1. Introduction
Among the determinants of basketball players’ performance, neuromuscular properties can play a very important role, especially in jumping ability [1]. Despite the number of jumps that a basketball player performs per game, it only counts for about 1.5% of the total playing time [2]. However, these jumps can determine the outcome of the game, since they are key for successful rebounds, blocks, and fast breaks.
Jumping ability is not only an essential determinant of on-court success but also a differentiating factor between players of different skill levels and positions. Vertical jumping performance has significantly correlated with draft position and subsequent game performance in the NBA [3]. Players drafted into the NBA consistently outperform undrafted players in vertical jump height and reach, highlighting its importance as a scouting metric [4]. Cui et al. [4] also pointed out the importance of speed running and agility as key performance metrics that can distinguish drafted and undrafted players.
Countermovement Jump (CMJ) and Squat Jump (SJ) are neuromuscular tests commonly used to assess the physical qualities underpinning basketball performance [1,5,6,7]. These jumping tests provide reliable insights into lower-limb power and neuromuscular coordination. On one hand, the CMJ, with or without an arm swing, is particularly valuable for assessing explosive strength, while the SJ isolates concentric muscle actions, offering a focused measure of lower-limb power [8]. Although SJ, CMJ, and Arm Swing CMJ (CMJA) assess slightly different capabilities, performing all of them provides a more comprehensive evaluation of a player’s performance. In this regard, unilateral CMJ is also a valuable test, as it offers insight into single-leg performance and helps identify inter-limb asymmetry. These jumping tests have shown high validity (strong correlations with strength and sprint performance) and reliability (high intraclass correlation coefficient) [9]. However, the sample was composed of soccer and basketball players, with different age groups (Under 15, Under 18, and Adults) and performance levels (adult player competing in the 3rd and 4th division).
Moreover, linear sprinting tests, especially over distances of 10 and 20 m, are also widely used to assess basketball-specific speed and anaerobic power. These attributes are critical for basketball performance, playing a key role in fast breaks, defensive recoveries, and transition plays [10]. In fact, the reactive repeated sprint test has shown moderate to high reliability (ICC > 0.80) and has been effective in distinguishing between professional and semiprofessional players [11].
Neuromuscular performance assessment through field-based tests is a fundamental component of performance monitoring in high-level sports. In basketball, jumping and sprinting tests are widely used due to their practicality and sensitivity in detecting fatigue and neuromuscular status. On the one hand, CMJ has proven to be the most reliable and robust measure across multiple time points post-fatigue, whereas the drop jump, while the most sensitive, is less consistent [12]. Although sprint performance has shown excellent repeatability, its sensitivity is primarily limited to the early stages of fatigue, further supporting the inclusion of jump-based tests as more informative tools for longitudinal neuromuscular monitoring. Furthermore, jumping and sprinting validity has been related to athletic performance. Rodríguez-Rosell et al. [9] concluded that both traditional and sport-specific vertical jump tests show high reliability and are strongly correlated with leg strength and sprint ability in soccer and basketball players across different age groups. Notably, the CMJ and bilateral sport-specific jump were identified as the most useful indicators of lower-limb neuromuscular power. Similarly, moderate to strong correlations between sprint, agility, and jump tests were obtained in youth soccer players, reinforcing their concurrent validity as markers of neuromuscular performance [13]. Therefore, standardized jumping and sprinting tests appear to be a valid and reliable tool for monitoring neuromuscular status in both developmental and elite sport contexts.
Basketball-specific playing positions entail distinct physical requirements, making neuromuscular demands highly position-dependent. Guards, for instance, perform more high-intensity movements such as sprinting and shuffling, while centers and forwards (Bigs) engage in more strength-based actions, such as post-ups and rebounds [14]. Positional differences are also evident in jump frequency, with Bigs averaging 49 jumps per game compared to 41 jumps for Guards [15]. This fact is not always taken into consideration, and it is extremely important for training specificity.
Despite the widespread use of neuromuscular tests, high-quality data on their application in professional basketball players remain limited. Most studies focus on amateur or young players, limiting their generalizability to higher level players. Furthermore, strength and conditioning coaches in professional basketball face time constraints, so they must carefully analyze the cost–benefit ratio of each physical test. Therefore, it seems necessary to explore which jumping and linear sprinting tests are the most valid and reliable for assessing professional basketball players’ neuromuscular performance, as well as the minimum change required to identify an improvement in professional basketball players’ physical condition. This could make it easier for basketball coaches to decide which jumping and linear sprinting tests to carry out with their players.
Therefore, this study aims to analyze intra-day reliability of different jumping and linear sprinting tests to assess neuromuscular performance in professional male basketball players, based on their specific playing position (Bigs vs. Guards). We hypothesize that linear sprint tests over 10 and 20 m will exhibit higher intra-day reliability and a lower percentage of minimum detectable change (MDC) for assessing basketball-specific neuromuscular performance. Additionally, we expect that both playing positions will show very similar results in terms of absolute and relative reliability, as well as MDC.
2. Materials and Methods
2.1. Study Design
A transversal study design was used to determine the reliability and validity of jumping and linear sprinting tests for professional basketball players, based on their playing position. All basketball players conducted the assessment during preseason. The protocol was performed in the following order: first, the jumping tests (SJ, CMJ, right and left SL-CMJ, and CMJA), followed by the linear sprinting tests (5, 10, and 20 m) (Figure 1). These jumping and linear sprinting tests were chosen due to their usefulness in both assessing neuromuscular fatigue [12] as well as neuromuscular performance [9,13].
Jumping testing was carried out on court, after a protocolized 12 min warm-up designed to optimize neuromuscular readiness while minimizing fatigue. The protocol warm-up general mobility exercises, low-intensity multidirectional movements, dynamic stretching, and progression from low-level to high-level plyometric drills. Each athlete then performed two submaximal practice attempts for each jump test to ensure technical familiarity. Then, players performed two practice attempts for each jump, separated by self-preferred rest period. This methodological decision was based on previous evidence suggesting that self-selected rest intervals may be superior to fixed rest intervals in optimizing neuromuscular performance. Hence, allowing athletes to determine their own recovery time accounts for individual differences in neuromuscular profiles and may reduce the risk of residual fatigue during subsequent efforts [16]. The jumping testing protocol followed the following order: SJ, CMJ, SL-CMJ, and CMJA. Players were encouraged in each jump to reach the highest possible height. Recovery time was estimated as complete between each assessment.
Linear sprinting testing was carried out next, following a standardized warm-up focused specifically on sprint mechanics. This included sprint-specific drills and two progressive efforts of 10 and 5 m at 80% and 90%, respectively, of maximum speed. The linear sprinting testing protocol followed the following order: 5, 10, and 20 m. Participants were randomized to avoid systematic bias, and instructed to run at their maximum possible speed while maintaining their effort beyond the timing gates. To reinforce this instruction, two additional barriers were positioned 1 m beyond the timing gates, encouraging players to sprint through to these secondary barriers.
2.2. Participants
One hundred two male professional basketball players from the German Basketball Bundesliga (47), Basketball Champions League (39), and Spanish Basketball League (16) were evaluated during preseason (age: 24.5 ± 3.4 years; body mass: 94.9 ± 10.8 kg; height: 197 ± 9.5 cm; fat %: 8.9 ± 1.8). However, sample size was calculated using G*power v3.1.9.4 for Windows (Heinrich-Heine-Universität Düsseldorf, Germany) for ANOVA repeated measures (2 assessment) with factor group, based upon an effect size of 0.25, a power of 0.95, and an alpha level of 0.05, indicating a needed sample size of 38 players.
Players were divided according to their playing position: 56 Guards (point guards, shooting guards, and small forwards) and 46 Bigs (centers and power forwards). This novel classification is based on modern basketball, where tactical responsibilities in elite players are now more influenced by functional demands than by nominal playing positions [17].
All players included in the study were injury-free and without physical limitations that could compromise the testing protocol. Players who reported an injury or discomfort during data collection were excluded from the study. All participants were informed about the nature, aims, and risks associated with the testing protocol. A signed informed consent was obtained from all basketball players. This study was approved by the local research ethics committee and conducted in accordance with the Declaration of Helsinki (64th WMA General Assembly, Fortaleza, Brazil, 2013).
2.3. Procedure
All performance assessments were carried out indoors on a hardwood basketball court under standardized environmental conditions to ensure consistency and replicability. The air temperature was maintained between 18 and 22 °C, with relative humidity ranging from 40 to 60%, in accordance with FIBA and sport performance testing recommendations. Adequate ventilation was ensured to maintain air quality and avoid thermal discomfort. The playing surface was regularly cleaned and dried before testing to prevent slippage and ensure proper traction. Lighting was uniform and met FIBA regulations.
Jumping ability was inferred by players’ flying time using a Chronojump BoscoSystem contact platform (v.1.7.0 for Windows, CHRONOJUMP Boscosystem®, Barcelona, Spain). This tool has been shown to have good reliability for measuring vertical jumps (ICC = 0.95) [18]. The jumping protocol was conducted individually with the researcher, completing the battery of tests in isolation to eliminate external distractions or pacing influences.
Linear sprinting time was recorded by the Microgate Witty Wireless Trainer Timer® (Microgate Srl, Bolzano, Italy). This photocell system is considered as a reference tool for sprint testing [19]. The linear sprinting protocol test was conducted in a group format. Each player completed their first maximal sprint attempt, followed immediately by their second attempt after all players had completed round one. Full rest was ensured between each attempt, as sufficient time was allowed for recovery between attempts.
2.3.1. Squat Jump
Squat Jump (SJ) was performed following Toumi et al.’s [20] protocol. Players were asked to go down to a semi squat position, maintaining this position for 2 s until the evaluator said “Go!”. Each player was allowed to self-select their knee angle, since knee flexion differences between 90°, 100°, and the self-selected knee angles are trivial [21] and may offer advantages in terms of both inter-session reliability and natural movement biomechanics [22]. Nevertheless, almost every player chose a depth within this range. During all jumps, arms had to be kept on the hips to prevent the use of upper limbs, thus eliminating elastic properties and upper body influence to isolate concentric strength.
2.3.2. Countermovement Jump
Countermovement Jump (CMJ) was carried out similarly to the SJ, without maintaining knee flexion position and performing a fast and explosive countermovement [9,20,23]. Players kept their hands on their hips, went down to a preferred place, and then tried to jump as high as possible. With this jump we tested not only the concentric strength, but also the elastic properties of the muscle-tendon structure of the player.
2.3.3. Single-Leg Countermovement Jump
The Single-Leg Countermovement Jump (SL-CMJ) was carried out similarly to the 2-legged CMJ. Players were asked to maintain balance on one leg with their hands on their hips, and, whenever they were ready, they were required to perform a maximum height jump while keeping their hands on their hips [9,20,23,24]. This jump not only aims to assess the concentric strength, but also the elastic properties of the muscle-tendon structure of the player as well as the asymmetry between legs.
2.3.4. Arm Swing Countermovement Jump
Arm Swing CMJ (CMJA) was performed with the only rule that the player must reach the maximum possible height [9]. To achieve it, they could use their upper limbs, reach their preferred depth in the impulse phase, and perform this phase faster or slower. We tried to analyze not only the concentric strength and the elastic properties but also the coordination specific skills.
2.3.5. Linear Sprinting Tests
Linear sprinting tests were performed over 5, 10, and 20 m. Each player was asked to step right before the photocells, as close as possible without cutting the line between each timing gate. The player started the test at their own discretion, with no external cues. The order was randomized. Players were strongly encouraged to not slow down before the second pair of timing gates. To achieve this goal, two cones were placed one meter after the second gate as a reference, helping players maintain maximal effort until reaching the second barrier.
2.4. Statistical Analysis
Application of the Kolmogorov–Smirnov test, in conjunction with the Lilliefors test, showed that the sample distribution was normal, linear, and homoscedastic. The relative reliability analysis was carried out by calculating the Intraclass Correlation Index (ICC), by single measures, 2-way mixed effects model and absolute agreement [25]. Values below 0.5 indicate poor reliability, between 0.5 and 0.75 moderate reliability, between 0.75 and 0.9 a good reliability, and above 0.9 indicates excellent reliability [26]. The coefficient of variation (CV) for raw data were calculated and used as an absolute reliability indicator [27]. A value above 10% has been considered insufficient absolute reliability [28]. The standard error of measurement (SEM, %SEM) and the minimum detectable change (MDC, %MDC) have also been used as complementary absolute reliability measures [28]. The SEM can be estimated as the square root of the mean square error term from the repeated measures ANOVA [29] SEM = √MSE, where MSE is the mean square error term from the repeated measures ANOVA [29]; % SEM was calculated as SEM/M × 100 [30], where M is the mean of the two intra-day measurement. MDC was calculated as SEM × 1.96 × √2 [29], %MDC was expressed as MDC/M × 100 [28] where M is the mean value of the two intra-day measurements. Analyses were carried out for all data and according to the players’ specific playing position (Guards vs. Bigs).
3. Results
As can be seen in Table 1, all neuromuscular tests, both jumping and linear sprinting, present very good absolute reliability (%CV < 3% and SEM < 8%). The %MDC for jumping test was between 5.38 and 20.82% and between 4.76 and 10.43% for linear sprinting tests.
The linear sprinting performance assessment over 10 and 20 m together with the CMJA obtained excellent absolute reliability (CV: 0.1–1.4%; 1.74–2.31% of SEM) and a lower MDC (4.76–6.36%). The unilateral jumping test (SL-CMJ) obtained a good absolute reliability (CV:1.6–2.5%; 4.96–7.92% of SEM) presents a higher percentage of MDC (13.75–20.82%), especially the jumping with the left leg.
In addition, relative reliability shows good to excellent reliability in the 10 and 20 m linear sprinting tests and in the jumping tests CMJ, SJ and SL-CMJ with the right leg. The 5 m linear sprint and CMJA showed moderate to excellent relative reliability while the unilateral jumping tests with the left leg showed the lowest relative reliability of the set of tests (low-excellent).
Regarding the analysis based on specific playing positions, both Bigs and Guards maintained very similar results to those in Table 1. Both have excellent absolute reliability in all tests. In the linear sprint there are hardly any differences in CV and %SEM. However, Bigs have better absolute reliability in SJ, CMJ, SL-CMJ, (CV: 0.9 vs. 1.8; 1.7 vs. 3.2; 1.7 vs. 3.1%, respectively) while Guards only have better absolute reliability in CMJA (CV: 1.3 vs. 1.6%; %SEM: 1.78 vs. 2.25%).
In relative reliability, Bigs have a better ICC than Guards in SJ, CMJ and CMJA (0.97 vs. 0.94; 0.95 vs. 0.90; 0.98 vs. 0.97, respectively) and in 10 and 20 m linear sprint (0.92 vs. 0.88; 0.92 vs. 0.90, respectively). On the contrary, Guards have a better reliability in SL-CMJ in both legs (0.90 vs. 0.83 right leg and 0.92 vs. 0.87 left leg) and in 5 m linear sprint (0.81 vs. 0.74).
The %MDC is lower in Bigs in SJ (4.49 vs. 8.72%), CMJ (7.76 vs. 14.15%), SL-CMJ left leg (16.70 vs. 17.03%), linear sprint 10 m (4.44 vs. 6.52%) and 20 m (4.76 vs. 4.89%). On the contrary, Guards show a higher %MDC in CMJA (6.25 vs. 4.95%), SL-CMJ right (23.04 vs. 17.21%) and linear sprint 5 m (12.52 vs. 7.30%).
4. Discussion
The main findings of this study indicate that the CMJA and the linear sprinting test over 10 and 20 m showed an excellent absolute reliability and good to excellent relative reliability, along with a low MDC. In contrast, although the SL-CMJ exhibits good absolute reliability, it is characterized by a notably higher MDC, particularly for the left leg, which also shows a poor–excellent relative reliability. Position-specific analysis revealed that Bigs demonstrated higher absolute reliability in SJ, CMJ and SL-CMJ, while Guards showed better absolute reliability in CMJA. Regarding relative reliability, Bigs have showed better ICC than Guards in SJ, CMJ, and CMJA and in 10 and 20 m linear sprint. Meanwhile, Guards exhibited better reliability in SL-CMJ in both right and left leg, as well as in 5 m linear sprinting test. Therefore, due to the ability of these tests to detect neuromuscular changes during the preseason, these findings encourage basketball physical coaches to use these jumping and sprinting tests to assess preseason neuromuscular performance.
The good to excellent relative reliability and the high absolute reliability together with the low CV, SEM, and MDC obtained in the jumping test CMJ and SJ, and the sprinting test over 10 and 20 m allows us to indicate the high sensitivity that these tests have to detect significant improvements in neuromuscular performance. This aspect is of great importance due to the small differences that have a big impact on professional sport [31]. In addition, these results highlight the importance of these tests for assessing speed and explosive capacity in basketball players, particularly given the role of sprinting and jumping in game scenarios [4].
Our results are very similar to those from Heishman et al. [7] who also found high reliability in both CMJ and CMJA in NCAA Division I basketball players, with low coefficients of variation < 10% and ICC > 0.70 in both types of jumps. These findings align with previous research indicating that the commonly used neuromuscular performance tests, such as the CMJ and linear sprint tests, show high reliability in controlled conditions [9,32]. The strong absolute reliability of these tests suggests that they can be confidently used to monitor players’ performance over time with minimal concern for measurement errors.
In line with our findings, Duthie et al.’s [33] results showed that the 10 m linear sprint test is highly reliable with a low MDC, in male junior rugby players. In fact, their ICC ranges between 0.86 and 0.92, depending on the starting technique used. These ICC values are similar to the ones we found. They reported an MDC of 1%, a clearly lower value than ours, and that other researchers like Moir et al. [34] who found an MDC ranging from 1.9% to 2.6%, in physical education students. Based on these differences, it would be ideal to use dual beam timing gates systems, requiring the simultaneous breaking of two beams to register a valid time. Although it is a non-realistic procedure in most of the sports clubs around the world.
In addition, McMahon et al. [35] found a similar trend than us regarding linear sprinting test reliability. The longer the distance, the higher the reliability (higher ICC and lower CV). Our results show a much lower CV than theirs (10 m: 0.1 vs. 1.37%; 20 m: 0.1 vs. 0.96%). However, it is worth noting that their study sample was composed by a recreational sports practitioner, showing women a lower reliability (lower ICC and higher CV) than men. Based on these data, even though in basketball 5 m sprints are much more specific [36], reliability tends to be lower. Therefore, it is necessary to analyze the trade of about specificity and reliability, or as we did, to gather the data of both distances.
Conversely, the SL-CMJ demonstrated good absolute reliability, but higher MDC percentages, particularly for the left leg. This finding suggests that while the SL-CMJ provides valuable insights into unilateral neuromuscular performance and the asymmetry between limbs, it is less sensitive to detect small improvements in performance compared to bilateral jumps and linear sprint tests. This may be due to the increased variability inherent in single leg movements, which require greater postural stability and coordination [21,23]. Therefore, this test should not be used isolated, as a single measure of neuromuscular improvement.
Other authors have found high reliability in more innovative jumping and sprinting tests to assess neuromuscular performance. Shalom et al. [37] tried to replicate real time basketball movements on court by combining both horizontal and vertical movements, through penetration to the basket with a layup. However, due to the low sample size (n = 22) and the characteristics of the group (young players), we must be cautious to avoid incorrect generalizations [37]. Pehar et al. [38] also analyzed a different jumping test, finding a new running single leg jump as a valid and reliable tool. Similarly, Brini et al. [11] pointed out a new multidirectional repeated sprinting test as a valid and a reliable tool to analyze neuromuscular performance in basketball players, able to discriminate between professional and non-professional players.
The SL-CMJ, particularly the left-leg jump, has greater variability. Although it provides useful information on unilateral strength and asymmetry, its higher MDC values suggest that observed improvements may need to be larger to confidently attribute them to actual performance gains rather than measurement error.
The CMJ and SJ maintain high relative reliability, reinforcing their value as key assessments for evaluating lower limb power in basketball players. This could be useful, since professional players are normally assessed though these jump several times, therefore the learning curve is already achieved [36].
When analyzing absolute and relative reliability based on players’ specific playing position, all neuromuscular tests showed an excellent absolute and relative reliability, however subtle differences were revealed between Bigs and Guards. Bigs exhibited greater absolute reliability in SJ, CMJ, and SL-CMJ, while Guards only outperformed in CMJA. In terms of relative reliability, Bigs showed higher ICC values than Guards in SJ, CMJ, and CMJA and in 10 and 20 m sprinting tests, while Guards showed greater relative reliability in SL-CMJ for both legs and in the 5 m sprint tests. In scientific literature, several authors have analyzed validity and reliability of different jumping [5,7,9,37] and linear sprinting tests [11,39,40] for basketball players. However, the analysis based on the specific playing position has been usually approached from a performance-related differences perspective [12,13,41]. Therefore, from our knowledge, this is the first study that aims to address absolute and relative reliability of jumping and linear sprinting specifically for Bigs and Guards players.
In basketball, sprints are not only performed linearly but also occur with changes in direction (COD). One of the main limitations of this study is not being able to assess sprint performance through a COD test. Therefore, we are missing an important piece the neuromuscular performance in basketball. On the other hand, due to the high number of matches and the difficulty in adjusting training loads to replicate two different assessments days, it has not allowed establishing inter-day reliability. In addition, even though our sample is very interesting since it compromises players from different Spanish and German leagues, data regarding years of training experience could allow avoiding possible participant differences. However, we have ensured that the average age of basketball players is comparable across groups, minimizing potential biases related to age differences. In addition, including players from other top leagues (i.e., Pro A in France, Basketball Süper Ligi in Turkey, Lega Basket Serie A in Italy) would allow us to analyze more leagues and players from different countries with different playing styles. This would allow us to better generalize our results to different leagues.
Given the time constraints in professional basketball settings, strength and conditional professionals should consider the trade-off between test reliability and practicality. While the SL-CMJ provides unique insights into unilateral function and asymmetry, its lower sensitivity to change may limit its usefulness as a primary monitoring tool for tracking performance improvements. Therefore, we recommend strength and physical conditional coaches to choose two-legged jumps, SJ, and CMJA. As well as sprinting test, prioritizing 10 and 20 m. In brief, these jumping and sprinting tests are suitable assessment tools for basketball physical coaches to assess preseason neuromuscular performance due to their sensitivity to detect neuromuscular changes in professional basketball players based.
5. Conclusions
This study provides evidence for the high reliability of commonly used neuromuscular performance tests in professional basketball players. The 10 and 20 m sprint tests, along with the SJ and CMJA, demonstrated the highest absolute and relative reliability, making them ideal for tracking performance changes. While SL-CMJ tests offer valuable information on unilateral function, their higher MDC values suggest that substantial improvements are necessary to confidently attribute gains to training adaptations. Both Bigs and Guards showed excellent reliability across all tests. Bigs showed greater reliability in SJ, CMJ, and 10 and 20 m linear sprints, while Guards outperformed in the 5 m sprint. SL-CMJ showed mixed results, with Bigs having higher absolute reliability and Guards showing higher relative reliability. These differences highlight the influence of playing position on performance consistency, which should be considered in training and assessment. Therefore, these findings aid basketball physical coaches in the selection of the most suitable jumping and sprinting tests for neuromuscular performance monitoring based on players’ playing position, ensuring time-efficient and reliable assessments during preseason to enhance players’ performance.
Conceptualization, Á.d.P.-M. and O.G.-G.; methodology, Á.d.P.-M. and O.G.-G.; validation, O.G.-G. and V.S.-G.; formal analysis, V.S.-G. and O.G.-G.; investigation, Á.d.P.-M. and T.Á.-Y.; resources, Á.d.P.-M. and T.Á.-Y.; data curation, Á.d.P.-M.; writing—original draft preparation, Á.d.P.-M., T.Á.-Y. and O.G.-G.; writing—review and editing, Á.d.P.-M., T.Á.-Y., V.S.-G. and O.G.-G.; supervision, V.S.-G. and O.G.-G.; project administration, T.Á.-Y. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Education and Sports of the University of Vigo (protocol code 05-1421 and date of approval 14 December 2021).
Informed consent was obtained from all subjects involved in the study.
The data that support the findings of this study are available from the corresponding author upon reasonable request.
The authors declare no conflicts of interest.
Footnotes
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Intra-session relative and absolute reliability analysis of jumping and sprinting tests.
| ICC (95% IC) | CV (%) | SEM | SEM (%) | MDC | MDC (%) | Mean 1 (SD) | Mean 2 (SD) | ||
|---|---|---|---|---|---|---|---|---|---|
| SJ | 0.96 (0.77–0.98) | 1.5 | 1.049 | 2.63 | 2.907 | 7.29 | 40.55 (4.95) | 39.19 (5.06) | |
| CMJ | 0.93 (0.84–0.96) | 2.6 | 1.835 | 4.27 | 5.086 | 11.83 | 43.68 (5.36) | 42.30 (5.68) | |
| SL-CMJ | R | 0.97 (0.90–0.99) | 1.6 | 1.089 | 4.96 | 3.018 | 13.75 | 22.09 (4.8) | 21.79 (4.17) |
| L | 0.84 (0.44–0.96) | 2.5 | 1.738 | 7.92 | 4.817 | 20.82 | 23.41 (3.85) | 22.86 (2.67) | |
| CMJA | 0.97 (0.70–0.99) | 1.4 | 1.003 | 1.94 | 2.780 | 5.38 | 52.43 (6.97) | 50.76 (6.58) | |
| Linear | 5 m | 0.81 (0.70–0.89) | 0.1 | 0.044 | 3.85 | 0.121 | 10.43 | 1.15 (0.08) | 1.17 (0.08) |
| 10 m | 0.91 (0.86–95) | 0.1 | 0.044 | 2.31 | 0.121 | 6.36 | 1.90 (0.09) | 1.90 (0.09) | |
| 20 m | 0.92 (0.87–0.95) | 0.1 | 0.054 | 1.74 | 0.149 | 4.76 | 3.13 (0.13) | 3.13 (0.13) | |
ICC: intra-class correlation coefficient; 95% IC: 95% confidence intervals; CV: coefficient of variation; SEM: standard error of measurement; MDC: minimal detectable change; SD: standard deviation; 1: Assessment moment 1; 2: Assessment moment 2; SL-CMJ: single leg countermovement jump; L: left leg; R: right leg; SJ: squat jump composite score; CMJ: countermovement jump; Abalakov: free jump 20Y-M; SEM for SL-CMJ, SJ, CMJ and Abalakov in centimeters, for Lineal sprint in seconds; MDC for SL-CMJ, SJ, CMJ, and Abalakov in centimeters, for Lineal Sprint in seconds.
References
1. De Pedro-Múñez, Á.; Álvarez-Yates, T.; Serrano-Gómez, V.; García-García, O. Intraseason changes in vertical jumps of male professional basketball players. Int. J. Environ. Res. Public Health; 2023; 20, 5030.
2. Narazaki, K.; Berg, K.; Stergiou, N.; Chen, B. Physiological demands of competitive basketball. Scand. J. Med. Sci. Sports; 2009; 19, pp. 425-432. [DOI: https://dx.doi.org/10.1111/j.1600-0838.2008.00789.x]
3. García-Rubio, J.; Carreras, D.; Feu, S.; Antunez, A.; Ibáñez, S.J. Citius, altius, fortius; is it enough to achieve success in basketball?. Int. J. Env. Res. Public Health; 2020; 17, 7355. [DOI: https://dx.doi.org/10.3390/ijerph17207355] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33050131]
4. Cui, Y.; Liu, F.; Bao, D.; Liu, H.; Zhang, S.; Gómez, M.Á. Key anthropometric and physical determinants for different playing positions during National Basketball Association draft combine test. Front. Psychol.; 2019; 10, 2359. [DOI: https://dx.doi.org/10.3389/fpsyg.2019.02359]
5. Edwards, T.; Spiteri, T.; Piggott, B.; Bonhotal, J.; Haff, G.G.; Joyce, C. Reliability and Sensitivity of Neuromuscular and Perceptual Fatigue Measures in Collegiate Men’s Basketball. J. Strength Cond. Res.; 2018; 32, e57.
6. Ferioli, D. Physiological Determinants and Physical Match Activities in Basketball. Ph.D. Thesis; Università degli studi Milano: Milan, Italy, 2018.
7. Heishman, A.D.; Daub, B.D.; Miller, R.M.; Freitas, E.D.; Frantz, B.A.; Bemben, M.G. Countermovement jump reliability performed with and without an arm swing in NCAA division 1 intercollegiate basketball players. J. Strength Cond. Res.; 2020; 34, pp. 546-558.
8. Ziv, G.; Lidor, R. Vertical jump in female and male basketball players—A review of observational and experimental studies. J. Sci. Med. Sport; 2010; 13, pp. 332-339. [DOI: https://dx.doi.org/10.1016/j.jsams.2009.02.009]
9. Rodríguez-Rosell, D.; Mora-Custodio, R.; Franco-Márquez, F.; Yáñez-García, J.M.; González-Badillo, J.J. Traditional vs. sport-specific vertical jump tests: Reliability, validity, and relationship with the legs strength and sprint performance in adult and teen soccer and basketball players. J. Strength Cond. Res.; 2017; 31, pp. 196-206.
10. Hoffman, J.R.; Tenenbaum, G.; Maresh, C.M.; Kraemer, W.J. Relationship between athletic performance tests and playing time in elite college basketball players. J. Strength Cond Res.; 1996; 10, pp. 67-71.
11. Brini, S.; Boullosa, D.; Calleja-González, J.; Delextrat, A. Construct validity and reliability of a new basketball multidirectional reactive repeated sprint test. Int. J. Environ. Res. Public Health; 2021; 18, 10695. [DOI: https://dx.doi.org/10.3390/ijerph182010695]
12. Gathercole, R.J.; Sporer, B.C.; Stellingwerff, T.; Sleivert, G.G. Comparison of the capacity of different jump and sprint field tests to detect neuromuscular fatigue. J. Strength Cond. Res.; 2015; 29, pp. 2522-2531. [DOI: https://dx.doi.org/10.1519/JSC.0000000000000912]
13. Sonesson, S.; Lindblom, H.; Hägglund, M. Performance on sprint, agility and jump tests have moderate to strong correlations in youth football players but performance tests are weakly correlated to neuromuscular control tests. Knee Surg. Sports Traumatol. Arthrosc.; 2021; 29, pp. 1659-1669. [DOI: https://dx.doi.org/10.1007/s00167-020-06302-z]
14. Puente, C.; Abián-Vicén, J.; Areces, F.; López, R.; Del Coso, J. Physical and physiological demands of experienced male basketball players during a competitive game. J. Strength Cond. Res.; 2017; 31, pp. 956-962. [DOI: https://dx.doi.org/10.1519/JSC.0000000000001577]
15. Abdelkrim, N.B.; El Fazaa, S.; El Ati, J. Time–motion analysis and physiological data of elite under-19-year-old basketball players during competition. Br. J. Sport Med.; 2007; 41, pp. 69-75. [DOI: https://dx.doi.org/10.1136/bjsm.2006.032318]
16. do Carmo, E.C.; De Souza, E.O.; Roschel, H.; Kobal, R.; Ramos, H.; Gil, S.; Tricoli, V. Self-selected rest interval improves vertical jump postactivation potentiation. J. Strength Cond. Res.; 2021; 35, pp. 91-96. [DOI: https://dx.doi.org/10.1519/JSC.0000000000002519] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29481453]
17. Sampaio, J.; McGarry, T.; Calleja-González, J.; Jiménez Sáiz, S.; Schelling i del Alcázar, X.; Balciunas, M. Exploring game performance in the National Basketball Association using player tracking data. PLoS ONE; 2015; 10, e0132894. [DOI: https://dx.doi.org/10.1371/journal.pone.0132894] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26171606]
18. De Blas, X.; Padullés, J.M.; López del Amo, J.L.; Guerra-Balic, M. Creation and Validation of Chronojump-Boscosystem: A Free Tool to Measure Vertical Jumps. RICYDE Rev. Int. Cienc. Deporte; 2012; 30, pp. 334-356. [DOI: https://dx.doi.org/10.5232/ricyde2012.03004]
19. Colino, E.; Garcia-Unanue, J.; Sanchez-Sanchez, J.; Calvo-Monera, J.; Leon, M.; Carvalho, M.J.; Gallardo, L.; Felipe, J.L.; Navandar, A. Validity and reliability of a commercially available indoor tracking system to assess distance and time in court-based sports. Front. Psychol.; 2019 10, 2076. [DOI: https://dx.doi.org/10.3389/fpsyg.2019.02076]
20. Toumi, H.; Best, T.M.; Martin, A.; Poumarat, G. Muscle plasticity after weight and combined (weight+ jump) training. Med. Sci. Sports Exerc.; 2004; 36, pp. 1580-1588. [DOI: https://dx.doi.org/10.1249/01.MSS.0000139896.73157.21]
21. Mitchell, L.J.; Argus, C.K.; Taylor, K.L.; Sheppard, J.M.; Chapman, D.W. The effect of initial knee angle on concentric-only squat jump performance. Res. Q. Exerc. Sport; 2017; 88, pp. 184-192. [DOI: https://dx.doi.org/10.1080/02701367.2017.1293777]
22. Argus, C.K.; Chapman, D.W. The effect of initial knee angle on the reliability of variables derived from a squat jump. Med. Sport; 2014; 18, pp. 125-130. [DOI: https://dx.doi.org/10.5604/17342260.1127307]
23. Sheppard, J.M.; Cormack, S.; Taylor, K.L.; McGuigan, M.R.; Newton, R.U. Assessing the force-velocity characteristics of the leg extensors in well-trained athletes: The incremental load power profile. J. Strength Cond. Res.; 2008; 22, pp. 1320-1326. [DOI: https://dx.doi.org/10.1519/JSC.0b013e31816d671b]
24. Fu, H.; Li, Z.; Zhou, X.; Wang, J.; Chen, Z.; Sun, G.; Zeng, H.; Wan, L.; Hu, Y.; Wang, F. et al. The profiles of single leg countermovement jump kinetics and sprinting in female soccer athletes. Heliyon; 2023; 9, e19159. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37664742]
25. McGraw, K.O.; Wong, S.P. Forming inferences about some intraclass correlation coefficients. Psychol. Methods; 1996; 1, pp. 30-40. [DOI: https://dx.doi.org/10.1037/1082-989X.1.1.30]
26. Koo, T.K.; Li, M.Y. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J. Chiropr. Med.; 2016; 15, pp. 155-163. [DOI: https://dx.doi.org/10.1016/j.jcm.2016.02.012] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27330520]
27. Hopkins, W.G. Measures of reliability in sports medicine and science. Sports Med.; 2000; 30, pp. 1-15.
28. Lohr, C.; Braumann, K.M.; Reer, R.; Schroeder, J.; Schmidt, T. Reliability of tensiomyography and myotonometry in detecting mechanical and contractile characteristics of the lumbar erector spinae in healthy volunteers. Eur. J. Appl. Physiol.; 2018; 118, pp. 1349-1359.
29. Weir, J.P. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J. Strength Cond. Res.; 2005; 19, pp. 231-240.
30. Sekulic, D.; Spasic, M.; Mirkov, D.; Cavar, M.; Sattler, T. Gender-specific influences of balance, speed, and power on agility performance. J. Strength Cond. Res.; 2013; 27, pp. 802-811.
31. Mujika, I. Tapering and Peaking for Optimal Performance; Human Kinetics: Champaign, IL, USA, 2009.
32. Padulo, J.; Bragazzi, N.L.; Nikolaidis, P.T.; Dello Iacono, A.; Attene, G.; Pizzolato, F.; Pupo, D.J.; Zagatto, A.M.; Oggianu, M.; Migliaccio, G.M. Repeated sprint ability in young basketball players: Multi-direction vs. one-change of direction (Part 1). Front. Physiol.; 2016; 22, 133.
33. Duthie, G.M.; Pyne, D.B.; Ross, A.A.; Livingstone, S.G.; Hooper, S.L. The reliability of ten-meter sprint time using different starting techniques. J. Strength Cond. Res.; 2006; 20, pp. 246-251.
34. Moir, G.; Button, C.; Glaister, M.; Stone, M.H. Influence of familiarization on the reliability of vertical jump and acceleration sprinting performance in physically active men. J. Strength Cond. Res.; 2004; 18, pp. 276-280. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15142028]
35. McMahon, J.J.; Kyriakidou, I.; Murphy, S.; Rej, S.J.; Young, A.L.; Comfort, P. Reliability of five-, ten-and twenty-metre sprint times in both sexes assessed using single-photocell electronic timing gates. Prof. Strength Cond.; 2017; 44, pp. 17-21.
36. Morrison, M.; Martin, D.T.; Talpey, S.; Scanlan, A.T.; Delaney, J.; Halson, S.L.; Weakley, J. A systematic review on fitness testing in adult male basketball players: Tests adopted, characteristics reported and recommendations for practice. Sports Med.; 2022; 52, pp. 1491-1532. [DOI: https://dx.doi.org/10.1007/s40279-021-01626-3]
37. Shalom, A.; Gottlieb, R.; Alcaraz, P.E.; Calleja-Gonzalez, J. A Unique Specific Jumping Test for Measuring Explosive Power in Basketball Players: Validity and Reliability. Appl. Sci.; 2023; 13, 7567. [DOI: https://dx.doi.org/10.3390/app13137567]
38. Pehar, M.; Sekulic, D.; Sisic, N.; Spasic, M.; Uljevic, O.; Krolo, A.; Milanovic, Z.; Sattler, T. Evaluation of different jumping tests in defining position-specific and performance-level differences in high level basketball players. Biol. Sport; 2017; 34, pp. 263-272. [DOI: https://dx.doi.org/10.5114/biolsport.2017.67122]
39. Baena-Raya, A.; Díez-Fernández, D.M.; López-Sagarra, A.; Martínez-Rubio, C.; Soriano-Maldonado, A.; Rodríguez-Pérez, M.A. Novel Curvilinear Sprint Test in Basketball: Reliability and Comparison With Linear Sprint. J. Strength Cond. Res.; 2023; 37, pp. e535-e540.
40. Keiner, M.; Kadlubowski, B.; Wirth, K.; Klusemann, M. The Influence of Linearsprint and Jump Performance on Change-of-Direction Performance in Male and Female State-Representative Youth Basketball Players. Int. J. Sports Exerc. Med.; 2021; 7, 186.
41. Adıgüzel, N.S. Strength, jump heights and physical characteristics of young male basketball players by their positions. J. Educ. Train. Stud.; 2019; 7, 17.
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