Modeling the Offensive-Defensive Interaction and Resulting Outcomes in Basketball

Abstract

PurposeWe analyzed the interaction between offensive (i.e. space creation dynamics -SCDs) and defensive (i.e. space protection dynamics—SPDs) actions in six play outcomes (free shot, contested shot, new SCD, reset, foul, and turnover) in Spanish professional basketball games.MethodData consisted of 1548 SCD-SPD-outcome triples obtained from six play-off games. We used Bayesian methods to compute marginal probabilities of six outcomes following five different SCDs. We also computed probabilities of the six outcomes following the 16 most frequent SCD-SPD combinations.ResultsThe pick action (e.g. pick and roll, pop and pop) was the most prevalent SCD (33%). However, this SCD did not produce the highest probability of a free shot (0.235). The highest probability of a free shot followed the SCD without ball (0.409). The pick was performed not only to attempt scoring but also to initiate offenses, as it produced the highest probability leading to a new SCD (0.403). Additionally, the SPD performed influenced the outcome of the SCD. This reinforces the notion that the opposition (offensive-defensive interaction) should be considered. To the best of our knowledge, in team sports, this is the first study to successfully model the tactical features involved in offense-defense interactions. Our analyses revealed that the high frequency of occurrence of some SCDs may be justified not only by an associated high probability of free shots but also by the possibility of progressively create more space in the defense (i.e. a new SCD as outcome). In the second case, it evidences offensive strategic features of progressive disruption of the defensive system through the concatenation of subsequent offensive actions.

Inside game effectiveness in NBA basketball

“…Interactions including on-ball and out-of-ball screens reduced defensive pressure and help on the receiver however they did not produce the highest effectiveness or enlarge shooting options (Figure 2). These results concur with those of Lamas et al (2015) who observed that pick actions were the most prevalent space creation dynamics, being used both to attempt scoring and to initiate offenses. Ball screen effectiveness relies on how the dribbler perceives defender's actions and how well the screener sets the screen to free the player with the ball Hollins, 2003;Vaquera, et al, 2016).…”

“…Considering the fact that the post area is naturally well protected for its proximity to the basket, it is proposed performing screens in favour of the receiver as an effective alternative to increase inside passing options since it reduces the defensive pressure. This aligns with the study by Lamas et al (2015), who reported that making the ball to reach the post generates a concentration of defensive players inside the zone to protect the basket, which often leads to the concatenation of a new offensive action. It is also worth noting that the linkage of teamwork actions should be performed under a relative intensity, which requires an active player cooperation (i.e., performing a sequence of screens and rolls during a limited ball possession time) to avoid defensive anticipation (Bazanov, Haljand, Võhandu, & Vohandu, 2005;Cárdenas, et al, 2015).…”

“…Through the categorization of player interactions in matches, research studies have identified a variety of actions used in the offence to create (1 vs. 1, screens on and off the ball, cuts towards the basket) and protect (defensive help, switch, screen deny) space (Lamas, et al, 2011;Santana, et al, 2015). These techniques have been implemented to analyse and model offensive and defensive interactions in elite teams (Lamas, Santana, Heiner, Ugrinowitsch, & Fellingham, 2015;Lorenzo Calvo, García, & Navandar, 2017;Vaquera, García-Tormo, Gómez Ruano, & Morante, 2016). Therefore, identifying trends and game patterns are key to the preparation of training sessions aimed at improving players' tactical performance and decision-making according to specific game situations and constraints (Eccles, Ward, & Woodman, 2009).…”

“…Notational analysis allows recording and quantifying data through the observation of emerging players' behaviours during the competition (O'Donoghue, 2015). Recently, Lamas et al (2011Lamas et al ( , 2015 have defined a series of actions to effectively explore players' interactions through observational analysis. This information is essential in detecting players' strength and weakness and, more importantly, in evaluating the quality of the players' decisions and its contribution to the whole attack phase (Cervone, et al, 2014).…”

Opportunities for model-based precision dosing in the treatment of sickle cell anemia

“…16, 17 In the context of dose optimization, pharmacokinetic-pharmacodynamic (PK/PD) model based Bayesian estimation was first described in the late 70’s by pioneers such as Sheiner and Jelliffe, 18, 19 and has been applied to drugs such as antibiotics with confirmed overall cost-effectiveness 20 . In recent years, it has gained renewed momentum due to a great push for precision dosing under the Precision Medicine Initiative launched by the US government 21 and rapid advances in computational power.…”