Introduction into the game states analysis system in basketball

Perica, Ante; Trninić, Slavko; Jelaska, Igor

doi:10.5937/fizkul1102051p

Cited by 3 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…У складу с тим важно је истакнути да је адаптабилност модела тактике игре повезана са обележјима играча целог тима. Сматрамо да се тим са више свестраних играча брже и ефикасније прилагођава моделу тактике игре и тренутним односима у игри (Trninić, 2006;Perica, 2011;Perica, Trninić, i Jelaska, 2011). Успешност изведбе појединог играча и целог тима је зависна од узајамних односа унутрашњих и спољних варијабли (Dežman, 1999; Trninić et al, 2010a;Trninić, Papić, i Trninić, 2011).…”

Section: уводunclassified

The relations between the morphological status, situational efficiency and sport achievement of elite junior basketball teams

Trninić¹,

Jeličić²,

Foretić³

2012

Fizicka kultura

View full text Add to dashboard Cite

Section: уводunclassified

The relations between the morphological status, situational efficiency and sport achievement of elite junior basketball teams

Trninić¹,

Jeličić²,

Foretić³

2012

Fizicka kultura

View full text Add to dashboard Cite

“…Basketball is a team sport in which each player coordinates his individual technique and individual tactics with his teammates through the team's collective tactics (Perica, Trninić, & Jelaska, 2011). Most of the key elements of basketball take place in anaerobic mode with high-intensity activities such as short sprints, rapid changes of direction, jumps, and other movements that come from the Creatine phosphate system (Delextrat & Coen, 2009).…”

Section: Introductionmentioning

confidence: 99%

Reliability and Validity of Change-of-Direction Speed Tests for Junior Basketball Players

Selaković

Krneta

2021

FU Phys Ed Sport

View full text Add to dashboard Cite

The main goal of this study was to determine the reliability and validity of change-of-direction speed (CODS) tests for junior basketball players and to test the differences between the positions of players on the team. On a sample of 66 junior basketball players (18.2±3.18 years), the CODS was tested using the following tests: the Lane Agility Test (LAT), Zigzag Agility Test (ZAT), Agility T-test and Modified Agility T-test. Body height and body mass were used as control variables. α-Cronbach's coefficient was calculated to determine the reliability and internal consistency of the measurements, as well as the average correlation between the trials of each test. The difference between groups of players was tested by MANCOVA. CODS tests showed good to high reliability (interclass correlations ranged from 0.83-0.93 with a variability of 4.4% to 6.4% for the entire sample). The first principal component was determined, which included 83% of the total variance of the analyzed variables. Very high coefficients of internal validity of all the applied tests (0.93-0.98) were obtained on the common subject of defined measurements. Significant differences were found between groups of players by position in favor of outside players (guards) on two tests LAT and ZAT (F=18.023; 8.559 and p≤0.005) with control of the influence of body height and body mass. All tests can be rated as reliable and valid for junior basketball players. LAT proved to be the most suitable for assessing the CODS in young basketball players, with the best discrimination of players by position on the team.

show abstract

Modelling the dynamic pattern of surface area in basketball and its effects on team performance

Metulini

Manisera

Zuccolotto

2018

Journal of Quantitative Analysis in Sports

View full text Add to dashboard Cite

Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players’ movement in relation to team performance in the context of big data analytics. A specific research question regards whether certain patterns of space among players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players’ coordinates, we focus on the dynamics of the surface area of the five players on the court with a two-fold purpose: (i) to give tools allowing a detailed description and analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent. We propose a three-step procedure integrating different statistical modelling approaches. Specifically, we first employ a Markov Switching Model (MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order to highlight associations between regimes and relevant game variables. Finally, we assess the relation between the regime probabilities and the scored points by means of Vector Auto Regressive (VAR) models. We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes are strongly associated to offensive and defensive game phases and that there is some association between the surface area dynamics and the points scored by the team and the opponent.

show abstract

Introduction into the game states analysis system in basketball

Cited by 3 publications

References 5 publications

The relations between the morphological status, situational efficiency and sport achievement of elite junior basketball teams

The relations between the morphological status, situational efficiency and sport achievement of elite junior basketball teams

Reliability and Validity of Change-of-Direction Speed Tests for Junior Basketball Players

Modelling the dynamic pattern of surface area in basketball and its effects on team performance

Contact Info

Product

Resources

About