The basketball game is developed for carrying out the technical-tactical skills in high intensity, intermittently and according to the momentary needs. In official matches, the control of the
occurrences number (ON) of these actions is done by game stats. To complement the analysis, it is also used a comprehensive index called efficiency ratio (ER). In the game, these actions occur
randomly, and their combination generates high physical demands on players, however, these components (technical, tactical and physical) are analyzed independently. In this sense, the knowledge of
these ON and ER, related to the physical demands placed on athletes can contribute to the understanding of the context and qualification training. The aim of this study was to relate the sum of the
occurrences number of the match (ΣON), the ER (both obtained by the statistics of the game) and the intensity represented by the percentage peak heart rate (%HRpeak), by match period (MP) and the
whole game (WG).
Ten elite basketball male players (27.6±5.54years; 91.61±11.51kg; 1.93±0.08m), from a specific team, were observed in six games of the National Basketball Championship, in the adult male category.
Before the beginning of the competition were performed anthropometric measurements and physical tests. The ∑ON was obtained from official statistics of games by adding the field goals, free throws,
rebounds, assists, steals, turnovers, blocks made, committed and received fouls. ER was obtained from the same official statistics determined by the following formula: ER = (field goals made + free
throws made + rebounds + assists + steals) - (field goals missed + free throws missed + turnovers). To check the physical demand athletes played with HR transmitter. Data were stored in a computer
database, organized by match period (MP) and whole game (WG) and produced descriptive information. Spearman’s correlation coefficient was used between ON, ER and %HRpeak (p<0,05).
The main results point to significant associations between variables, ranging weakening, from the 1st MP to the 4th MP. The associations between ΣON vs ER were: 1st MP = 0.763 (p<0.001), 2nd MP =
0.763 (p<0.001), 3rd MP = 0.686 (p<0.001), 4th MP = 0.639 (p<0.001) and WG = 0.798 (p<0.001); between ΣON vs %HRpeak: 1st MP = 0.551 (p<0.001), 2nd MP = 0.678 (p<0.001), 3rd MP = 0.451 (p<0.005), 4th
MP = 0.383 (p<0.01) and WG = -0.005 (p>0.05); and between ER vs %HRpeak: 1st MP = 0.355 (p<0.005), 2nd MP = 0.500 (p<0.001), 3rd MP = 0.398 (p<0.01), 4th MP = 0.283 (p>0.05) and WG = -0.047 (p>0.05).
There are positive direct relationship (significant) between variables, which will weaken over the course of the MP, except for 4th MP between ΣON vs %HRpeak and the 4th MP and WG between ER vs