The perceptual, heart rate and technical-tactical characteristics of 3 × 3 basketball

The aim of this study was to investigate the perceptual, heart rate and technical-tactical characteristics of elite male and female 3 × 3 basketball games. Eleven male and twenty-two female elite basketball players were monitored using heart rate telemetry, Ratings of Perceived Exertion (RPE) and video analysis across three 3 × 3 basketball tournaments. Linear mixed models were performed to determine the influence of round (pool game, quarter-final, semi-final, final, classification game) and sex on all dependent variables (alpha = 0.05). There was no difference between sexes for heart rate variables (p = 0.53 - 0.85). The greatest percentage (56.9 ± 20.1%) of game time was spent in heart rate zone 5 (90-100% peak heart rate). Overall RPE was higher in semi-finals (7.2 ± 1.5, p ≤ 0.001, ES: 1.27) and finals (7.7 ± 1.6 p ≤ 0.001, ES: 1.67) compared to pool games (5.1 ± 1.5). An analysis of the technical-tactical actions revealed that there were less steals in semi-finals (p = 0.01, ES = 0.56) and finals (p = 0.01, ES = 0.71) compared to pool games, with no sex-related differences present (p = 0.06 - 0.97). Players generally spent one minute on the bench for every three minutes on the court, creating a 3:1 work to rest ratio. Physical preparation programs for elite 3 × 3 basketball athletes should include exposure to high-intensity activity in which heart rates ≥80% of peak heart rate are reached for periods of time similar to that experienced during gameplay. A 3:1 work-to-rest ratio may be beneficial during conditioning training for this population.

How Haptic Feedback in a Mixed Reality Pool Game Affects Real-Life Pool Performance

Mechanisms for training pool skills have evolved from manually setting up balls in different positions on the table and hitting them one-by-one to now using technology to precisely set up these plays and practice the game virtually. The aim of this study was to investigate how adding haptic feedback into a pool video game affects transfer of training into real-life pool skills. A 2 x 4 mixed factorial design was used to see how haptic feedback (its absence or presence) and four types of shots affect pool performance. Half of the participants experienced the pool video game without haptic feedback while the other half experienced it with haptic feedback. Performance before and after the video game practice was recorded as successful or unsuccessful, with a series of the same 40 pre- and post-video-game shots. Results from 38 participants are presented, and their implications are discussed.

Using GM(1,1) to Clean-Table Offensive Techniques

The objective of this thesis is to make a position play for a billiard robot in a nine ball pool game by the Grey System Theory. The position play is the placement of the cue ball on the best position to the next planned shot. The robot is able to decide a shooting mode with a corresponding shooting strength from the developed data base of rebound paths of the cue ball. The rebound paths are calculated and recorded from four shooting modes (free shot, cushion shot, bank shot, kiss shot) with five different shooting strengths by the collision theory in a PC. The continuous position play is called the clean-table in the pool game. The moving path of object ball and cue ball are calculated by the collision theory. The grey decision making is developed to find out the best position of cue ball after shooting for the position play. The decision factors are the block ball, the shooting angle, the distance between the object ball and the pocket, and the distance between the object ball and the cue ball. The first priority of the position play is to choose the corresponding object ball and the rebound path of cue ball without any block ball. Then, the second priority is to choose the higher successful pocketing rate (large than 60%). Finally, the offensive decision is set up to make a position play by the Grey Decision-making Sub-system. The experimental results show this clean-table offensive system works very well in the pool game.