Most Demanding Passages in Basketball: A Preliminary Study

Salazar H., Castellano J.

Headline

Recently there is a special interest for knowing about the most demanding passages (MDP) in competition. The MDP which are most valid or best reflect this reality come from the rolling average technique, which has been applied to Australian (3) or European (6) football and Rugby League (2). Depending on the time window chosen, from the shortest to the longest results in a decreasing magnitude of the particular variable studied following the power law (4). Nevertheless, in basketball, the description of the most demanding passages has not been reported until now.

Aim

The purpose of this study is to examine MDP during official game in sub-elite basketball players using micro-technology.

Methods

Athletes: Nine semi-professional male basketball players (Spanish basketball LEB league) took part in the study (mean ± SD age, 20.3 ± 2.1 years; height, 201.9 ± 9.2 cm; weight, 93.7 ± 8.5 kg). They were all members of the same team competing at the second level, with a mean playing experience (federation level) of 2.5 years. All players were notified of the research design and its requirements, as well as the potential risks and benefits. They all provided their informed consent before the study commenced. The Ethics Committee of the University of the Basque Country gave its institutional approval for the study.

Methodology: One official match was monitored in the 2018-19 season. Two external variables were assessed: Total Distance (TD) and total Player Load (PL). Five different rolling average windows were used, 15, 30, 45, 60, and 90 seconds. Then, all values were relativized to minute of practice; meters per minute for TD and arbitrary units per minute for Player Load. The two external variable were obtained using ClearSky T6 local positioning system devices (Catapult Innovations), which enable movement patterns in sports to be monitored in a valid and reliable manner in indoor sports (5). Players were familiar with the technology used as it is used during training sessions.

Statistical Analysis: Data are presented with means, interquartile range, and minimum (Q1-1.5 SD) and maximum (Q3+1.5 SD) in Figures 1 and 2 for both total distance covered and Player Load, respectively. In addition, effect sizes (ES) were also calculated to determine meaningful differences with magnitudes classified as (1): trivial (<0.2), small (>0.2-0.6), moderate (>0.6-1.2), large (>1.2-2.0), very large (>2.0-4.0), and extremely very large (>4.0).

Results

Figure 1 showed the distance covered (m·min-1) by players regarding rolling average windows selected. The magnitude of the differences were (Cohen’d, standard error and qualitative assessment): from 15 sec to 30 sec = -2.90 (0.67) and very large decrease; from 15 sec to 45, 60, and 90 sec = -4.94 (0.95), -5.84 (1.08), and -6.62 (1.20), respectively, and extremely large decrease for all; from 30 sec to 45 sec and 60 sec = -2.68 (0.65) and -3.94 (0.81), and very large decrease for both; from 30 sec to 90 sec = -5.03 (0.96) and extremely large decrease; from 45 sec to 60 sec = -1.30 (0.52) and large decrease, and from 45 sec to 90 sec = -2.61 (0.64), and very large decrease; finally, from 60 sec to 90 sec = -1.43 (0.53), and large decrease. Figure 2 shows the Player Load (AU·min-1) by regarding rolling average windows selected. The magnitude of the differences were (Cohen’d, standard error and qualitative assessment): from 15 sec to 30 sec = -1.86 (0.56) and large decrease; from 15 sec to 45 sec and 60 sec = -3.01 (0.69) and -3.51 (0.75), respectively, and very large decrease for both; from 15 sec to 90 sec = -4.10 (0.83), and extremely large decrease; from 30 sec to 45 sec and 60 sec = -2.13 (0.59) and -3.14 (0.70), and very large decrease for both; from 30 sec to 90 sec = -4.01 (0.82), and extremely large decrease; from 45 sec to 60 sec = -0.75 (0.49), and moderate decrease; and finally, from 45 sec to 90 sec and from 60 sec to 90 sec = -1.86 (0.56) and -1.29 (0.52), and large decrease for both.

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