Half Court Research Articles

Physiological and metabolic responses of Parabadminton athletes to field simulated effort.

Due to the increase in the number of Parabadminton (PBd) athletes and the lack of scientific knowledge of the sport, it is important to evaluate performance variables in different game stimuli. Thus, this study sought to examine the physiological and metabolic responses in a simulated effort protocol in PBd athletes. Forty-seven volunteers (WH1=7; WH2=9; SL3=8; SL4=9; SU5=6; SH6=8) performed a simulated effort protocol, consisting of 2 blocks of activities (1st change of direction + 1st simulated effort; 2nd change of direction + 2nd simulated effort). Peak and average oxygen consumption (VO<inf>2</inf>peak and VO<inf>2</inf>avg), peak, percentage, and average heart rate (HRmax, %HRmax, and HRavg), percentage of carbohydrates and lipids contributions (%CARB and %FAT), and average and total energy expenditure (EEavg and EEtotal) were evaluated. The data was compared between protocol stages, functional classes (FCs), and court size. It was adopted P<0.05. Differences were found between the stages of the protocol in VO<inf>2</inf>peak (P=0.0008), VO<inf>2</inf>avg (P=0.0004); HRmax (P<0.0001); %HRmax (P=0.0001), HRavg (P=0.0001), %CARB (P=0.0001), %FAT (P=0.0001), EEavg (P=0.0002), and EEtotal (P=0.008). Among FCs, SL4 athletes were superior to WH1 athletes for VO<inf>2</inf>peak (P=0.075), VO<inf>2</inf>avg (P=0.022), EEavg (P=0.011), and EEtotal (P=0.022). Athletes who completed protocol in the full court were greater than half court for VO<inf>2</inf>peak (P<0.001), VO<inf>2</inf>avg (P<0.001), %HRmax (P=0.032), HRavg (P=0.018), %CARB (P=0.022), %FAT (P=0.022), and EEavg (P=0.016). PBd athletes belonging to higher FCs (4, 5, and 6) and who cover greater distances on the court exhibit physiological and metabolic responses under greater influence of the type of disability.

Perbedaan Recovery Denyut Nadi Berdasarkan Jeda Waktu Makan Setelah Olahraga

The right time to eat for athletes is suggested to support achievement. However, research evidence on this matter still needs to be more extensive. This study aims to reveal evidence of differences in pulse after exercise by looking at the pause after eating. A one-shot case study experiment was conducted with 22 student samples divided into three groups. The first group of 7 people exercised immediately after eating (A), the second group of 8 people 1 hour after eating (B), and group 3 2 hours after eating (C). Pulse testing is carried out before exercising (basketball man to man half court) for 10 minutes, and then the pulse is measured after playing; further measurements are carried out every 3 minutes up to 4 times and 1 hour after stopping playing. The rest is done passively. The instruments used are tests and measurements of the pulse. Data analysis used is descriptive statistics and different tests using ANOVA. The results showed that, in this case, group A and Group C had the same pulse rate of 65 per minute, while Group B had an average of 77.5 per minute. Pulse after exercising consecutively 1130.29, 128, and 128.9 per minute. At the end of measuring the pulse after 1 hour of rest, it turned out that group C had the lowest pulse compared to groups A and B.&#x0D; Keywords: Recovery, Food before sport, pulse

Effects of Different Formations on The Running Performance of High-level Football Players

The match formation is the football player’s position arrangement on the field, the attacking and defending strength collocation and the duty division form. It is the match tactics important constituent. This study took the three most commonly used match formations (4-5-1, 4-4-2, 3-5-2) of the 2018 FIFA World Cup as independent variables and the running performance index as dependent variables, aiming to explore the influence of different match formations on the running performance of players in the team as a whole and at various positions. The research results showed that :1. Teams in 4-5-1 and 3-5-2 formations completed more sprints than teams in 4-4-2 formations. 2.3-5-2 Centre-backs needs to complete more intense runs and sprints, as well as more sprints, than a 4-4-2 Centre-backs. Wide positions in a 4-5-1 formation complete more intense runs and sprints, as well as more sprints, than those in a 4-4-2 formation. The Centre midfielders of 4-5-1 and 3-5-2 get more sprints than 4-4-2; Strikers in a 4-5-1 formation showed a more marked decrease in the intensity of running distance, sprints and sprints in the second half than those in a 4-4-2 formation. 3.The 3-5-2 Centre-backs have a significantly higher proportion of half-court activity than 4-5-1 and 4-4-2, and a significantly higher proportion of running time than 4-5-1; In 4-5-1 and 3-5-2 formations, the Centralmidfielders running time proportion in half court and attacking three zones is significantly higher than that in 4-4-2 formation. Therefore, when each team conducts daily training, it should take into account the different physical needs of different teams and players in different formations and positions.

Constructing a Gaming Model for Professional Tennis Players Using the C5.0 Algorithm

Professional tennis players have their own habits of tactics and play. However, players’ shortcomings can be corrected by constantly practicing professional techniques and by tactical analysis. Therefore, this study aimed to develop a two-stage, expert decision-making system for tennis matches. The first stage consisted in dividing the court area and defining the technical classification of the net. Tennis coaches were invited to assess tennis players’ skills on the competition court, dividing it into 48 areas on both sides of the court centerline and identifying the skills used by the players. In the second stage, a classification model was developed, and the score, hitting habits, and tennis skills of the players, Roger Federer and Rafael Nadal, over 10 matches, played from 2007 to 2019, were analyzed and classified using notational analysis and the C5.0 decision tree algorithm. The results show that the two players’ highest scored techniques were the forehand stroke in the backcourt and the backhand stroke in the half court. Thus, using this expert decision-making system, our data can provide other players with imaginary training objects from two of the top players in the world to be used during training and can allow the accumulation of experience for players through continuous simulation and training analysis.

Training load monitoring by position and task in professional men´s basketball

The aim of this study was to analyze the training load of the different tasks of a professional basketball team, based on the tasks and player positions. A total of 10 professional basketball players participated (Mage = 23.70; SD = 2.26) who carried out three different training tasks for four weeks: situation in the middle court (MC); situation in the middle court followed by a counterattack in the opposite court (FB); half court situation followed by two full court counterattack situations (CB). GPS Polar Team Pro© was used to monitoring the physical load. Internal physical load and external physical load variables were measured. One-way ANOVA was performed to explore the main differences between the different types of tasks and player positions on each of the dependent variables. The results show that FB tasks involve a higher internal load, while CB tasks involve a greater external load. Regarding the type of players, the exteriors reached higher values in the different variables analyzed. Therefore, it has been found that different training tasks imply different physical demands. Specifically, using training tasks that reproduce the dynamics of competition imply an increase in conditional load.

Basketball half court dimensions

Basketball half court dimensions

Basketball Half Court Dimensions

Basketball Half Court Dimensions

Measuring spatial allocative efficiency in basketball

Abstract Every shot in basketball has an opportunity cost; one player’s shot eliminates all potential opportunities from their teammates for that play. For this reason, player-shot efficiency should ultimately be considered relative to the lineup. This aspect of efficiency—the optimal way to allocate shots within a lineup—is the focus of our paper. Allocative efficiency should be considered in a spatial context since the distribution of shot attempts within a lineup is highly dependent on court location. We propose a new metric for spatial allocative efficiency by comparing a player’s field goal percentage (FG%) to their field goal attempt (FGA) rate in context of both their four teammates on the court and the spatial distribution of their shots. Leveraging publicly available data provided by the National Basketball Association (NBA), we estimate player FG% at every location in the offensive half court using a Bayesian hierarchical model. Then, by ordering a lineup’s estimated FG%s and pairing these rankings with the lineup’s empirical FGA rate rankings, we detect areas where the lineup exhibits inefficient shot allocation. Lastly, we analyze the impact that sub-optimal shot allocation has on a team’s overall offensive potential, demonstrating that inefficient shot allocation correlates with reduced scoring.

Futsal in Field with Variable Dimensions

This study aims to verify how the variation of game area in futsal game alters the requirement for each athlete. It is an empirical study with transversal characteristics. The sample consisted of six young, male, aged between 16 and 26 years, with experience playing futsal. The independent variable was the square footage of the field per athlete. The dependent variables were the number of contacts with the ball, passing, dribbling/feints, shooting and ball stolen and the number of errors passing, dribbling/feints and shooting and total goals scored. Games were conducted with two teams in 3x3 format players with open goals. The goal was valid if they shots were after the half court. The procedures follow the criterion of game space simulation in accordance with the minimum and maximum of futsal rules in sizes from 80m2, 45m2 and 25m2 for each player dimensions. Whereas the 6 subjects, the games had spaces of 30mx16m, 24mx11m and 17.5mx8.5m respectively, totaling 480m2, 265m2 and 148.7m2. A team made more passes than other by possession. Game actions should always be relativised to have summed and actual results of what happened. The biggest field was no decrease in the shots errors. The percentage of time played was higher in the biggest field, which is more interesting for the fans and the press.

Comparing the Most Demanding Passages of Official Matches and Training Drills in Elite Roller Hockey

The aim of this research was to identify and compare the most demanding passages (MDP) in elite roller hockey in competition and in different training situations. Data were collected using WIMU PRO™ sensors with inertial micro-technology and ultra-wide band positioning. Eight professional roller hockey players from the Spanish First Division League (Ok Liga) were analysed during the 2017-2018 season. The MDP were studied using a rolling average method in which maximal values were calculated for three different time windows (1’, 2’ and 5’) in official matches and in four different training drills commonly used in the weekly team-training schedule: practice match (TRAINING MATCH), 4 vs. 4 in half court and one transition (4vs4+1T), 4 vs. 4 in half court and two transitions (4vs4+2T) and 3 vs. 2 wave transition drill (3vs2). The variable used for the comparison was the distance covered in high speed skating (HSS: >18 km · h–1; m · min–1) and only the maximum value of each player, drill and time window were stored for the study. The results show that training drills could not reproduce the maximum conditional effort that occurs in an official match in any time window. Moreover, all the situations and games analysed had higher levels of effort as the time of the window studied decreased. The analysis of shorter time windows could be a topic for future research. In conclusion, the findings of this study pave the way for future research into the identification and comparison of the most demanding scenarios in elite roller hockey that may help coaches to design training situations.

Physical and physiological demands of basketball small-sided games: the influence of defensive and time pressures.

Different small-sided games (SSG) can be used by coaches to induce specific demands on athletes during team sports training. In basketball, defensive and time pressures are common stressors experienced by players during official matches. However, no studies have investigated the effect of changing these variables in SSG during training. We compared the physical and physiological demands of three basketball SSG performed in a half court with two hoops: 3vs3 with man-to-man defence in the half playing area, 3vs3 with man-to-man defence in the full playing area, and 3vs3 with a reduced shot-clock (3vs3HALF, 3vs3FULL, 3vs3RT, respectively). Twelve male U-17 basketball athletes formed four balanced teams. Each team played the three SSG against each other in a random order, totalling 18 SSG. During the SSG, the players wore triaxial accelerometers and heart rate monitors. SSG were filmed to record the players’ motor actions. The results showed that 3vs3FULL (p=0.004, d=0.42, small-to-moderate effect) and 3vs3RT (p=0.026, d=0.33, small-to-moderate effect) increased the time spent in higher acceleration zones compared to 3vs3HALF. Both 3vs3FULL and 3vs3RT presented more transition sprints compared to 3vs3HALF. The 3vs3FULL also presented more fakes and the 3vs3RT presented more jumps compared to the 3vs3HALF. Physiological responses presented no differences between the SSG formats. In conclusion, defensive and time pressures increase the physical demand in 3vs3 SSG performed in the half court. The three SSG investigated in this study presented mean heart rate values close to 90% of the maximum heart rate, which suggests that these SSG may be used to increase athletes’ aerobic performance.

Changes in tactical performance and self-efficacy on young female basketball players

Abstract The present study examined changes in tactical performance and self-efficacy amongyoung female basketball players across a 4-months competitive season. Repeated measures preand post a 4-month season in 30 young female basketball players (11.4 to 14.7 years-old) was considered. We applied the Self-Efficacy General Scale and examined tactical performance in a standardized 3 vs 3 exercise in half court. The 3 vs 3 exercise was analysed using Game Performance Assessment Instrument (GPAI) and Team Sport Assessment Procedure (TSAP).We examined changes in tactical performance and self-efficacy using multilevel modelling.Theresults showed that changes of Self-Efficacy scores were not influenced by 4 months of training across competition period, chronological age and years of sport participation, the changes of TSAP performance was influenced only by years of sport participation, and the changes of GPAI performance was influenced only by the period of training and competition games.

Changes in External Load When Modifying Rules of 5-on-5 Scrimmage Situations in Elite Basketball.

Vazquez-Guerrero, J, Reche, X, Cos, F, Casamichana, D, and Sampaio, J. Changes in external load when modifying rules of 5-on- 5 scrimmage situations in elite basketball. J Strength Cond Res 34(11): 3217-3224, 2020-Constraining tasks are very frequent during the team sports training process; however, most of the effects of these coaching decisions are unknown, which leads to less controlled performing environments, with less chances to promote improvements. The aim of this study was to determine the effects of modifying rules of 5-a-side scrimmage on the physical performance of professional basketball players. Data were collected from 12 elite male players (age, 29.6 ± 4.5 years; height, 1.99 ± 9.6 cm; body mass, 92.1 ± 11.9 kg) from the Spanish first Division of Basketball during thirty-three 5-on-5 scrimmage situations over a 18-week period. Physical demands were assessed using WIMU PRO Local Positioning System (Realtrack Systems, Almeria, Spain) and included total and speed-ranged distance covered, player load, peak speed, number of high-intensity actions, number of total and high-intensity accelerations and decelerations, and peak acceleration. A repeated-measures analysis of variance was used to test the differences in all variables, considering playing in half-court (HALF), half-court and transition (HTRAN), and full-court (FULL) conditions for the 5-on-5 scrimmage drill. Results showed that during the HALF condition, there was less distance covered (effect size [ES] = 3.55), lower peak speeds (ES = 3.00), less player load (ES = 2.79), lesser number of high-intensity actions (ES = 1.45), and lesser number of high-intensity accelerations (ES = 1.44) and decelerations (ES = 1.31) than in FULL. In HTRAN, players covered more distance (ES = 2.42), presented higher player load (ES = 1.88), higher intensity actions (ES = 1.02), and peak speed (ES = 4.22) than in HALF. In conclusion, physical demands can be modulated changing the rules and court size using 5-on-5 scrimmage situations, and this factor should be taken into account when designing training drills and when fine-tuning periodization.

Interactive Smart Tennis Ball Collecting Vehicle

Background: As one of the most popular racket sports in the world, tennis usually takes a considerable amount of repetitive training that uses a great number of tennis balls. After the training, collecting the tennis balls is an annoying, time consuming, and labor taking task. To cope with such problem, a great number of tennis ball collectors such as the stroller-based, basket-based, and wheeler-based collectors were proposed, also described in various patents. However, existing tennis ball collectors mostly require manual operation. To eliminate human intervention, a recent trend is to automate the process by electronic devices. Methods: Our new collector combines a wheeler-based collector with a smart vehicle providing both automatic programmed route and interactive remote-controlled collection. To accommodate tennis balls of various sizes, the basic collector comprises two discs of resilient material attached with four springs. By cascading a number of basic ball collectors side-by-side with an axle through their center, we may extend the basic tennis ball collector from single channel to multiple channels. Results: In order to simulate the distribution of tennis balls after a practice session, 30 tennis balls are randomly distributed over a half court at the start of each test. In interactive navigation tests, the user is requested to collect the 30 tennis balls as soon as possible by controlling the vehicle through a smartphone. The test results showed that the amount of time taken to complete the interactive collection fall into the range of 4 to 15 minutes; on the other hand, the time taken to complete automatic preprogramed route collection is around 14 to 15 minutes. Conclusion: In comparison with traditional labor work that usually takes more than 15 minutes, our novel design greatly reduces the collection time and improves the user experience by changing the tennis ball collection from a dull and painful task to an interesting one. Keywords: Tennis ball collector, smart vehicle, microcontroller, automatic control, collection time, labor work.

Effects of 3 months of full-court and half-court street basketball training on health profile in untrained men

PurposeThe aim of the present study was to investigate whether street basketball organized as 3 v 3 on either a half court (HC) with 1 basket or a full court (FC) with 2 baskets could improve fitness and health profiles of untrained men after 3 months of supervised training. MethodsThirty-five untrained men (aged 20–42 years) completed the pre- and post-intervention testing (FC: n = 13, HC: n = 12, CO (control): n = 10). The training attendance was 2.0 ± 0.4 and 1.9 ± 0.3 times per week in FC and HC, respectively. Mean heart rate (HR) was 83.8 ± 6.0 percent of maximal heart rate (%HRmax) and 84.5 ± 2.9 %HRmax in FC and HC, respectively. ResultsThe 3 months of street basketball training on an FC with 2 baskets increased maximal oxygen uptake (2.4 mL/min/kg (95% confidence interval (CI): 1.0–3.9)), time to exhaustion (47 s (95%CI: 26–67)), lean body mass (0.8 kg (95%CI: 0.1–1.5)), and bone mineral density (0.021 g/cm2 (95%CI: 0.011–0.031)), whereas mean arterial pressure (–5.6 mmHg (95%CI: –7.5 to 3.7)), body fat percentage (–1.6%, (95%CI: –2.5 to –0.7)), heart rate (–18 bpm (95%CI: –24 to –12)), and blood lactate (median: –1.4 mmol/L (interquartile range: –1.5 to –0.6)) during submaximal running were lowered. The changes were less pronounced after the training period when playing on an HC with 1 basket, but increases in maximal oxygen uptake (1.6 mL/min/kg (95%CI: –0.1 to 3.3)), time to exhaustion (28 s (95%CI: 9–47)), lean body mass (1.3 kg (95%CI: 0.3–2.4)), and lower body fat percentage (–0.9% (95%CI: –1.9 to –0.1)) were observed in this group. ConclusionThree months of 3 v 3 street basketball training improved fitness and led to broad-spectrum improvements in variables related to overall health profile, with the most marked effects observed when playing on an FC with 2 baskets.

Space Creation Dynamics in Basketball Small-Sided Games.

Space creation dynamics (SCDs) describe actions players perform to create a scoring opportunity. This study compared SCDs and types of offense during three different three versus three (3vs.3) basketball small-sided games (SSGs) played in half court: 3vs.3 with man-to-man defense in half playing area (3vs.3HALF), 3vs.3 with man-to-man defense in full playing area (3vs.3FULL), and 3vs.3 with reduced shot clock (3vs.3RT). We also investigated the efficacy of SCDs in all SSGs and the reliability of SCDs in 3vs.3HALF. While the efficacy of SCDs did not differ among these SSGs, 3vs.3RT presented significantly more "space creation with ball dribbled" and "shot clock violations," and less "on ball screens." 3vs.3FULL presented no differences in the SCDs and types of offense compared with 3vs.3HALF. Reliability within 3vs.3HALF was higher for "space creation with ball dribbled," "space creation without the ball," "set offenses," "fast breaks," and "loss of ball during passing or dribbling." We concluded that 3vs.3 basketball SSGs with different rules can be used for training different tactical behaviors important to formal games, especially since the 3vs.3HALF presented good reliability for many variables related to tactical behavior.

Performance profile of NCAA Division I men's basketball games and training sessions.

This study aimed to analyse live and stoppage time phases, their ratio, and action played on half and full court in college basketball games. Differences were assessed for the entire games and between halves. Moreover, differences of the live/stoppage time ratio were analysed between games and game-based conditioning drills. Ten games as well as fifteen defensive, fourteen offensive and six scrimmage-type drills of the same division I men's college team (13 players) were analysed using time-motion analysis technique. Live and stoppage time were classified in five classes of duration: 1-20, 21-40, 41-60, 61-80, >80 seconds. Half court actions started and finished in the same half court. Full court actions were classified as transfer (TR) phases when at least 3 teammates crossed the mid-court line. TR phases were then classified in 5 classes of frequency: 1TR, 2TR, 3TR, 4TR, and >4TR. The results revealed no statistically significant differences between games or between halves for the considered parameters. The only significant difference was observed for live/stoppage time ratio between halves (p<0.001). Furthermore, a significant difference of the live/stoppage ratio was found between games and game-based drills (p<0.01). Post-hoc analysis demonstrated significant differences of scrimmage-type drills in comparison to games, and defensive and offensive drills (p<0.05), whereas no differences emerged for the other pairwise comparisons. The absence of differences between games in the analysed parameters might be important to characterize the model of performance in division I men's college games. Furthermore, these results encourage coaches to use game-based conditioning drills to replicate the LT/ST ratio documented during games.

Position-Dependent Cardiovascular Response and Time-Motion Analysis During Training Drills and Friendly Matches in Elite Male Basketball Players.

The purpose of this study was to measure differences in the cardiovascular workload (heart rate [HR]) and time-motion demands between positional groups, during numerous basketball training drills, and compare the results with in-game competition demands. A convenience sample of 14 top-level professional basketball players from the same club (Spanish First Division, ACB) participated in the study. A total of 146 basketball exercises per player (performed over an 8-week period in 32 team training sessions throughout the competitive season) and 7 friendly matches (FM) played during the preparatory phase were analyzed. The results reveal that HRavg and HRpeak were the highest in FM (158 ± 10; 198 ± 9 b · min(-1), respectively). Time-motion analysis showed 1v1 to be the most demanding drill (53 ± 8 and 46 ± 12 movements per minute for full and half court, respectively). During FM, players performed 33 ± 7 movements per minute. Positional differences exist for both HR and time-motion demands, ranging from moderate to very large for all basketball drills compared with FM. Constraints such as number of players, court size, work-to-rest ratios, and coach intervention are key factors influencing cardiovascular responses and time-motion demands during basketball training sessions. These results demonstrate that systematic monitoring of the physical demands and physiological responses during training and competition can inform and potentially improve coaching strategy, basketball-specific training drills, and ultimately, match performance.

Time-motion analysis of Italian elite women's basketball games: individual and team analyses.

The aim of this study was to assess elite women's basketball game performance. Five elite women's games (3 Italian first division and 2 Euroleague) were analyzed for individual and team time-motion analyses. The individual analysis evaluated the players' movement patterns with particular focus on high-intensity activity (HIA), sprint activity, and repeated sprint events (RSEs). Team analysis included live time (LT), stoppage time (ST), and their ratio, transfer (TR) phases, and half court and full court actions. The frequency of occurrence of changes of activities was n = 576 ± 110, one every 2.56 seconds of LT. Total HIA was 8.5 ± 1.8% of LT and no significant differences between quarter periods were observed. In general, players performed linear sprints (48.3 ± 2.9%) over 1-5 m distance (56.8 ± 5.6%). The occurrence of RSE was 4.4 ± 1.7, with 58.6 ± 18.5% passive recovery between sprints. Team analysis showed no significant difference between games for LT and ST phases (ratio = 1.18 ± 0.25). For game analysis, LT and ST were 43.4 ± 7.8% and 51.1 ± 8.4%, respectively. A difference between games was found for half court actions (p < 0.01) and TR phases (p ≤ 0.05). Moreover, 1 TR and 2 TR were the most performed (45.3 and 23.9%) actions. These results encourage coaches to include repeated sprint ability with mainly linear and short sprints into a comprehensive training program.

Acute effects of strength training in the physiological and perceptual response in handball small-sided games

Summary Aim The purpose of this study was to identify the acute effects of different strength training (ST) programs in perceptual and physiological responses to handball small-sided games (SSG). Methods Twelve senior male players participated in the study (age 22.2 ± 3.4, height 1.82 ± 0.05 m, weight 80.6 ± 5.38 kg, BMI 24.4 ± 1.33; HR max 195 ± 10.3). The heart rate (HR) and the rating of perceived exertion (RPE) were measured during SSG (3 × 3 and 6 × 6: 4 blocks of 5 minutes each) in a handball half court, with and without precedent ST. Results The results showed that ST increased the time spent above 90% HR max (ST × HR Zone, P