Intensity Thresholds for External Workload Demands in Basketball: Is Individualization Based on Playing Positions Necessary?

Currently, basketball teams use inertial devices for monitoring external and internal workload demands during training and competitions. However, the intensity thresholds preset by device manufacturers are generic and not adapted for specific sports (e.g., basketball) and players' positions (e.g., guards, forwards, and centers). Using universal intensity thresholds may lead to failure in accurately capturing the true external load faced by players in different positions. Therefore, the present study aimed to identify external load demands based on playing positions and establish different intensity thresholds based on match demands in order to have specific reference values for teams belonging to the highest competitive level of Spanish basketball. Professional male players (n = 68) from the Spanish ACB league were monitored during preseason official games. Three specific positions were used to group the players: guards, forwards, and centers. Speed, accelerations, decelerations, impacts/min, and player load/min were collected via inertial devices. Two-step clustering and k-means clustering categorized load metrics into intensity zones for guards, forwards, and centers. Guards covered more distance at high speeds (12.72-17.50 km/h) than forwards and centers (p < 0.001). Centers experienced the most impacts/min (p < 0.001). Guards exhibited greater accelerations/decelerations, albeit mostly low magnitude (p < 0.001). K-means clustering allowed the setting of five zones revealing additional thresholds. All positions showed differences in threshold values (p < 0.001). The findings provide insights into potential disparities in the external load during competition and help establish position-specific intensity thresholds for optimal monitoring in basketball. These data are highly applicable to the design of training tasks at the highest competitive level.

Concurrent Validity and Reliability of Devices to Measure Jump Height in Men's Handball Players

Although there is a wide range of validated devices to measure vertical jump height, the degree of interchangeability among them is currently unknown.

AIMS

The purpose of this study was to examine the concurrent validity and reliability of multiple devices to measure jump height in men's handball players.

METHODS

Sixteen players (age = 24.0 ± 3.7 years old) performed three types of jumps (n= 144-squat jump (SJ), countermovement jump (CMJ) and Abalakov jump (ABK)) on a contact platform (CHRONOJUMP^®) while simultaneously being measured with two inertial devices (WIMU^® and VERT^®) and recorded with a high-speed camera. Vertical jump height was analyzed according to each type of jump.

RESULTS

The t-test showed statistically significant differences (p = 0.001) between the contact platform (reference standard) and the rest of the tools that tended to overestimate jump height in all jumps. SJ and CMJ proved to be the jump tests with the most stable reliability values in all devices (ICC: 0.92-0.98), except in the comparison with VERT^®.

CONCLUSIONS

Although all the analyzed devices proved to be valid and reliable in previous studies, they are not interchangeable. Therefore, it is suggested to always use the same type of device to evaluate vertical height jump.

Exploring Physical Fitness Profile of Male and Female Semiprofessional Basketball Players through Principal Component Analysis-A Case Study

Basketball is a sport in continuous evolution, being one of these key aspects of the players' physical fitness that has an impact on the game. Therefore, this study aimed to characterize and identify the physical fitness level and profiles of basketball players according to sex. Total of 26 semi-professional basketball players were assessed (13 male, 13 female) through inertial devices in different previously validated fitness tests. T-test for independent samples and principal component analysis were used to analyze sex-related differences and to identify physical fitness profiles. The results showed differences according to sex in all physical fitness indexes (p < 0.01; d > 1.04) with higher values in males, except in accelerometer load during small-sided games (p = 0.17; d < 0.20). Four principal components were identified in male and female basketball players, being two common ([PC1] aerobic capacity and in-game physical conditioning, [PC4 male, PC3 female] unipodal jump performance) and two different profiles (male: [PC2] bipodal jump capacity and acceleration, [PC3] curvilinear displacement; female: [PC2] bipodal jump capacity and curvilinear displacement, [PC4] deceleration). In conclusion, training design must be different and individualized according to different variables, including physical fitness profiles between them. For practical applications, these results will allow knowing the advantages and weaknesses of each athlete to adapt training tasks and game systems based on the skills and capabilities of the players in basketball.

Multi-Location External Workload Profile in Women's Basketball Players. A Case Study at the Semiprofessional-Level

The external workload measured in one anatomical location does not determine the total load supported by the human body. Therefore, the purpose of the present study was to characterize the multi-location external workload through PlayerLoad_RT of 13 semi-professional women’s basketball players, as well as to analyze differences among anatomical locations (inter-scapulae line, lumbar region, 2× knee, 2× ankle) and laterality (left vs. right) during five tests that represent the most common movements in basketball—(a) linear locomotion, 30-15 IFT; (b) acceleration and deceleration, 16.25-m RSA (c) curvilinear locomotion, 6.75-m arc (d) jump, Abalakov test (e) small-sided game, 10’ 3 vs. 3 10 × 15-m. Statistical analysis was composed of a repeated-measures t-test and eta partial squared effect size. Regarding laterality, differences were found only in curvilinear locomotion, with a higher workload in the outer leg (p < 0.01; η_p² = 0.33–0.63). In the vertical profile, differences among anatomical locations were found in all tests (p < 0.01; η_p² = 0.56–0.98). The nearer location to ground contact showed higher values except between the scapulae and lumbar region during jumps (p = 0.83; η_p² = 0.00). In conclusion, the multi-location assessment of external workload through a previously validated test battery will make it possible to understand the individual effect of external workload in each anatomical location that depends on the type of locomotion. These results should be considered when designing specific strategies for training and injury prevention.

Assessment of the Multi-Location External Workload Profile in the Most Common Movements in Basketball

The present study analyzed the multi-location external workload profile in basketball players using a previously validated test battery and compared the demands among anatomical locations. A basketball team comprising 13 semi-professional male players was evaluated in five tests (abilities/skills/tests): (a) aerobic, linear movement, 30-15 IFT; (b) lactic anaerobic, acceleration and deceleration, 16.25 m RSA (c) alactic anaerobic, curvilinear movement, 6.75 m arc (d) elastic, jump, Abalakov test (e) physical-conditioning, small-sided game, 10' 3 vs.3 10 × 15 m. PlayerLoad_RT was evaluated at six anatomical locations simultaneously (interscapular line, lumbar region, knees and ankles) by six WIMU PRO^TM inertial devices attached to the player using an ad hoc integral suit. Statistical analysis was composed of an ANOVA of repeated measures and partial eta squared effect sizes. Significant differences among anatomical locations were found in all tests with higher values in the location nearer to ground contact (p < 0.01). However, differences between lower limb locations were only found in curvilinear movements, with a higher workload in the outside leg (p < 0.01). Additionally, high between-subject variability was found in team players, especially at lower limb locations. In conclusion, multi-location evaluation in sports movements will make it possible to establish an individual external workload profile and design specific strategies for training and injury prevention programs.

Strength and Speed Profiles Based on Age and Sex Differences in Young Basketball Players

Team sports are in continuous evolution, and physical performance is acquiring greater importance in the game. The assessment of physical fitness is the most reliable method for knowing if the athlete’s physical fitness is appropriate. Therefore, the objectives of this research were to identify profiles of physical-physiological demands with different specific tests of physical fitness related to the maximum strength of the lower body and speed. Moreover, some differences based on the sex and age of the players were identified. One hundred and forty-nine basketball players were analyzed (men n = 103 vs. women n = 46, weight: 74.74 ± 11.65 kg vs. 56.89 ± 3.71 kg, height: 184.66 ± 11.67 vs. 164 ± 4 and BMI: 21.7 ± 0.83 vs. 21.6 ± 0.90). The players performed an Abalakov test, a multi-jump test, and a repeat sprint ability test. Each player was equipped with a WIMU PRO device, and photoelectric cells were used. A MANOVA was performed to discover the differences between ages, and a t-test was used regarding sex. The results showed significant differences based on age and sex in variables related to time and Player Load/min (p < 0.001). The variables related to steps (contact, step, flight) also showed significant differences as a function of age (p < 0.001) and sex (p < 0.05). The multi-jump test showed differences based on age (p < 0.05 except in between jumps), but not on sex. These results confirm the importance of working together on lower body strength and speed skills. In addition, the planning of the work on these abilities must be individualized and according to the characteristics of the athlete.

Match and Training High Intensity Activity-Demands Profile during a Competitive Mesocycle in Youth Elite Soccer Players

The monitoring of the high intensity activity-demands profile during official matches (OMs) and training sessions (TSs) provides a deeper understanding of the relationship between training and competition loads as well as players’ fitness characteristics. The aims of this study were to: 1) describe the training and match high intensity activity-demands profile in U-19 soccer players; 2) compare the profile depending on the type of session (OM or TS) throughout match-weeks; and 3) differentiate between profiles depending on the match location (home or away). Twenty-five U-19 Spanish soccer players were monitored during TSs and OMs for a one-month competitive period using a WIMU PRO^TM wearable inertial device. The variables of the study were: high speed running distance (HSRD), total sprints (SPs), maximum speed (MS) and player load (PL). OMs required higher demands than TSs in HSRD (460.99 ± 206.18 vs. 315.45 ± 180.12 m; p < 0.01; d = 0.75), SPs (10.86 ± 6.64 vs. 7.23 ± 4.82; p < 0.01; d = 0.69), MS (29.99 ± 2.54 vs. 28.50 ± 2.4 km/h; p < 0.01; d = 0.59) and PL (103.08 ± 24.15 vs. 83.18 ± 17.96 a.u.; p < 0.01; d = 0.94). The interaction between the type of session and mean week’s demands presented differences with medium effect size in MS (p < 0.01; ω_p² = 0.06) and small effect size in HSRD (p = 0.04; ω_p² = 0.03), and SP (p = 0.05; ω_p² = 0.03), but there were no differences in PL (p = 0.18; ω_p² = 0). Finally, no differences were found in the match location comparison (p > 0.33; d = 0.22–0.33). Therefore, the profiles presented could be useful for future scientific purposes and serve as valid information for coaches trying to optimize performance.

Influence of Contextual Variables in the Changes of Direction and Centripetal Force Generated during an Elite-Level Soccer Team Season

The study of the contextual variables that affect soccer performance is important to be able to reproduce the competition context during the training sessions. Therefore, the aim of the present study was to evaluate the effect of match outcome as related to goal difference (large win, >2 goals, LW; narrow win, 1–2 goals, NW; drawing, D; narrow loss, 1–2 goals, NL; or large loss, >2 goals, LL), match location (home, H; away, A; neutral, N), type of competition (international, INT; national, NAT; friendly, F), phase of the season (summer preseason, SPS; in-season 1, IS1; winter preseason, WPS; in-season 2), and the field surface (natural grass, NG; artificial turf, TF) on the change of direction (COD) and centripetal force (CentF) generated during official games. Thirty male elite-level soccer players (age: 26.57 ± 5.56 years) were assessed while using WIMU PRO^TM inertial devices (RealTrack Systems, Almeria, Spain) in 38 matches during the 2017–2018 season, selecting for analysis the number of COD at different intensities and the CentF, depending on the turn direction. Statistical analyses comprised a one-way ANOVA with the Bonferroni post-hoc and t-test for independent samples. The main results showed that the match outcome (ω_p² = 0.01–0.04; NW = D = NL > LL), match location (ω_p² = 0.01–0.06; A = N > H), type of competition (ω_p² = 0.01–0.02; INT > NAT > F), and period of the season (ω_p² = 0.01–0.02; SPS = IS1 = WPS > IS2) all exert some influence. No effect was found for the playing surface. Therefore, match outcome, match location, type of competition, and period of the season influence the demands of centripetal force and changes of direction. These aspects should be considered in the design of training sessions and microcycle workload planning during the season to improve competitive success.

Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer

There has recently been an increase in quantification and objective analysis of soccer performance due to improvements in technology using load indexes such as Player Load (PL) and Metabolic Power (MP). The objectives of this study were: (1) to describe the performance of PL and MP in competition according to the specific role, match-to- match variation, periods of play, game location and match status according to game periods, and (2) to analyze the relationship between both indexes. Twenty-one national-level soccer players were distributed in the following specific positional roles: external defenders (ED) (n = 4), central defenders (CD) (n = 4), midfielders (M) (n = 5), external midfielders (EM) (n = 4) and attackers (A) (n = 4). A total of 12 matches played by a Spanish Third Division team during the 2016/2017 season were analyzed. WIMU PROTM inertial devices (RealTrack System, Almeria, Spain) were used for recording the data. The main results were: (1) a performance reduction in both variables over the course of match time, (2) significant differences in both variables based on the specific position, (3) differences in physical demands during the season matches, (4) winning during a game period and the condition of being the visitor team provoked higher demands, and (5) a high correlation between both variables in soccer. In conclusion, different contextual variables influence the external load demands; both indexes are related so they could be used for external load quantification, and it is necessary to analyze physical demands of the competition for a specific and individualized load design in training sessions.

The Acceleration and Deceleration Profiles of U-18 Women's Basketball Players during Competitive Matches

The ability of a player to perform high-intensity actions can be linked to common requirements of team sports, and the ability to accelerate can be an important factor in successfully facing the opponent. The aim of this study was to determine the acceleration and deceleration profiles of U-18 women's basketball players during competitive matches. This study categorized accelerations and decelerations by playing position and quarter. Forty-eight U-18 female basketball players from the same Spanish league participated in this study. Each player was equipped with a WimuPro^TM inertial device. Accelerations/decelerations were recorded. The number of accelerations and decelerations, intensity category, and type were recorded. These variables varied between quarters (first quarter, second quarter, third quarter, and fourth quarter) and playing positions (Guard, Forward and Center). The shorter but more intense accelerations took place in the last quarter, due to the tight results of the matches. Besides, players in the Guard positions performed more accelerations and their intensity was greater than that of other positions. An acceleration profile was established for the quarters of a basketball game, and was shown to depend on the playing position, being different for Guards, Forwards and Centers in U-18 women's basketball players.

Comparative Analysis of Load Profile between Small-Sided Games and Official Matches in Youth Soccer Players

The purposes of the present study are: (a) to characterize the external (eTL) and internal load (iTL) of official matches and small-sided games (SSGs) in relation to their objective, (b) to compare demands between SSG, and (c) to analyze the SSG requirements in relation to official matches during a one-month competition period. Twenty under-18 national-level soccer players were recorded using WIMU^TM inertial devices (RealTrack Systems, Almeria, Spain) during four official matches and 12 training sessions where four SSGs with different objectives were performed: (SSG1) keeping the ball; (SSG2) keeping the ball and progressing; (SSG3) keeping the ball, progressing and ending in mini-goals; and (SSG4) keeping the ball, progressing and ending in an official goal with a goalkeeper. Statistical analysis included Kruskall-Wallis’ H and Mann-Whitney’s U with Cohen’s d effect size. The SSGs presented walking and jogging intensity movements (0.7–7 to 7–14 km/h), with a 5-to-8 %HIA (high intensity activity, >16 km/h), where low intensity accelerations, decelerations and impacts were predominant (1–2.5 m/s²; 5–7 G), and %HR_MAX (maximum heart rate percentage) was between 70–90%. Only SSG4 presented similar demands to competition, finding differences between SSGs (p < 0.05; d = 1.40 − 0.36). In conclusion, the objective of the SSGs directly influenced the demands on the players in training sessions. For this reason, it is important to monitor demands for designing specific training sessions.