The effects of maturity matched and un-matched opposition on physical performance and spatial exploration behavior during youth basketball matches

Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review

BACKGROUND

Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.

OBJECTIVES

The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).

METHODS

PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.

RESULTS

Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s-2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s-1) and acceleration/deceleration zones (> 2.0 m·s-2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.

CONCLUSIONS

Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.

Selection-Dependent Differences in Youth Elite Basketball Players' Relative Age, Maturation-Related Characteristics, and Motor Performance

Purpose: The aim of the present study was to investigate the influence of players' relative age, maturation-related characteristics, and motor performance tests on two different stages of talent selection (regional and national level) in youth elite basketball. Methods: Relative age, maturation-related variables (height, weight, maturity offset, maturity timing) and motor performance (Countermovement jump, Standing long jump, Modified agility T-test, Linear sprint 20 m) of N = 68 male youth basketball players (Mage = 14.39 ± 0.28 years) were assessed during the initial selection tournament for the German U15 national team. Pre-selection biases regarding relative age and maturity timing on the regional level were investigated utilizing one-sample t-tests. Differences in relative age, maturation-related characteristics and motor performance between players selected (n = 27) and non-selected (n = 41) for the youth national team were examined via independent samples' t-tests and logistic regression analyses. Results: Strong pre-selection biases toward early-born and early-maturing players were confirmed on the regional level. Significant advantages in height and weight and higher values in maturity offset and maturity timing were found for selected players. Among the motor variables, only Countermovement jump performance was significantly better in selected players. When controlling for relative age and biological maturation regression models including motor performance variables did not significantly discriminate players' selection status. Conclusion: Coaches working in national, but also preceding selection stages (regional and club level) should raise their awareness to relative age and biological maturation when evaluating players' potential and current (motor) performance.

Exploring the existence, strength, and independence of relative age and maturation selection biases: a case study in Gaelic football talent development programmes

BACKGROUND

Biological maturity and relative age player selection biases are well documented in youth sports. However, there has been limited examination of the relationship between these biases.

AIM

This study investigated the presence, strength, and independence of relative age and biological maturity selection biases in Gaelic football.

SUBJECTS AND METHODS

A total of 247 male players from U14 to U16, from two talent academies were assessed for relative age (decimal age (DA)) and biological maturity (discrepancy between biological and chronological age (BA-CA)).

RESULTS

Relative age effects (RAE) were observed in the U14 (DA = 0.62, d = 0.40) and U15 squads (DA = 0.57. d = 0.26) only. A bias towards advanced maturity status was present at U14 (BA-CA = 0.60, d = 0.83), U15 (BA-CA = 0.78, d = 0.89), and U16 (BA-CA, d = 1.01). There was a trivial (U14, r(83) = -0.210; U15, r(88) = 0.060) and low (U16, r(76) = 0.352) correlation between relative age and maturity status.

CONCLUSION

Substantial maturity selection biases and, to a lesser degree, relative age biases are evident in youth Gaelic football. Critically, these biases are independent constructs. Coaches and policy makers should be educated on the distinct influences of relative age and maturation, and on strategies to address these biases.

The Influence of Somatic Maturity on Anthropometrics and Body Composition in Youth Soccer Players

The primary aim of this investigation was to compare players' anthropometric (AP) and body composition (BC) characteristics between distinct maturity bands (pre-PHV, circa-PHV, post-PHV) in youth elite soccer. This study considered 320 male soccer players (mean age 13.8 y). Participants were from U14 (n = 157) and U15 (n = 163) age categories. The Khamis-Roche method was applied to calculate the percentage of predicted adult height (PAH) at the time of assessment based on which the players were further divided into maturity bands (pre-PHV ≤ 87%, circa-PHV = 88-95%, post-PHV > 95%). The findings indicated that most of the players were in the circa-PHV stage at the time of investigation. Measurements included height and weight. The estimates of BC parameters were derived using bioelectrical impedance (BIA) analysis. These various AP and BC attributes displayed significant differences among the maturity bands (F = 139.344-7.925; p < 0.001; large effect sizes) except in body fat mass (BFM) (F = 2.998; p = 0.051; small effect size). The current somatic maturity stage of the athletes should be considered when evaluating BC results, otherwise there is a risk of misinterpretation.

Integrating physical and tactical factors in football using positional data: a systematic review

Background

Positional data have been used to capture physical and tactical factors in football, however current research is now looking to apply spatiotemporal parameters from an integrative perspective. Thus, the aim of this article was to systematically review the published articles that integrate physical and tactical variables in football using positional data.

Methods and Materials

Following the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to August 2021. The methodological quality of the studies was evaluated using the modified Downs and Black Quality Index (observational and cross-sectional studies) and the Physiotherapy Evidence Database (PEDro) scale (intervention studies).

Results

The literature search returned 982 articles (WoS = 495; PubMed = 232 and SportDiscus = 255). After screening, 26 full-text articles met the inclusion criteria and data extraction was conducted. All studies considered the integration of physical and tactical variables in football using positional data (n = 26). Other dimensions were also reported, such as psychophysiological and technical factors, however the results of these approaches were not the focus of the analysis (n = 5). Quasi-experimental approaches considered training sets (n = 20) and match contexts (n = 6). One study analysed both training and play insights. Small sided-games (SSG) were the most common training task formats in the reviewed studies, with only three articles addressing medium-sided (MSG) (n = 1) and large-sided games (LSG) (n = 2), respectively.

Conclusions

Among the current systematic review, the physical data can be integrated by player's movement speed. Positional datasets can be computed by spatial movement, complex indexes, playing areas, intra-team and inter-team dyads. Futures researches should consider applying positional data in women's football environments and explore the representativeness of the MSG and LSG.

From Junior to Elite in Soccer: Exploring the Relative Age Effect and Talent Selection in Spanish Youth National Teams

The implications of relative age grouping in sport are known as the Relative Age Effect (RAE). This study has the twofold purpose of analyzing RAE in Spanish youth national soccer teams and examining the prediction value of being selected for national youth teams to be a professional. The sample was composed of 548 players divided into five groups. A descriptive analysis of distribution and participation, frequencies, mean and standard deviation, crosstabs, Sankey charts, coefficient correlation and Cohen's effect size criteria and two regression analyses were performed. Results established that the RAE is present in U'17 to U'21 Spanish youth national teams. Talent detection and selection programs are more reliable the closer they are to adulthood, reaching a success rate of almost 100% at the U'21 stage. The selection of players for such programs should be delayed as much as possible, thus, preventing younger players from dropping out and those selected from thinking they have already reached their goal. To this end, they should focus on long-term improvement, not short-term performance. In addition, factors such as the RAE or the maturity level of the athletes should be monitored.

Training and match demands differ between the regular season and finals in semi-professional basketball

Basketball competitions often include a scheduled regular season followed by knock-out finals. Understanding training and match demands through the season can help optimize performance and reduce injury risk. This study investigated whether training and/or match demands differed between the regular season and finals, and whether these differences were dependent on player role. Average session intensity and volume and durations of relative exercise intensities (inactive, light, moderate-vigorous, maximal, supramaximal) were quantified during training sessions and matches using accelerometry in two semi-professional basketball teams (n = 23; 10 women, 13 men). Training and match demands were compared between the regular season (training: 445 observations; matches: 387 observations) and finals (training: 113 observations, matches: 75 observations) with consideration of player role (starters, in-rotation bench, out-rotation bench). During finals matches, starters received 4.4 min more playing time (p = 0.03), performed 14% more absolute maximal activity (p < 0.01) and had 8% less relative inactive time (p = 0.02) when compared to the regular season. Out-rotation bench players received 2.1 min less playing time (p < 0.01), performed 33% less absolute maximal activity (p = 0.01) and 57% less absolute supramaximal activity (p < 0.01) in finals when compared to the regular season. During finals training sessions, average training intensity was 5% higher (p = 0.02), absolute moderate-vigorous activity was 3% higher (p = 0.04), relative maximal activity was 12% higher (p < 0.01), and relative inactive time was 5% lower (p = 0.03) when compared to the regular season. These findings suggest starters need to be physically prepared for greater match demands during finals, while out-rotation bench players should supplement their training during finals with extra supramaximal activity to maintain their conditioning levels for matches.

Effects of Chronological Age, Relative Age, and Maturation Status on Accumulated Training Load and Perceived Exertion in Young Sub-Elite Football Players

The aims of this study were 1) to analyze the influence of chronological age, relative age, and biological maturation on accumulated training load and perceived exertion in young sub-elite football players and 2) to understand the interaction effects amongst age grouping, maturation status, and birth quartiles on accumulated training load and perceived exertion in this target population. A 6-week period (18 training sessions and 324 observation cases) concerning 60 young male sub-elite football players grouped into relative age (Q1 to Q4), age group (U15, U17, and U19), and maturation status (Pre-peak height velocity (PHV), Mid-PHV, and Post-PHV) was established. External training load data were collected using 18 Hz global positioning system technology (GPS), heart-rate measures by a 1 Hz short-range telemetry system, and perceived exertion with total quality recovery (TQR) and rating of perceived exertion (RPE). U17 players and U15 players were 2.35 (95% CI: 1.25–4.51) and 1.60 (95% CI: 0.19–4.33) times more likely to pertain to Q1 and Q3, respectively. A negative magnitude for odds ratio was found in all four quartile comparisons within maturation status (95% CI: 6.72–0.64), except for Mid-PHV on Q2 (95% CI: 0.19–4.33). Between- and within-subject analysis reported significant differences in all variables on age group comparison measures (F = 0.439 to 26.636, p = 0.000 to 0.019, η2 = 0.003–0.037), except for dynamic stress load (DSL). Between-subject analysis on maturity status comparison demonstrated significant differences for all training load measures (F = 6.593 to 14.424, p = 0.000 to 0.037, η2 = 0.020–0.092). Interaction effects were found for age group x maturity band x relative age (Λ Pillai’s = 0.391, Λ Wilk’s = 0.609, F = 11.385, p = 0.000, η2 = 0.391) and maturity band x relative age (Λ Pillai’s = 0.252, Λ Wilk’s = 0.769, F = 0.955, p = 0.004, η2 = 0.112). Current research has confirmed the effects of chronological age, relative age, and biological maturation on accumulated training load. Perceived exertion does not seem to show any differences concerning age group or maturity status. Evidence should be helpful for professionals to optimize the training process and young football players’ performance.

A Glimpse of the Sports Nutrition Awareness in Spanish Basketball Players

Basketball is a team sport, with many fans and practitioners worldwide from all ages and levels. In all cases, players accumulate high levels of fatigue, and there is also limited time to recover between games or practices. In particular, nutrition plays a key role in optimizing performance and recovery. However, it is typical to observe erroneous nutritional behaviors among basketball players. It has been theorized that these behaviors are influenced by habits acquired based on the individual’s knowledge. Therefore, the main aim of this study was to conduct a descriptive research of the sports nutrition knowledge and practices in a sample of Spanish basketball players, from athletes under 18 years old (n = 69) to nonprofessional (n = 14) and professional adult players (n = 21). The sample was comprised of 49 men and 55 women. This was a transversal, cross-sectional, observational and descriptive study. All participants (n = 104) completed an anonymous online survey in order to analyze their sports nutrition knowledge and practices. In view of the obtained results, we can conclude that the knowledge of sport-specific nutrition in players under 18 years old, as well as non-professional and professional adult basketball players, is insufficient through all the categories and levels. The lack of professional support and time management difficulties were identified as some of the main barriers.