Relationship of Age and BMI with Physical Fitness in Futsal Players

The aim of this study was to examine the relationship of age and body mass status with field and laboratory measures of physical fitness in futsal players. Futsal players (n = 65, age 12.9 ± 2.8 years), who were classified into U11 (n = 28, 9-11 years), U13 (n = 21, 11-13 years), and adults (n = 16, >18 years), performed a physical fitness battery consisting of both laboratory and field tests. A similar prevalence of overweight (25%) was observed in all age groups (χ² = 1.94, p = 0.380, φ = 0.17). Age groups differed for all parameters, except body fat percentage, with adult players showing higher values than the younger groups (p < 0.05). U13 was heavier, taller, and had larger fat-free mass than U11 (p < 0.05). Adult players had superior values than their younger counterparts for all physical fitness parameters (p < 0.05). Body mass index (BMI) correlated inversely with aerobic capacity (U13), jumping ability, relative isometric muscle strength, and relative mean power in the Wingate anaerobic test (WAnT) (U11) (p < 0.05). Also, it correlated directly with absolute isometric muscle strength (U11) and peak power, mean power (all groups), and fatigue index (U11, U13) in WAnT (p < 0.05). Considering the results of this study, it was concluded that the prevalence of overweight in futsal players should be an important concern for practitioners working in this team sport. Optimizing BMI should be considered as a training and nutrition goal in order to improve sport performance.

Development of physical fitness performance in young Swiss men from 2006 to 2015

From 1980 to 2000, physical fitness decreased and body mass index (BMI) increased in the population of many industrialized countries. Little is known about these trends after the year 2000. This study aimed to investigate physical fitness performance, physical activity (PA) behavior, and BMI of young, male Swiss adults between 2006 and 2015. For this purpose, results from the Swiss Armed Forces mandatory recruitment were used. A total of 306 746 male conscripts provided complete fitness test data, mean ± SD (range from 5th to 95th percentile): 20 ± 1 (18‐21) years, 178 ± 7 (168‐189) cm; 74 ± 13 (58‐97) kg, predicted maximal oxygen consumption of 49.9 ± 4.6 (41.8‐56.9) mL/kg/min (Conconi test), 125 ± 58 (43‐232) seconds in trunk muscle strength test (prone bridge), 2.31 ± 0.24 (1.90‐2.66) m in standing long jump, 6.46 ± 0.73 (5.30‐7.70) m in seated shot put (2 kg medical‐ball shot) and 45.6 ± 12.2 (29.9‐66.7) seconds in one‐leg standing test (sum of both legs; eyes closed after 10 seconds and head tilted back after 20 seconds). In the investigated population, 73.8% fulfilled basic PA recommendations, 46.2% were classified as regularly vigorously active. Performances in aerobic endurance and muscle power did not show secular changes over time. However, core stability performance and PA behavior increased, while balance ability decreased over this 10‐year period. Average BMI increased by 2.0% between 2006 and 2010 and did not change thereafter. Male Swiss adults are at least as physically fit as they were a decade ago. The secular trends of decreasing physical performances and increasing BMI have stopped, and self‐reported sport participation and leisure time PA have been increased in the observed population over the last 10 years.

Field-Based Performance Tests Are Related to Body Fat Percentage and Fat-Free Mass, But Not Body Mass Index, in Youth Soccer Players

The primary aim of this study was to determine the association between body composition and performance outcomes in youth soccer players. Twenty-five competitive male youth soccer players (age = 13.7 ± 0.8 years, height = 167.4 ± 9.7 cm, weight = 57.6 ± 12.1 kg) volunteered to participate in this study. Height and weight were used to calculate body mass index (BMI). Body fat percentage (BF%) and fat-free mass (FFM) were determined with dual-energy X-ray absorptiometry. Each athlete performed the Pacer test, vertical jump, and t-test drill. Participants were predominantly normal weight (20.4 ± 2.7 kg·m-2). The body composition results were 20.3 ± 4.9% for BF% and 46.5 ± 8.7 kg for FFM. The results of the performance tests indicated a mean ± standard deviation (SD) of 1418 ± 332 m for Pacer, 57.2 ± 7.4 cm for vertical jump, 11.6 ± 0.7 s for t-test. Body mass index was not associated with any performance measure (r = 0.02 to -0.21, all p > 0.05). Body fat percentage was associated with the Pacer, vertical jump, and t-test (r = -0.62, -0.57, 0.61, respectively; all p < 0.01) and remained after accounting for BMI. Fat-free mass was only significantly related to t-test (r = -0.43, p < 0.01). However, after controlling for BMI, FFM was related to all three performance tests. Body fat percentage and FFM are associated with performance in youth soccer players, with stronger relationships reported in the former metric. The findings highlight the need for accurate body composition measurements as part of an assessment battery in young athletes.

The Effect of Heart Rate on Jump-Shot Accuracy of Adolescent Basketball Players

Basketball is a team sport, where fundamental skills - fundamentals - are key determinants for success. Jump-shot (JS) is a basketball fundamental used frequently during game. It is interesting to spread light on the relationship between effort intensity and JS ability. Study aim was to investigate different heart rates (HRs) effect on JS accuracy (JS%) in 22 male youth (15.7 ± 0.9 years) players. Experimental sessions consisted of 10 JSs from five spots 5 m from basket at three different HRs: rest (0HR) and after warm-up (50% [50HR] and 80% maximal HR [80HR]). Analysis of variance showed differences in JS% over sessions (42.27 ± 14.78% at 0HR, 38.18 ± 10.53% at 50HR, and 30.00 ± 16.62% at 80HR; P = 0.018). Least significant difference test did not show any significant difference between 50HR and 0HR JS% (P = 0.343), while 80HR elicited significantly lower values with respect to both 0HR (P = 0.006) and 50HR (P = 0.049). Study provided practical indications on maintaining high JS%: preliminary warm-up (even if injury-protecting) does not improve JS%, because between 50HR and 0HR difference was not significant; and 80HR significantly decreases JS%. Therefore, to maximize JS scoring players have to rest as much as possible during game-play pauses, and coaches should manage timeouts and substitutions accordingly, especially during final minutes of close games.

Anthropometry, Body Composition, and Performance in Sport-Specific Field Test in Female Wheelchair Basketball Players

Data on the physical and performance characteristics of female wheelchair basketball (WB) players are scarce. In several countries female WB players train and compete with male players on mixed teams due to the limited total population of players, which would otherwise lead to large territorial spread for each team. Any differences in terms of physical characteristics and/or WB skill proficiency between male and female WB players would be relevant to team performance in mixed teams. This work examined anthropometry, body composition, and performance in a set of sport-specific field tests in a sample of 13 female WB players representing about 40% of the eligible population in Italy across a range of functional point scores (Point). Point is assigned on an ordinal scale from 1.0 (i.e., players with minimal functional potential) through to 4.5 (players with maximum functional potential). Our female sample was then compared against twice as many (n = 26) Point-matched (±0.5 points) male players. The two groups were similar for age (P = 0.191; effect size [d] = 0.2), self-reported duration of injury (P = 0.144, d = 0.6), WB experience (P = 0.178, d = 0.5), and volume of training (P = 0.293, d = 0.4). The large majority of measured linear anthropometric variables (10/13) were lower in female players than males (0.001 < P ≤ 0.041). Skinfold-estimated percent body fat was higher (+7.6%) in females (30.7 ± 6.0%; P < 0.001, d = 1.3). Mean performance was worse in female than in males in six out of seven sport-specific field tests, scores being significantly lower in females for the maximal pass (7.5 ± 2.0 m for females vs. 10.4 ± 2.8 m for males; P = 0.002, d = 1.2) and suicide tests (55.8 ± 6.4 s for females vs. 45.4 ± 6.7 s for males; P < 0.001, d = 1.6). When performance in subgroups of females (n = 9) chosen across a range of Point was compared with that of males assigned 1.0 or 1.5 Point less (each n = 9), performance differences between male and female WB players were partially and completely eliminated, respectively. This work contributed new data for characterizing the physique and performance of female WB players. Further, the results suggested that when male and female athletes compete together in mixed teams, a 1.5 points subtraction from female players is needed to match the real gender difference in performance.

Do running speed and shoe cushioning influence impact loading and tibial shock in basketball players?

Background

Tibial stress fracture (TSF) is a common injury in basketball players. This condition has been associated with high tibial shock and impact loading, which can be affected by running speed, footwear condition, and footstrike pattern. However, these relationships were established in runners but not in basketball players, with very little research done on impact loading and speed. Hence, this study compared tibial shock, impact loading, and foot strike pattern in basketball players running at different speeds with different shoe cushioning properties/performances.

Methods

Eighteen male collegiate basketball players performed straight running trials with different shoe cushioning (regular-, better-, and best-cushioning) and running speed conditions (3.0 m/s vs. 6.0 m/s) on a flat instrumented runway. Tri-axial accelerometer, force plate and motion capture system were used to determine tibial accelerations, vertical ground reaction forces and footstrike patterns in each condition, respectively. Comfort perception was indicated on a 150 mm Visual Analogue Scale. A 2 (speed) × 3 (footwear) repeated measures ANOVA was used to examine the main effects of shoe cushioning and running speeds.

Results

Greater tibial shock (P < 0.001; η² = 0.80) and impact loading (P < 0.001; η² = 0.73-0.87) were experienced at faster running speeds. Interestingly, shoes with regular-cushioning or best-cushioning resulted in greater tibial shock (P = 0.03; η² = 0.39) and impact loading (P = 0.03; η² = 0.38-0.68) than shoes with better-cushioning. Basketball players continued using a rearfoot strike during running, regardless of running speed and footwear cushioning conditions (P > 0.14; η² = 0.13).

Discussion

There may be an optimal band of shoe cushioning for better protection against TSF. These findings may provide insights to formulate rehabilitation protocols for basketball players who are recovering from TSF.

Effect of Heart rate on Basketball Three-Point Shot Accuracy

The three-point shot (3S) is a fundamental basketball skill used frequently during a game, and is often a main determinant of the final result. The aim of the study was to investigate the effect of different metabolic conditions, in terms of heart rates, on 3S accuracy (3S%) in 24 male (Under 17) basketball players (age 16.3 ± 0.6 yrs). 3S performance was specifically investigated at different heart rates. All sessions consisted of 10 consecutive 3Ss from five different significant field spots just beyond the FIBA three-point line, i.e., about 7 m from the basket (two counter-clockwise “laps”) at different heart rates: rest (0HR), after warm-up (50%HRMAX [50HR]), and heart rate corresponding to 80% of its maximum value (80%HRMAX [80HR]). We found that 50HR does not significantly decrease 3S% (−15%, P = 0.255), while 80HR significantly does when compared to 0HR (−28%, P = 0.007). Given that 50HR does not decrease 3S% compared to 0HR, we believe that no preliminary warm-up is needed before entering a game in order to specifically achieve a high 3S%. Furthermore, 3S training should be performed in conditions of moderate-to-high fatigued state so that a high 3S% can be maintained during game-play.

Evaluation of different jumping tests in defining position-specific and performance-level differences in high level basketball players

The importance of jumping ability in basketball is well known, but there is an evident lack of studies that have examined different jumping testing protocols in basketball players at advanced levels. The aim of this study was to assess the applicability of different tests of jumping capacity in identifying differences between (i) playing position and (ii) competitive levels of professional players. Participants were 110 male professional basketball players (height: 194.92±8.09 cm; body mass: 89.33±10.91 kg; 21.58±3.92 years of age; Guards, 49; Forwards, 22; Centres, 39) who competed in the first (n = 58) and second division (n = 52). The variables included anthropometrics and jumping test performance. Jumping performances were evaluated by the standing broad jump (SBJ), countermovement jump (CMJ), reactive strength index (RSI), repeated reactive strength ability (RRSA) and four running vertical jumps: maximal jump with (i) take-off from the dominant leg and (ii) non-dominant leg, lay-up shot jump with take-off from the (iii) dominant leg and (iv) non-dominant leg. First-division players were taller (ES: 0.76, 95%CI: 0.35-1.16, moderate differences), heavier (0.69, 0.29-1.10), had higher maximal reach height (0.67, 0.26-1.07, moderate differences), and had lower body fat % (-0.87, -1.27-0.45, moderate differences) than second-division players. The playing positions differed significantly in three of four running jump achievements, RSI and RRSA, with Centres being least successful. The first-division players were superior to second-division players in SBJ (0.63, 0.23-1.03; 0.87, 0.26-1.43; 0.76, 0.11-1.63, all moderate differences, for total sample, Guards, and Forwards, respectively). Running vertical jumps and repeated jumping capacity can be used as valid measures of position-specific jumping ability in basketball. The differences between playing levels in vertical jumping achievement can be observed by assessing vertical jump scores together with differences in anthropometric indices between levels.

Weekly physical activity patterns of university students: Are athletes more active than non-athletes?

The aim of the present study was to compare weekly physical activity (PA) and obesity-related markers in athlete and non-athlete university students. One hundred and twenty-six university students (53 males, 20.46 ± 2.04 years old, and 73 females, 19.69 ± 1.32 years old) participated in this study. Participants were fitted with a tri-axial accelerometer (ActiGraph wGT3X-BT, Shalimar, FL, USA) to assess the daily PA. Anthropometric measures of height, weight, BMI and %fat mass were determined with a stadiometer and an electronic scale. The comparison indicated that male and female athletes had a significant lower percentage of body fat than did non-athletes (p value = 0.001; ES = 0.043). Athletes spent significantly more time in light PA than did non-athletes (p value = 0.003; ES = 0.024). Female athletes spent significantly less time in sedentary mode than did non-athletes (p value = 0.040; ES = 0.008). On the other hand, female athletes spent significantly more time in light PA (p value = 0.003; ES = 0.017) and vigorous PA (p value = 0.001; ES = 0.086) than did non-athletes. Despite some statistical differences with minimal effect size, the results of this study suggested proximity between PA levels of athletes and non-athletes, mainly in the case of sedentary behaviour. No significant effects were found in the variances of PA tested in this study.

Acute Responses to 10×15 m Repeated Sprint Ability Exercise in Adolescent Athletes: the Role of Change of Direction and Sport Specialization

Background

The repeated sprint ability (RSA) has been studied with protocols using distances longer than 20 m per sprint, whereas basketball players cover on average less than 20-meter distance per sprint during match.

Objectives

The aim of the present study was to examine the physiological impact of 10 × 15 m RSA test in straight-line (RSASL) or with change of direction (RSACOD), i.e. 10 × (7.5 + 7.5 m)) in young national level basketball players.

Patients and Methods

Young basketball players (n = 11, age 17.1 (1.0) years, body mass 76 (6) kg, height 184 (4) cm, body mass index 22.6 (1.8) kgm^-2, sport experience 6.9 (2.7) years, mean (standard deviation)) and a control group consisting of high-school athletes (n = 7, 16.1 (0.7) years, 67 (6) kg, 177 (6) cm, 21.5 (1.0) kgm^-2, 7.7 (1.6) years, respectively) performed RSASL and RSACOD on a counter-balanced order. Sprints started every 30 seconds (active recovery) and there was 30 minutes break between RSA protocols; time variables were total time (TT), best time (BT) and fatigue index (FI). Countermovement jump (CMJ) was tested before and after each RSA protocol. Heart rate (HR) was continuously monitored during testing procedures.

Results

Compared with RSASL, TT and BT were worst in RSACOD (38.13 vs. 27.52 s and 3.67 vs. 2.66 s, P < 0.001, respectively), whereas FI did not differ (3.8 vs. 3.5%, P = 0.388). A 2 × 2 repeated measures ANOVA showed main effect of RSA on CMJ (pre-test vs. post-test, increase + 1.8 cm, P = 0.020, η² = 0.28); there was neither main effect of RSA protocols (RSASL vs. RSACOD +0.7 cm, P = 0.251, η² = 0.08) nor an interaction between pre-post measurements and RSA protocols (P = 0.578, η² = 0.02). Compared with RSASL, RSACOD induced higher mean and peak HR responses (175 vs 172 bpm, P < 0.001, and 185 vs 182 bpm, P = 0.002, respectively). No statistical difference was observed between basketball players and control group neither for TT (27.98 vs. 26.80 seconds, + 4.4%, P = 0.149) and BT (2.71 vs. 2.59 seconds, + 4.5%, P = 0.157) in RSASL nor for TT (38.55 vs. 37.47 seconds, + 2.9%, P = 0.169) and BT (3.70 vs. 3.63 seconds, 1.8%, P = 0.414) in RSACOD.

Conclusions

In conclusion, RSASL and RSACOD differed for time variables (TT and BT) and HR responses. Despite being non-significant, the trend that adding COD reduced the percentage differences in TT and BT between the two groups highlighted the role of sport specialization.