Puolimo charakteristikos ir jų įtaka krepšinio efektyvumui tarp laiminčių ir pralaiminčių komandų

Offensive modalities for this research were chosen from the provided “Synergy Sports Technology” software database: isolation, transition, post-up, spot-up, cut, hand-off, off-screen offense, pick and roll ball handler; roll man, putback, miscellaneous. WIN% and LOSS% were used to determine winning and losing teams on NBA playoffs. Three most used modalities were found to be: spot-up, pick and roll ball handler, and transition, while most efficient ones were cut and putbacks. Results show that significant differences were found in isolation, transition, and cuts finishing action for winning teams and pick and roll ball handlers as well as roll man for defeated teams. Efficiency differences for winning teams were found in off-screen offense, putbacks, cuts and miscellaneous modalities. NBA teams follow analytical strategy trends and tend to rely on long-range shooting, shots to close to the basket and easy baskets. Both type teams play in similar offensive structure, but winners were able to create more fast-break opportunities due to their defense and rebounding. Off the ball movement, making tough shots, offensive rebounding and putbacks, cuts had the biggest margin between winning and losing teams in terms of efficiency

The benefits of advanced data analytics in basketball: approach of the managers and coaches of Lithuanian Basketball League teams

The aim of the study: To identify approach of the managers and coaches of Lithuanian Basketball League teams to advanced data analytics in basketball. Methodology: 1. Scientific literature review 2. Online survey 3. Statistical analysis using SPSS 2.0 and Microsoft Excel programs The survey results showed, that in teams of Lithuanian Basketball League there is employees, whose main goal is to analyse performance indicators, statistical data of opponents and new incoming players. Majority of managers and coaches believe, that new information technologies of advanced basketball data could help to improve team performance results and draw more attention to basketball from fans perspective. Advanced statistics analytics is recommending teams to shoot more three point shots and drive to the basket more often, while avoiding shots from mid – range area. However there are still managers and coaches of Lithuanian Basketball League who believe, that a mid – range shot is a good and efficient shot in basketball. Managers and coaches of Lithuanian Basketball League teams believe, that advanced data specialists have a bright future in basketball industry, but first they have to prove, that advanced basketball data is important and could significantly improve team and players performances. Lithuania is a basketball country, yet a lot of organisations have difficulties using their financial resources effectively, so that is why the possibilities of advanced basketball data analysis is very important for teams managers and coaches. The correct use of limitless data would definetely help improve team performance and effectively use their financial resources recruiting the most efficient players

Puolimo charakteristikos ir jų įtaka krepšinio efektyvumui tarp laiminčių ir pralaiminčių komandų

Offensive modalities for this research were chosen from the provided “Synergy Sports Technology” software database: isolation, transition, post-up, spot-up, cut, hand-off, off-screen offense, pick and roll ball handler; roll man, putback, miscellaneous. WIN% and LOSS% were used to determine winning and losing teams on NBA playoffs. Three most used modalities were found to be: spot-up, pick and roll ball handler, and transition, while most efficient ones were cut and putbacks. Results show that significant differences were found in isolation, transition, and cuts finishing action for winning teams and pick and roll ball handlers as well as roll man for defeated teams. Efficiency differences for winning teams were found in off-screen offense, putbacks, cuts and miscellaneous modalities. NBA teams follow analytical strategy trends and tend to rely on long-range shooting, shots to close to the basket and easy baskets. Both type teams play in similar offensive structure, but winners were able to create more fast-break opportunities due to their defense and rebounding. Off the ball movement, making tough shots, offensive rebounding and putbacks, cuts had the biggest margin between winning and losing teams in terms of efficiency

The Benefits of advanced data analytics in basketball: approach of managers and coaches of Lithuanian Basketball League teams

Background. Many industries use a variety of statistical models for a decision-making, but no industry relies on analytical data as a professional sport (Davenport, 2014). Sports organization management and decision-making have a direct relationship with the sports teams and this relationship is called a comprehensive statistical analysis (Radovanović, Radojičić, Jeremić & Savić, 2013). Alamar (2013) argues that a detailed statistical analysis of the game activities is an important aspect in order to more accurately assess the player’s market value. Methods. The sample consisted of 30 respondents (10 managers, 10 coaches, 10 coach assistants) of the 10 men’s basketball teams. Managers and coaches of Lithuanian Basketball League teams had to fill in online questionnaire, the main focus of which was to identify their opinion about advanced data analytics. The questionnaire was designed based on scientific studies (Alamar, 2013; Martinez & Martinez, 2011). Questionnaire scales were tested using SPSS 20.0 statistical analysis program. Results. Statistical analysis showed that questionnaire reliability was average (Cronbach α=.549–.558). The survey results showed that the teams of Lithuanian Basketball League there employ professionals whose main goal is to analyse performance indicators, statistical data of opponents and new incoming players. Majority of managers and coaches believe that new information technologies of advanced basketball data could help improve team performance results and draw more attention to basketball from fans’ perspective. It was found that managers and coaches thought that offensive strategy depends on the players of the team. Coaches and managers had a positive approach to basketball analytics and believed that it had a bright future in basketball industry.Conclusions. The correct use of limitless data would definitely help improve team performance and effectively use their financial resources recruiting the most efficient players