Time Estimation Among Basketball Players

Extensive research has provided much evidence for an attention-based model of time estimation (Zakay, 1992; Zakay, 1993a; Zakay 1993b; Zakay, 1998; Zakay, Nitzan, & Glicksohn, 1983; Zakay & Tsal, 1989); however, limited research on time estimation has been conducted in the sport domain. The purpose of this study was to extend time estimation research and the notion of an attention-based model into the sport arena, specifically basketball. This study implemented principles of the automatization theory (Brown, 1997) to a situation where the task is automatically performed without the need of directed attention. In particular, this study added a familiar time interval, 30 seconds, which was considered familiar to basketball players because they are accustomed to estimating it through the 30 second shot clock. Twenty female individuals within the age range of 12 – 22 participated in the study (i.e., ten basketball players and ten non-basketball players). The participants estimated three different time intervals: the familiar time interval (i.e., 30 s), a shorter time than the familiar interval (i.e., 20 s), and a longer time interval (i.e., 40 s). All estimations were done through a reproduction method. Three types of non-temporal tasks were utilized as interference with the timing task (i.e., cognitive, motor, and visual). Each interference task consisted of two difficulty levels, easy and hard. The cognitive task involved counting backwards by five (i.e., easy) or by three (i.e., hard). Dribbling one basketball was the easy motor task, while simultaneously dribbling three basketballs was the hard motor task. For the visual task participants searched for a target letter, 'K', among circular distracters, C, O, Q, U (i.e., easy) or angular distracters, V, W, X, and Y (i.e., hard). The participants first engaged in a single task, either reproducing the time intervals or performing the non-temporal tasks for all three time interval durations. Each condition consisted of four trials. A week later all participants engaged in the dual tasks, estimating the time intervals while performing the distracter non-temporal tasks. Findings revealed that basketball players experienced less interference from the non-temporal distracter tasks than non-basketball players. Basketball players were more accurate on their time estimations on all three time intervals across all types of interference than non-basketball players. Their closest estimations were during the 20 s time interval. Previous research on time estimation in sport has been extremely limited. This study provides further support for an attention-based model of time estimation, specifically within sport. The findings also suggest that athletes engaged in sport which require time estimation develop a better "sense for time" than people who have not been familiar with time constraints. Interestingly, time estimation of athletes is better than non-athletes not particularly in the specific sport time, but rather along all time estimations alike.