Abstract
Abstract AIMS The main objective of this study was to analyze the factors that preceded field goals made in the 2014 NBA finals considering the number of passes per offense, shooting conditions, and offense type variables. METHODS We assessed field goals attempted by 27 professional players that participated in the 2014 NBA finals. Data were collected by three researchers through an adapted version of the Technical-Tactical Performance Evaluation Tool in Basketball to systematically analyze all five games of those finals. Descriptive analysis consisted in absolute and relative frequency and inferential statistics were applied through Chi-Square test, Cohen’s D for effect size, and binary logistic regression test. Significance levels were set at 5% and all statistics were applied through SPSS 23.0. RESULTS Shooting efficacy was not associated with the number of passes made per offense. Regression statistics showed that shooting efficacy was highly associated with shooting condition rather than the offense type performed. However, fast breaks seem to lead to better shooting conditions (passively guarded and wide open) when compared to set and regained offenses. CONCLUSION Evidence pointed to the importance of shooting condition as a determining factor in increasing the probability of field goals made throughout the games analyzed.
Highlights
In the last decades, the ongoing search for understanding and interpreting the complex actions present in basketball has led researchers and coaches to use game statistics techniques[1,2]
When compared to the other offense types, the detailed analysis showed that fast breaks provided smaller percentages of field goals attempts (FGA) under pressured conditions, while presenting a higher percentage of FGA under passively guarded and wide open conditions
In investigating the relation between offense type and shooting condition, the present study identified that fast breaks provided a higher relative frequency of passively guarded and wide open shooting conditions when compared to the other offense types
Summary
The ongoing search for understanding and interpreting the complex actions present in basketball has led researchers and coaches to use game statistics techniques[1,2]. Among these methods, notational analysis is characterized by being used during or after games through video recordings or specialized software to investigate athletes’ performance[3]. High numbers of field goals made (FGM)[6,7,8,9], free throws made[1,7], defensive rebounds[1,8], and assists[6,7] have been pointed out as crucial factors to ensure winning in basketball. Because game indicators represent basketball athletes’ performance in a fragmented manner, sport scientists have sought methods of data collection and analysis that contextualize game indicators and enable a broader interpretation amongst the actions present in the game[2,10]
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