LITHUANIAN UNIVERSITY

MSC INTERNATIONAL COACHING AND MANAGEMENT

PROGRAMME

JAUNIUS DAVNIUKAS

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PERFORMANCE PROFILE ANALYSIS: THE INSIGHTS OF ELITE MEN TOURNAMENT

FINAL MASTER‘S THESIS

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KAUNAS 2021

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I hereby declare, that the present final Master’s thesis “Performance Profile Analysis: The Insights of Elite Men 3X3 Basketball Tournament” 1. Has been carried out by myself; 2. Has not been used in any other university in Lithuania or abroad; 3. Have not used any references not indicated in the paper and the list of references is complete.

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ABSTRACT ...... 4 SANTRAUKA ...... 5 INTRODUCTION ...... 6 1. LITERATURE REVIEW ...... 7 1.1. Importance of performance indicators ...... 7 1.2. Fatigue factor ...... 9 1.3. 3x3 Basketball ...... 11 1.4. Game-Related statistics ...... 13 2. RESEARCH METHODOLOGY AND ORGANIZATION ...... 15 3. RESEARCH FINDINGS ...... 20 4. CONSIDERATIONS ...... 24 CONCLUSIONS ...... 28 SUGGESTIONS ...... 29 REFERENCES ...... 30

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ABSTRACT

PERFORMANCE PROFILE ANALYSIS: THE INSIGHTS OF ELITE MEN 3X3 BASKETBALL TOURNAMENT

Keywords: FIBA 3x3; performance analysis; tactics; ball possession; coaching The aim of the research is to determine the differences between winning and losing teams by comparing variables of ball possession in the final day of FIBA 3x3 2020 in Jeddah. Research methods: The results were classified into three groups according to the analyzed duration of the game: full game; first 5 min and remaining time of the game. Eight best teams in the second day of the tournament during quarterfinal, semi-final and the final game were investigated. By analyzing the 506 attacks in total, the types of ball possessions were observed. Main findings: The results showed statistically significance differences between 1-point zone (p < 0.05) and large Effect Size (ES) (ES = 1.24). By comparing the results of winning and losing teams, it was determined that the most significant differences of the ball possession were: P&R screener (p < 0.001; ES = -0.98); P&R ball handler (p < 0.05); dribbling shot (p < 0.01; ES = -0.68); post-up (p < 0.001; ES = 1.31) and penetration (p < 0.05). Conclusions: 1. According to the evaluation of the performance profile outcomes between winning and losing teams it was found that the winning teams performed more often in the group actions and executed that in 2- point zone. 2. By evaluating the types of ball possession during the full game according to different variables per minute, it was revealed that winning teams performed more often at P&R Screener, P&R ball handler and dribbling shot than losing teams. The losing teams also performed greater number at off-screen, cuts, post up and penetration. 3. By comparing the executed types of ball possession during the first 5 min of the game, it was noticed that the winning teams performed significant difference at dribbling shot. The situations of all types of P&R action showed no differences between the results of winning and losing teams. The losing teams played more often at off-screen, cut, post up. During the last 5 min of the game, a significant difference was found in the between P&R Screener and put back action, by comparing results of winning and losing teams.

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SANTRAUKA

RUNGTYNIŲ PROFILIO ANALIZĖ: ELITINIO LYGIO VYRŲ 3X3 KREPŠINIO TURNYRO ĮŽVALGOS Raktiniai žodžiai: FIBA 3x3; žaidimo analizė; taktika; kamuolio valdymas; treniravimas Tikslas: nustatyti skirtumus tarp laiminčių ir pralaiminčių komandų lyginant skirtingų tipų atakas finalinėje FIBA 3x3 turnyro dienoje Džedoje 2020 m. Tyrimo metodai: Tyrimo rezultatai buvo kvalifikuoti į tris grupes remiantis analizuojamu rungtynių laikotarpiu: pilnos rungtynės, pirmosios 5 min ir likęs rungtynių laikas. Buvo analizuoti atakų tipai geriausių aštuonių komandų iš finalinės turnyro dienos žaidžiant ketvirtfinalius, pusfinalius ir finalą. Išanalizavus iš viso 506 atakas, buvo stebimi atakų tipai. Tyrimo rezultatai: Tyrimo rezultatai parodė statistiškai reikšmingus skirtumus tarp atakos užsibaigimu 1 taško zonoje (p > 0.05; ES = 1.24). Palyginus laiminčių ir pralaiminčių komandų rezultatus, buvo nustatyta, kad reikšmingiausi atakų tipų skirtumai buvo: žaidimo du prieš du perduodant kamuolį statančiam užtvarą (p < 0.001; ES = -0.98); žaidimo du prieš du užbaigiant ataką tam pačiam žaidėjui (p < 0.05); metimai po kamuolio varymo (p < 0.01; ES = -0.68); žaidimo nugara į krepšį (p < 0.001; ES = 1.31) ir prasiveržimai (p < 0.05). Išvados: 1. Remiantis laimėjusių ir pralaimėjusių komandų rungtynių analizės rezultatų įvertinimu buvo nustatyta, jog laiminčios komandos dažniau atliko komandinius veiksmus ir juos realizuodavo 2 taškų zonoje. 2. Įvertinus atakų tipus, remiantis skirtingais kintamaisiais, atliktais per minutę, buvo nustatyta, jog tiriant visą rungtynių laiką, laimėjusios komandos dažniau atlikdavo žaidimo du prieš du veiksmą atiduodant kamuolį statančiam užtvarą arba užbaigiant ataką tam pačiam žaidėjam, kuris gavo užtvarą, taip pat dažniau atlikdavo metimus po kamuolio varymo nei pralaimėjusios komandos. Pralaimėjusios komandos dažniau atlikdavo užtvaras žaidėjui be kamuolio, prakirtimus, žaidimo nugara į krepšį ir prasiveržimo veiksmus. 3. Palyginus atakų tipus, atliktus per pirmąsias 5 žaidimo minutes, buvo pastebėta, jog laimėjusios komandos pasižymėjo statistiškai reikšmingu skirtumu tarp metimų po kamuolio varymo. Palyginus laimėjusių ir pralaimėjusių komandų rezultatus, skirtumas nebuvo nustatytas atliekant visų tipų veiksmus du prieš du situacijose. Pralaimėjusios komandos dažniau žaidė naudojant užtvaras žaidėjui be kamuolio, prakirtimus ir žaidimą nugara į krepšį. Apžvelgus laimėjusių ir pralaimėjusių komandų rezultatus, per paskutiniąsias 5 žaidimo minutes buvo nustatytas reikšmingas skirtumas palyginus du prieš du veiksmą atiduodant kamuolį statančiam užtvarą, ir kamuolio pataisymą ore po netaiklaus komandos draugo metimo veiksmo. 5

INTRODUCTION

Relevance of the topic. FIBA 3x3 basketball has had an exponential increase in popularity in recent years, with claims that it is now the most popular urban team in the world. To support this popularity, 3x3 basketball has developed European and competitions, a profitable professional league competing in exotic locations around the world and has now been included in the 2020 (FIBA. History, 2016). According to that, 3x3 basketball is a relatively new sport, therefore little is known regarding the teams and players performance profiles, physical and physiological responses of players during these games (Conte, Straigis, Clemente, Gomez, & Tessitore, 2019; Montgomety & Maloney, 2018). However, there may be an assumption within the basketball community that these demands are similar to traditional 5x5 basketball. Since the research of this topic has not been fulfilled widely, there is no evidence to support this notion yet. The problem of this research is to find the best performance analysis in the offense, therefore the obtained data is valuable for the coaches and players in order to achieve the better results and to develop the level of 3x3 basketball (Conte et al., 2019; Matulaitis & Bietkis, 2021). By applying the performance indicators in analysis, this research enables the perception about basketball game performance, which can reflect teams’ performance for coaches in order to create the best strategies and tactics within the games (Sampaio, Godoy, & Feu, 2004). The aim of the research: to determine the differences between winning and losing teams by comparing variables of ball possession in the final day of FIBA 3x3 2020 world cup in Jeddah. Objectives: 1. To investigate the outcomes of offensive profile between winning and losing teams by comparing group or isolation actions and the realization zone of offense. 2. To evaluate the differences of performance profile types during the full game according to the ball possession variables per minute by comparing the winning and losing teams. 3. To determine and evaluate the first 5 min and the remaining time of the game by comparing the differences of performance profile types according to ball possession variables per minute between the winning and losing teams. Hypothesis: 1. The winning teams more often perform in a greater number of group actions and finish the attacks more in 1-point zone than losing teams. 2. The P&R situations are the dominants actions performed by the winning teams. 3. During the first 5 min of the game the use of variables of group and isolation actions are similar; however, the variables of group actions are dominant in the winning teams, while variables of isolation action are more applied by the losing teams during the remaining time of the game.

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1. LITERATURE REVIEW

1.1. Importance of performance indicators

Performance indicators analysis is used to identify performance of an individual or team elements (Hughes & Bartlett, 2002). Performance analysis is a branch of sport science, investigating at different levels of performance (youth, semi-professional, or professional players) (Gomez, Ibanez, & Leicht, 2020), is very important for many participants involved in this sphere such as coaches, technical staff, performance analysis, managers, media, fans and players. Various researches in previous investigations have analyzed the game performance indicators in winning and losing teams during one season or more seasons, or a short-duration of tournament (Saenz-Lopez, Gimenez, & Janeira, 2003; Ibanez, Sampaio; Ibanez, Garcia, Feu, Lorenzo, & Sampaio, 2009; Mikolajec, Maszczyk, & Zajec, 2013; Conte et al., 2019). The game style between different parts of the game (Gomez, Lorenzo, Ibanez, & Sampaio, 2013; Gomez, Lorenzo, Saiz, & Navarro, 2015), between regular and playoffs game (Garcia, Ibanez, De Santos, Leite, & Sampaio, 2013; Puente, Coso, Salinero, & Abian-Vicen, 2015), between close and balanced games (Sampaio & Janeira, 2003; Gomez, Lorenzo, Sampaio, Ibanez, & Ortega, 2008; Csataljay, O’Donoghue, Hughes, & Dancs, 2009; Lorenzo, Gomez, Ortega, Ibanez, & Sampaio, 2010; Cene, 2018), were also investigated by other scientists. The knowledge of the most important performance elements enables the coach for the better preparation for the games (Csataljay et al., 2009). One of the performance analysis methods is that the systems of the coach have to be build up on the performance indicators strategy by comparing winning and losing teams (Gomez et al., 2008). By using performance indicators, the coach was able to identify performances the quality of the game. In the close game situations especially, the coaches should know what kind of indicators were the most important. By analyzing the games of the team and by using performance indicators, the coach can determine the reasons of winning or losing that game. In addition, coach should find the elements that were not achieved after the losing game (Christmann, Akamphuber, Mullenbach, Gullich, 2018). The protocol of the FIBA statistics showed 13 separate variables of the basketball games. Moreover, this information could be useful after the first half, in order to prepare the team better for the second half of the game (Csataljay et al., 2009). During the last decade, the performances indicators have been applied not only for the preparation of the performance, but for the practices too. Therefore, it was very important tool for the

7 whole staff of coaches. This method of analysis helped the coaches to collect the required information about opponents, competitions, and own team (Garcia et al., 2013). By using performances indicators, the coach could prepare the microcycle, mesocycle plan for the team (Garcia et al., 2013). According to this information, the more successful basketball teams were characterized by offensive or defensive tactical strategies. Even though the offensive game actions were more correlated to the winning team, it was likely that a balance between offensive and defensive tactics was the most successful basketball strategy (Puente et al., 2015). According to Abdelkrim, Fazaa, & Ati, (2007), it was determined that shortening the attack time-limit had led to a decline in the adoption of long offensive tactical systems in favor of a further exploitation of players individual creativity. By comparing performed number of actions in small-sided basketball with traditional one, it was noticed that the small side players accomplish a larger number of actions, which may be explained by that small-sided players were more involved in ball possession during a match (Bredt et al., 2018). Furthermore, few studies have examined how basketball teams used their opportunities to score and analyzed the effectiveness of ball possession (Gomez et al., 2013; Matulaitis & Bietkis, 2021). Moreover. Gomez and his colleagues (2010) have suggested the importance of group tactical offensive and defensive behaviors, such a screens on the off the ball, multiple screens and defensive system. It was determined that by using the tactical of the ends of possession, the coaches could coordinate the offence structure, player decision making and create greater effectiveness of the offence (Matulaitis & Bietkis, 2021). Other researches are comparing different performance indicators during the game (Sampaio, Lago, Casais, & Leite, 2010; Gomez et al., 2015). According to Gomez and his partners, (2015) during last 5 min or of the game, players may be more exposed to distractions and it could have impacted the poorer decision-making ending in turnovers or bad field-goal selection. Performance indicators were therefore important as means which evaluate and provide feedback on the team and individual players on good and bad performances and were able to identify which performance indicators influence the outcomes of matches, which would aid the coaches in planning game strategies to their opponents’ weakness, to improve the team’s chances of winning (Csataljay et al., 2009; Francis, Owen, & Peters, 2019). By using the performance analysis in basketball with the determination of the most important game-related statistics during the game, it was aimed to improve the team performance, increasing the knowledge of the performance of each coach (Lorenzo, Lorenzo, Conte, & Gimenez, 2019). Every coach in conceiving their training should have very clear goal, for example: to create independent and creative players thinking. The coach should always take a critical and constructive relation with its own exercises so it would be possible to verify the effectiveness and,

8 in time, to be able to use certain exercises in order to highlight aimed aspects and to correct any bad habits (Altavilla & Raiola, 2014). A player capable of recognizing the technical and tactical aspects during the game, is certainly more capable than others to understand in advance the intentions of the opponents. Therefore, this puts him in a position to choose which key to play effectively perform in a given game situation (Altavilla & Raiola, 2014). According to all the above information, in order to accomplish the successful fulfilment of the team, the performance indicators are extremely important for the coaches in preparation for practices, tournament and the whole season.

1.2. Fatigue factor

Since FIBA 3x3 tournaments were usually played as a day-by-day tournament, there was only a little time for physical recovery for the players. On the first day of the tournament, teams had two games and tried to overcome a group stage. In the final day of tournament, teams had from 1 to 3 games, depending on how many games have they won (final teams play 3 games in the second day of the tournament) (FIBA. Rules, 2019). Therefore, it was very important to consider the factor of fatigue (Royal et al., 2006). The latter was a very complex conception, involving psychological, physiological, and technical factors (Astrand, Rodahl, Dahl, & Stromme, 2003; Montgomery & Moloney, 2018). A study revealed that 3x3 basketball game was considered to be as a high-intensity game that demanded highly developed aerobic and anaerobic capacities in order to be successfully played. Furthermore, basketball with high-speed inertial movements within limited distance created a relatively high physiological response (Montgomery & Maloney, 2018). Furthermore, fatigue is one of the most important factors in a sport as basketball because it is one of the indicators determining the winning and losing teams (Lyons, Al-Nakeeb, & Alan, 2005). There are a lot of different physical elements in basketball, depending on the fatigue such as changing tempo, requiring speed, acceleration, explosive movements and jumps (Montgomery, Pyne, Minahan, 2010). Players of FIBA 3x3 had wide variation for height and mass, although the relevance of height as 3x3 may be less important as player and teams focus on the ability to score quickly (Montgomery & Moloney, 2018). Moreover, with this reduce game format all players were encouraged to better develop awareness of basic attack and defense elements (Sampaio, Abrantes, & Leite, 2009). However, size and shape of 3x3 players may be aggregating towards that of shooting guard or forward as described in traditional basketball, as these player types combined attributes of speed, agility and shooting capacity,

9 while still being able to maintain physical strength and be able to , make shots which are important demands in elite 3x3 basketball (Montgomery & Moloney, 2018). Furthermore, the anaerobic capacity for the smaller athletes was not impressively developed, because the bigger athletes hold the ball most of the time (Zamzami, Solahuddin, Widiastuti, Tangkudung, & Pradityana, 2020). To determine physiologically standard performance tests, there was often little difference between levels for male and female of 3x3 players across the various international tournaments (Montgomery & Moloney, 2018). Such information could be useful for coaches to prepare for tournaments and to help improving the design of effective physical training programs to avoid the fatigue (Sampaio, Abrantes, & Leite, 2009). Wearable technology has been applied in many sports, because it was helpful in measuring the external load during the game (Royal et al., 2006; Montgomery & Moloney, 2018). Since basketball traditionally is an indoor court-based sport, it had a little exposure to the investigation and research of the game demands using wearable technology (Rodriguez-Alonso, Fernandez-Garcia, & Perez, 2003). However, FIBA 3x3 basketball is usually played outdoors courts, allowing combined inertial sensors to be accessed for investigation of the game demands (Montgomery & Moloney, 2018). The study of Montgomery & Moloney (2018) had investigated 238 males and measured the external load during the game. Male 3x3 players covered on average 867.0 ± 220.8 m and 46.6 ± 10.3 m∙min-1 during a game. The previous study of Montgomery & Moloney (2018) was aimed to investigate the physical and physiological. However, by comparing several physiological aspects the outcomes of research it was revealed that 3x3 players were a group of players which have different performance capacities, and this may be related to the differing game demands of 3x3 compared to traditional basketball (Montgomery & Moloney, 2018). The study of Sampaio and his colleagues (2009), has determined that the heart rate of 3x3 groups beats 173.4 ± 8.3 min-1 and 87 ± 4% of HRmax. Therefore, 3x3 game contributed to higher physiological demands than traditional basketball, which had a significant influence on the fatigue (Sampaio et al., 2009; Montgomery & Moloney, 2018). Furthermore, it was noticed that by reducing the number of players and the playable area, the game intensity was increasing (Hill Haas, Rowsell, Coutts, & Dawson, 2008). The other investigation of small-sided basketball demonstrated that by reducing the duration during FIBA 3x3 basketball games, the number of violations was increased (Bredt et al., 2018). Thus, players had much less time to create a ball possession, and this might produced more turnovers and defensive fouls compared to traditional 5x5 basketball (Bredt et al., 2018; Conte, Tessitore, Gjullin, Mackinnon, Lupo, & Favero, 2018; Conte et al., 2019). According to literature, the majority of the live time and stoppage

10 time phases had less than 20 s duration 58.1% and 57.6% respectively (Conte et al., 2019). However according to Montgomety and his partners (2008), the fatigue and performance could be identified by the power of the three-points appearing in the third game of the tournament and by the ability of winning teams to shoot better from longer distance. This could have been the results of higher conditioning status comparing with losing teams. Finally, the total movement of the athletes in 3x3 games was greater than traditional 5 on 5 game, considering greater players load and distance covered per minute (Zamzami, Solahuddin, Widiastuti, Tangkudung, & Pradityana, 2020). According to the search data mentioned above, factors, having the biggest influence on the fatigue, are little recovery time, multiple games per day. In comparison with traditional basketball, small-sided basketball has smaller playing area, a smaller number of players, shorter clock duration which also have a significant influence on the fatigue.

1.3. 3x3 Basketball

During recent years, FIBA 3x3 basketball has had an exponential increase in popularity, with claims that it is now the most popular urban in the world. To support this popularity, 3x3 basketball has developed European and World Championship competitions, a profitable professional league competing in exotic locations around the world, and since 2020 it has been included in Olympic Games (FIBA. History, 2016). Many countries have hosted the tournaments of different levels, with the numbers of competitive 3x3 events reported to grow in 2019 compared with 2018: the number of professional 3x3 competitions has grown by 20 %; and qualifications for the professional 3x3 competitions and national competitions have grown by 39 % and 30 %, respectively. This means that the national federations are increasingly active in the rating events to qualify for the Olympic Games (Zurubina, Andryushchenko, Averyasova, Gineviciene, & Organ, 2020). According to the FIBA and the department specifically dealing with the development of 3x3 basketball, organizing a single FIBA 3x3 basketball event has a lot of benefits for the country and the host cities at sports, financial, promotional, and social levels (FIBA. History, 2016). However, the organization of FIBA only intensified the focus on 3x3 basketball in 2007, when FIBA decided to approve new sport branch in the 2010 (YOG) in . In addition, this change had a significant influence on this sport popularity. FIBA worked intensively on adapting the rules, that this sport would be attractive to the players and spectators. Moreover, FIBA 3x3 basketball has a lot of unique characteristic: it is played on a half of the court (15 m width x 11 m length) with

11 only one hoop, the game ball is smaller, but the same weight as men 5x5 basketball ball. Furthermore, teams have a smaller number of members: three starting players and one bench player. The coach is not allowed to contact with players in any kind of behaviour during the game, the scoring is 1-2 points, no personal fouls, 12 seconds shot clock duration. Furthermore, a shot after score or rebounded by the defensive team must be returned to outside the traditional 3-point line before the transition to offence and the finally team who reached 21 points first is a winner of the game. The players are not excluded based on the number of personal fouls. If the team reaches 7, 8 and 9 fouls, the team will always be penalized with 2 free throws. If the team gets 10th fouls and more, any subsequent team will be penalized with 2 free throws and the ball possession (Table 1). There is no inbounding ball in the FIBA 3x3 basketball. The possession of the ball after the any dead ball situation will start with a check-ball (exchange of the ball between the defensive and the offensive player at the top of playing court) (FIBA. Rules, 2019). Table 1. The differences of rules between FIBA 3x3 and FIBA 5x5 basketball (FIBA. Rules, 2019). Criteria FIBA 5x5 FIBA 3x3 Coach during the game Yes No Shot clock violation, s 24 12 Game time, min 4 x 10 10 Overtime 5 min. Up to 2 points Maximum points - 21 Player (Bench player) 5 (7) 3 (1) Personal fouls 5 - Scoring points 3-2-1 1-2 Ball size 7 6 Inbounding After dead ball or points - Court Full (two basket) Half (one basket)

As a popular urban team sport, 3x3 basketball rules are relatively simple and designed to be fast, spectacular and exiting (Zamzami et al., 2020).

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1.4. Game-Related statistics

The analysis of game-related statistics can be helpful for understanding the FIBA 3x3 basketball performances (Conte et al., 2019). Most of the statistics related with basketball game consisted of the offensive and defensive complex of tactics (Lorenzo et al., 2019). The recent study of game-related statistics has shown the most important differences between winning and losing teams in 3x3 basketball (Conte et al., 2019). According to the study of Conte and his colleagues (2019), it was determined that winning teams made and attempted more free throws compared with losing teams. In addition, it was the indication that losing teams likely fouled more during shooting actions, and then allowed the winning teams to have more attempts to score points and win the game (Conte et al., 2019). Furthermore, statistically significant differences between models were found, which stated that losing teams performed higher number of offensive rebounds, defensive rebounds, and turnovers compared to winning teams. Moreover, it was established that winning teams had a higher offensive rating and recovered more balls per ball possession, while losing teams had a higher defensive rating and higher offensive rebounding percentage (Conte et al., 2019). It is important to note, that in 3x3 basketball 2- points shots are counting as a 1-point shot. The study of Koh, Wang, & Mallett (2017) has determined the statistics of top 10 bottom teams in the first ever organized tournament of female 3x3 basketball in Youth Olympic Games 2010. The results have shown that the successful teams had greater results in field goal percentage, fouls on (create fouls on opponents), assists, turnovers and free throw awarded. Game related statistics were widely investigated in traditional 5x5 basketball (Gomez et al, 2008; Lorenzo et al., 2010; Conte et al., 2018). According to research implemented in traditional basketball, the winning teams showed a likely higher percentage of 3–point goals made, number of defensive rebounds and steals, and a higher number of free throws made and free throws attempted (Ibanez et al., 2009). Furthermore, the winning teams showed a statistically higher team offensive rating, effective field goal percentage and a higher free throw rate compared to losing teams (Conte et al., 2018). According to Dogan, Isik & Ersoz (2017), it was determined that offensive rebounds, defensive rebounds, assists, steals and turnovers were more important for game-related statistics than the others and had the greatest effect on a team’s success. This analysis also showed that the defense was more effective on team success than the offense. According to literature, it was considered that the half of the top teams usually performed a higher number of assists and offensive rebounds than the half of the bottom teams, which indicated that the half of the top teams in general shared ball and attacked more (Dogan et al., 2017). Moreover, Zhang and his colleagues (2018) study showed that during away games, center position players from winning team made more assists and steals than the same position 13 players from losing team. Meanwhile forward position players from winning team made more free throws than the same position players from the opponent team. Furthermore, defensive rebounds, blocked shots, and assists were the main three components to classify the winning teams (Zhang et al., 2018). According to Clay & Clay (2014) study, it was determined that NCAA team, had a greater number of defensive and offensive rebounds and steals, if they had a larger rotation. The teams, which had a smaller rotation, tended to made field goals and three throws better. They also were more effective at taking care of the ball, which led to a smaller number of turnovers. According to various researchers, the game related statistics might be investigated in different interval of the game. For example, Navarro, Lorenzo, Gomez, & Sampaio, (2009) examined the 41 critical moments of close games during the last 5 min and identified that unsuccessful 3-point field goals, successful free-throws and defensive rebounds were the main components separating winning and losing teams. The results of Gomez and his colleagues (2015) study showed that during the last 5 min of the close games the winning teams increased their chance to win by obtaining better values in successful 2-points, 3-point and free throws field goals, defensive rebounds, offensive rebounds, steals and blocks. On the other hand, the variables that increased the probabilities to lose the game during last 5 min were the fouls committed, unsuccessful 3-point field goal, turnovers and blocks received. In fact, the teams, which were more focused on attacks with longer ball possessions and more passes, generated better and clearer field-goals from open spaces, better defense with pressure that forced the opponent to commit mistakes or to make unprepared shots (Gomez, Silva, Lorenzo, Kreivyte & Sampaio, 2017). The coach also can control and manipulate the variables on the court in order to influence the team scoring. The performance before and after the substitution had an influence on immediate fouls in the first game quarter or personal fouls of the team and players (Gomez et al., 2017). The study of Petrov & Bonev, (2020), analyzed 3x3 basketball players the most common action after a player receives a pass from a teammate. The shooting was performed at 44%; game 1 on 1 – 26%; double pass – 15%; Pick and roll with a ball – 11% and Pick and roll without a ball – 4%. According to the literature, in FIBA 3x3 the most important game related statistics are free throws, fouls, offensive rebounds, defensive rebounds, turnovers. By analyzing this data, the differences between winning and losing teams can be obtained.

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2. RESEARCH METHODOLOGY AND ORGANIZATION

Research object

The performance profile indicators of the best eight teams of FIBA 3x3 World Cup in 2020, Jedda.

Research strategy and logic

3x3 basketball is a new type of basketball, with different rules and play style. This research will help the basketball coaches to gain new knowledge about this type of basketball. Only a few research studies were performed about FIBA 3x3 basketball. Game-related statistic statistics were investigated by Conte et al., in 2019. Physical and physiological characteristics together with movement and physiological demands were examined by Montgomery & Maloney in 2018. However, the investigation about the performance analysis has not been conducted. The type of performance analysis strategy from traditional basketball studies was applied in this work (Matulaitis & Bietkis, 2021).

The nature of research

Quantitative analysis of basketball performance, particularly through game statistics, was being widely used among coaches in order to analyze the game events with more valid and reliable data. The published research on this subject was mainly focused on the identification of the most discriminant statistics according to winning and losing teams (Sampaio & Janeira, 2003).

Research subjects

The eight best teams from the final of FIBA 3x3 2020 world cup in Jeddah were analyzed. Only the second day of the tournament was investigated: quarterfinal, semi-final and final game (points per game = 17.8 ± 3.3; average game duration = 9.1 min). In order to make to the second day, the team must have passed the group stage. Each team composed of four players (mean ± SD: age: 30.3±3.1 years; height: 195.38±6.27 cm; body mass: 95.31±7.75 kg). On average, each player had played 218.56±161.62 official games.

Research methods

According to FIBA 3x3 basketball rules, the analyzed games consisted of 10 minutes per game, or until 21 points were reached firstly by one of the teams. The videos of the games were downloaded from a public website (https://www.youtube.com/3x3planet). During the research, the performance of 15 basketball 3x3 tournament was analyzed and the comparison of the full game, the first 5 min of the game and the remaining part of the game was made. The number of actions performed by the team was calculated per minute due to differences of each game duration (Navarro et al., 2009; Gomez et al., 2015; Sampaio et al., 2016; Gomez et al., 2017). The formula of calculation: (min *60 + s) / 60 (O’Donoghue, 2010). The analysis and calculations of performance indicators parameters were carried out by using “Microsoft Excel 2010” program. For technical parameter analysis, “LongoMatch Video Analysis 1.0” was used.

Game observations

In total 506 attacks were observed during the second day of world cup. The protocol with situational variables was created in order to gather all the data (Table 2). Definitions of these variables can be found in the previous studies (Matulaitis & Bietkis, 2021). The results were divided into 3 categories, according to the analyzed part of the game: the full game, first 5 minutes and remaining time of the game. The protocol of the data was used in the analysis of all games of the second day in the tournament: quarter finals, semi-finals and the final (Conte et al., 2019).

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Table 2. Definition of outcomes and the ends of the actions of the ball possession (Matulaitis & Bietkis, 2021; FIBA. Rules, 2019).

Variables Description Ends of the ball possession play types An offensive player, after the ball has been cleared, shall not hold the ball and/or dribble Post up inside the basket with his back or side to the basket. For this move player has no more than 5 consecutive seconds. Ball-handler playing isolation situation and Penetration finishing from the pain. Ball-handler playing isolation situation and Dribbling shot finishing from the pain. The player making a shot or penetration without the ball dribble. These shots have been making Spot Up shot after the “check-ball” or after the pass from the teammate. After the unsuccessful shot the offensive player Put back jump and fixed the shot in the air. Quick-lost ball and other actions that cannot be classified into either of the above-mentioned Other finishing actions (offensive foul, half-court or longer shots, ). Group actions outcome The player hands out the ball to another player, Hand off which uses the passer’s screen to make a shot or to penetrate to the basket. Pick and Roll screener (P&R screener) Screener rolls to the rim or rolls away. Pick and handler (P&R ball handler) Screen set on the ball handler’s assigned defender. After the P&R situation the ball goes to the Pick and Roll remaining player (P&R skip pass) remaining player. Inside cut or outside cut and finishing action with Cut a shot or penetration after a pass. Quick-lost ball and other actions that cannot be classified into either of the above-mentioned Off-screen finishing actions (draw foul during the screen or hand off, make a turnover after situation which not included in any outcome).

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The mentioned above outcomes have been also classified into the first and second actions, isolation or group action and the realization zone of offense (1 point zone or 2 points zone). If the first and the second action coincided, then it was assigned as the isolation outcome, if the first and second actions were separated, then it was assigned as the group actions. One of the aims of the study was to identify the importance of ball possessions in FIBA 3x3 basketball, when controlling for situational variables of game zone (Figure 1) (Gomez et al., 2013).

Figure 1. 1- and 2-points zones in FIBA 3x3 basketball (FIBA. Rules, 2019).

The effectiveness of ball possession was transformed into a dichotomous dependent variable: the successful ball possessions (when the offensive team scored a 1- or 2-points field goals; received a foul; took the offensive rebound), and the unsuccessful ball possessions (when the offensive team missed a 1- or 2-points field goals; got the blocked a shot; committed a foul; made a turnover; made any other rule violation) (Gomez, Gasperi, & Lupo, 2016; Dogan et al., 2017; Zhang et al., 2018; Matulaitis & Bietkis, 2021). It is worth noting that in FIBA 3x3 basketball every shot from inside the arc (1-point field goal area) shall be awarded by 1 point, every shot from behind the arc (2-points field goal area) shall be awarded by 2 points and free throw be awarded by 1 point (FIBA. Rules, 2019).

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Research organization

The direction of the research (3x3 basketball) was chosen in 2020 August. The manuscript of literature review was finished by 2020/11/01 and consistently filled in until 1st of April. The video analysis had been started on 2020/12/18, after the FIBA 3x3 2020 world cup final in Jeddah. The statistics data analysis of the official score sheets and game observation started in January and was finished in February of 2021. The study was approved by the University Ethics Committee and met the ethical standards (2020/12/02 Nr. SMTEK-61). Statistical data analysis All analyses were conducted using the statistical software IBM SPSS version 25 for Windows (IBM. Corp., Armonk, NY). The descriptive statistics were reported as mean and standard deviations for all variables. The data normality assumptions were calculated using the Shapiro–Wilk test to check the use of non-parametric or parametric analysis. Then, the Mann–Whitney U (non-parametric) and student-t (parametric) tests were considered to check univariate differences between teams (winning vs losing). In the assessment of the reliability of the results, the difference was deemed to be statistically significance where p < 0.05 (the reliability of 95%). The Effect Size (ES) was characterized for the practical significance rather than simple interpretation of statistical significance (Batterham & Hopkins, 2006). Magnitudes of effect sizes were assessed and classified using the criteria of: <0.2; trivial, 0.2- 0.6; small, 0.6-1.2; moderate, 1.2-2.0; large and >2.0; very large, with corresponding 90% confidence intervals. Where the confidence intervals crossed both the positive and negative small effect (0.2) the ES was deemed unclear (Hopkins, Marshall, & Batterham, 2009).

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3. RESEARCH FINDINGS

By comparing results of winning and losing teams, the types of outcomes and place of their performance on average during the full game of top 8 teams in FIBA 3x3 Saudi Arabia world cup 2020 are presented in table 3. The results showed statistically significant differences between losing and winning teams in situations per game in 1-point zone (p = 0.038) and large effect size value (ES = 1.24). The outcomes per game in 2-point zone showed moderate effect size value (ES = -0.65) on average. It was determined that the losing teams played more often in isolation situations, the results showed moderate ES (0.85). Between group actions, the results did not show statistically significant differences (Table 3).

Table 3. Full game outcomes average by comparing winning and losing teams, between 1- and 2-point zones and isolation or group actions.

Teams losing vs winning teams Outcomes Winning Losing P-value ES (90% CI) Interpretation 1-point zone 18.3 ± 4.6 23.4 ± 3.6 P=0.038 1.24 (0.25; 2.19) Large 2-point zone 16.9 ± 4.3 13.4 ±6.1 P=0.251 -0.65 (-1.54; 0.27) Moderate Isolation action 13.9 ± 5 17.6 ± 3.7 P=0.137 0.85 (-0.09; 1.76) Moderate Group action 21.1 ± 4.5 19.4 ± 6 P=0.555 -0.32 (-1.20; 0.57) Small

The analysis of variables among different ends of the ball possession, by comparing twelve ends of the ball possessions are presented in table 4. During the second day of the FIBA 3x3 world cup, it was estimated that the winning teams on the first action of the position most often played in P&R screener (p < 0.001; ES = 0.98); P&R ball handler (p = 0.044) and Off-screen (p = 0.005; ES = 0.7). Furthermore, the variables of the final play were often performed in dribbling shot (p = 0.043; ES = - 0.68); post up (p = 0.001; ES = 1.31); penetration (p = 0.022; ES = 0.56) and cut (p = 0.001; ES = 0.8). However, the other results showed unclear differences between winning and losing teams (Table 4).

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Table 4. Action of the ball possessions counted per min, by comparing full game of the winning and losing teams.

Teams Variables of group Losing vs. winning teams First play action Winning Losing P - value ES (90% CI) Interpretation Hand off 0.4 ± 0.3 0.4 ± 0.2 P=0.898 -0.03 (-0.43; 0.35) Trivial P&R Screener 0.4 ± 0.2 0.2 ± 0.2 P<0.001 -0.98 (-1.39; -0.55) Moderate P&R Ball Handler 0.8 ± 0.3 0.7 ± 0.2 P=0.044 -0.49 (-0.92; -0.12) Small P&R skip pass 0.1 ± 0.1 0.0 ± 0.1 P=0.116 -0.38 (-0.81; -0.02) Small Off-screen 0.3 ± 0.2 0.4 ± 0.2 P=0.005 0.70 (0.30; 1.11) Moderate Cut 0.2 ± 0.1 0.3 ± 0.1 P=0.001 0.80 (0.49; 1.32) Moderate Teams Variables of Losing vs. winning teams Final play isolation action Winning Losing P - value ES (90% CI) Interpretation Post up 0.5 ± 0.3 0.9 ± 0.2 P<0.001 1.31 (0.88; 1.75) Large Penetration 1.2 ± 0.3 1.4 ± 0.4 P=0.022 0.56 (0.17; 0.97) Small Dribbling shot 0.9 ± 0.4 0.7 ± 0.2 P=0.043 -0.68 (-1.11; -0.30) Moderate Spot Up shot 0.6 ± 0.4 0.5 ± 0.3 P=0.606 -0.12 (-0.53; 0.25) Trivial Put back 0.1 ± 0.1 0.1 ± 0.1 P=0.573 -0.14 (-0.39; 0,39) Small Other 0.4 ± 0.4 0.3 ± 0.2 P=0.460 -0.18 (-0.57; 0.22) Small

Moreover, the results of the actions during first 5 min of the game are presented in table 5. The variables of the group actions showed statistically significant difference in the off-screen (p = 0.04; ES = -0.68). By comparing results between losing and winning teams in the final possession, the statistically significant difference and moderate effect size was discovered in dribbling shot (p = 0.04; ES = 0.68); cut (p = 0.04; ES = 0.77) and post-up situations (p = 0.02; ES = -0.76) (Table 5).

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Table 5. First and the last action of the ball possessions per min, during first 5 min of the game by comparing results of winning and losing teams.

Teams Variables of group Losing vs. winning teams First play action Winning Losing P - value ES (90% CI) Interpretation Hand off 0.5 ± 0.4 0.5 ± 0.2 P=0.418 -0.26 (-0.76; 0.28) Small P&R Screener 0.3 ± 0.3 0.3 ± 0.3 P=0.590 -0.17 (-0.67; 0.37) Trivial P&R Ball Handler 0.8 ± 0.5 0.7 ± 0.2 P=0.811 0.08 (-0.60; 0.44) Trivial P&R skip pass 0.1 ± 0.2 0.1 ± 0.1 P=0.494 -0.22 (-0.75; 0.30) Small Off-screen 0.2 ± 0.3 0.4 ± 0.3 P=0.038 0.68 (0.13; 1.20) Moderate Cut 0.2 ± 0.2 0.3 ± 0.2 P=0.086 -0.56 (0.05; 1.11) Small Teams Variables of Losing vs. winning teams Final play isolation action Winning Losing P - value ES (90% CI) Interpretation Post up 0.5 ± 0.5 0.8 ± 0.4 P=0.022 -0.76 (0.20; 1.28) Moderate Penetration 1.2 ± 0.4 1.4 ± 0.5 P=0.213 -0.40 (-0.13; 0.92) Small Dribbling shot 1.1 ± 0.7 0.7 ± 0.4 P=0.035 0.69 (-1.22; -0.15) Moderate Spot Up shot 0.6 ± 0.4 0.4 ± 0.3 P=0.159 0.45 (-0.97; 0.08) Small Put back 0.0 ± 0.1 0.1 ± 0.1 P=0.307 - Small Other 0.3 ± 0.3 0.5 ± 0.3 P=0.127 -0.49 (-0.02; 1.04) Small

Furthermore, the important results were the types of ball possession during the last minutes of the game (Table 6). By analyzing the results between losing and winning teams in the first action of possession, it was determined that P&R Screener situation had statistically significant differences and moderate effect size (p < 0.05; ES = -1.11). Moreover, the winning teams played more often in the entire P&R situations than losing teams. However, no statistically significant differences were found in the ends of ball possession by comparing the results of losing and winning teams (Table 6).

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Table 6. First and last action of the ball possessions during remaining 5 min of the game, by comparing results of winning and losing teams.

Teams Variables of group Losing vs. winning teams First play action Winning Losing P - value ES (90% CI) Interpretation Hand off 0.2 ± 0.2 0.3 ± 0.3 P=0.155 0.53 (-0.08; 1.14) Small P&R Screener 0.5 ± 0.4 0.1 ± 0.1 P=0.05 -1.11 (-1.75; -0.46) Moderate P&R Ball Handler 0.9 ± 0.1 0.7 ± 0.5 P=0.270 -0.41 (-1.02; 0.20) Small P&R skip pass 0.1 ± 0.1 0.0 ± 0.1 P=0.240 -0.44 (-1.04; 0.18) Small Off-screen 0.3 ± 0.3 0.4 ± 0.4 P=0.445 0.28 (-0.32; 0.88) Small Cut 0.2 ± 0.3 0.2 ± 0.1 P=0.841 0.07 (-0.53; 0.68) Trivial Teams Variables of Losing vs. winning teams Final play isolation action Winning Losing P - value ES (90% CI) Interpretation Post up 0.6 ± 0.3 0.8 ± 0.4 P=0.159 0.53 (0.09; 1.14) Small Penetration 1.1 ± 0.4 1.4 ± 0.6 P=0.134 0.56 (-0.06; 1.17) Small Dribbling shot 0.9 ± 0.4 0.7 ± 0.3 P=0.291 -0.39 (-1.00; 0.22) Small Spot Up shot 0.5 ± 0.6 0.6 ± 0.5 P=0.616 0.19 (-0.42; 0.79) Trivial Put back 0.1 ± 0.1 0 ± 0 P=0.031 -0.83 − Other 0.5 ± 0.5 0.3 ± 0.3 P=0.197 -0.48 (1.09; 0.13) Small

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4. CONSIDERATIONS

The aim of this study was to determine the differences between various types of outcomes (group or isolation), the zones of play (1-point zone or 2-point zones) and the types of the ball possessions by comparing results of winning and losing teams during the final day of 2020 world cup FIBA 3x3 basketball. All those outcomes and variables were classified into three groups according to analyzed duration of the game: full game; first 5 min and remaining time of the game. Game performance indicators in winning and losing teams during the season or a short-duration tournament were analyzed in previous investigations (Ibanez et al., 2003, 2009; Mikolajec et al., 2013; Conte et al., 2019). The scientists also investigated the differences of game style in different part of the game (Gomez, et al., 2013; 2015), regular and playoffs game (Garcia et al., 2013; Puente et al., 2015), close and balanced games (Sampaio & Janeira, 2003; Gomez et al., 2008; Csataljay et al., 2009; Lorenzo et al., 2010; Cene, 2018). The first part of hypothesis, which stated that the winning teams more often perform the group action, was confirmed. However, the second part of hypothesis was not verified, because the winning teams finished the attacks more in 2-point zone. The findings of outcomes showed large effect size and significantly different results of the possessions in the 1-point zone (p = 0.038; ES = 1.24). The winning teams finished the offense more at 2-point zone, while losing teams finished the offense more at 1-point zone. By comparing results of losing and winning teams, the research showed moderate ES of isolation action (ES = 0.85). The winning teams played more often in group actions while losing teams played more in isolation actions. However, according to research, it was determined that 1 on 1 situations were the most used offensive actions to be chosen by the coaches (Garefis, Xiromeritis, Tsitskaris, & Mexas, 2006). On the other hand, the group-tactical decisions enabled to create the optimal space-time for field-goal opportunities inside the paint (Gomez et al., 2013). According to literature, the isolation action was less effective in basketball than group action in both of the play zones (Matulaitis & Bietkis, 2021). The study findings of the crunch time in the NBA showed that plays of 1 on 1 were more static and had less variable action to finish the offensive, which let providing better possibilities of defenses to adapt to the offense play (Christmann, Akamphuber, Mullenbach, Gullich, 2018). The second hypothesis was confirmed because the winning teams dominate in all of the P&R actions. Furthermore, by analyzing the group action of the possession of winning teams during the full game, the statistically different results were obtained in: P&R screener (p < 0.001; ES = -0.98) and P&R ball handler (p = 0.044; ES = -0.49). Meanwhile, by analyzing the group action of the possession 24 of losing teams during the full game, the statistically significant different results were obtained in off- screen (p = 0.005; ES = 0.70) and cuts (p < 0.001; ES = 0.80). The statistical significant difference was obtained in the results of dribbling shot (p = 0.043; ES = -0.68) in the types of possession during the final actions of winning teams. Meanwhile, the results of losing teams indicated more performed actions in the post up (p < 0.001; ES = 1.31) and penetration (p = 0.022; ES = 0.56). In the recent study, it was determined that men teams mostly turn the ball over on offense when using P&R ball handler as an end other ball possession (Matulaitis & Bietkis, 2021). The teams also had lower success when they did not use screen and attacked more 1 on 1 situations (Remmert, 2003). In the other study it was determined that guards (point guard, shooting guard and small guard) used one on one situations facing the basket, while power forwards and centers often played back to the basket (Garafis et al., 2006). It is worth mentioning that FIBA 3x3 rules allow playing back to the basket just for 5 seconds, therefore this further complicates the application of this element to the game (FIBA. Rules, 2019). Furthermore, more positive ES of the types of the ball possession in the group actions was discovered and negative ES was estimated on the isolation action. However, the final action of winning teams was the offense with dribbling shot, while losing team usually performed post-up and cuts. If teams were ahead in score, the ball possession success enhanced the longer possession duration which generated the better field-goal selection and assists (Gomez et al., 2013). According the other study, it was discovered that the technical and tactical factors are significantly important when improving the ball possession effectiveness, and the stress accompanied by the pressure of the close game can be simulated during the preparation of the game (Gomez et al., 2016). The findings revealed that the players spent most time improving the screener/roller, the screen defender, and the free space between the players, before fixing other chosen options (Van Maarseveen, Savelsbergh, & Oudejans, 2018). A player capable of recognizing what was happening technically and tactically on the ground, was certainly more capable to make better decisions on the court than others and also in advance the intentions of the opponents. This put him in a position to choose which key to perform effectively in a given game situation (Altavilla & Raiola, 2014). The other important results were the differences between the types of ball possession during first 5 min and the remaining time of the game. The hypothesis was confirmed, which stated that both teams performed the similar number of variables of group and isolation actions. It was also confirmed that losing teams during the remaining time after the first 5 min of the game, performed more variables of isolation action, while winning teams continued to execute the variables of group action. The differences between the results could be impacted by: fatigue factor, fouls and the team results of the

25 game after first 5 min. The estimated ES indicated the moderate differences between dribbling shot (0.69) and post-up (-0.76) after the first 5 min of the game. Furthermore, no differences between ball possessions of the group action were noticed after 5 min of the game, which suggested that both teams played in similar style of basketball. According to literature, the men’s teams increased the probability of obtaining a successful ball possession with only one pass or no passes at all during the first five minutes of the game. This indicated that both teams were trying to be acquainted with the opponents weakness, and they used one-on-one situations and fast-breaks with only one pass more frequently, allowing them to receive a foul or score a basket (Fotinakis, Karipidis, & Taxildaris, 2002). According to the study of Malarranha, Figueira, Leite, & Sampaio, (2013), the research results of offensive and defensive ratings between winning and losing teams during the first 5 minutes of game showed no significant difference. However, in the remaining time of game, the results showed moderate ES difference between P&R screener (1.11) and post-up (-1). The winning teams in the second part of the game kept group actions play style until the end, while losing teams started to play more in isolation actions. The calculations of ball possession efficiency during the last five minutes of the game showed dependency on the number of players, the possession duration and number of passes (Gomez et al., 2013). The elite players had higher level of physical fitness, which allowed the player to make better decision during the game (Royal et al., 2006; Garcia et al., 2013). The study of Van Maarseveen and his colleagues (2018) determined, that in 3x3 basketball, the P&R action was the most frequently used in offensive play. Playing both on the left and right side of the court and facing three different types of defense (under, over, hedge), the ball carrier had to decide upon and perform one of four options: shooting at the basket, driving towards the basket followed by a lay-up, passing to the teammate who set the screen or passing to an additional teammate in the corner of the court. According Gomez and his partners (2013) study which investigated ball possessions, higher frequency of ball screens during the first 5min (50.0%), the middle 30 min (40.6%) and the last 5 min (36.7%) of the game that was reported. The results of Gomez et al., (2013) research found that coaches should prepare different game strategies such as screens on and off the ball to attack during the middle thirty minutes of games. The results of present study showed the importance of free-throw, especially during the last 5 minutes by comparing winning and losing teams (Malarranha et al., 2013). These findings suggested that coaches should create preparation plan to achieve a good free throw efficiency across the game, with special tasks in the last minutes, because these mentioned tasks were tended to be more important in influencing the shooting performance than fatigue factor (Malarranha et al., 2013). Is worth noting, that in FIBA 3x3 basketball the shot violation is 12 s and it is double less than traditional basketball. The

26 study of Matulaitis & Bietkis (2021) determined that the most efficient ball possessions were performed more than 10 s. The similar study of De Saa et al. (2013) identified that during close NBA games, ball possessions spent around 20 s for shooting during successful offensive. According to the Gomez and his colleagues (2013), men teams obtained more successful ball possessions when ball possessions ended in the paint and possession durations ranged between 0 – 20 s during the middle thirty minutes of the game. Moreover, the teams increased possession effectiveness by using no passes or four players or possession durations between 0 – 20 s during the last five minutes of the game (Gomez et al., 2013). During some moments of the game, the teams showed relative stability - free throws, field- goals. However, in other moments the teams were characterized by instability - turnovers or mistakes, when the opponent changed the defensive strategies, originating time-dependent dynamics that reflected team efforts to break or destabilize the opponents during each ball possession (Travassos, Davids, Araujo, & Esteves, 2013). Basketball has a lot of different situations, in which the players must make decisions in every possession and to make them by choosing independently within the system of play (defensive and offensive) based on the team system rules. Basketball is definitely a physical activity with sport skills, however the relation of mind theory on motor control and performance is the strictly connected (Altavilla & Raiola, 2014).

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CONCLUSIONS

1. According to the evaluation of the performance profile outcomes between winning and losing teams it was found that the winning teams performed more often in the group actions and executed that in 2-point zone. 2. By evaluating the types of ball possession during the full game according to different variables per minute, it was revealed that winning teams performed more often at P&R Screener, P&R ball handler and dribbling shot than losing teams. The losing teams also performed greater number at off-screen, cuts, post up and penetration. 3. By comparing the executed types of ball possession during the first 5 min of the game, it was noticed that the winning teams performed significant difference at dribbling shot. The situations of all types of P&R action showed no differences between the results of winning and losing teams. The losing teams played more often at off-screen, cut, post up. During the last 5 min of the game, a significant difference was found in the between P&R Screener and put back action, by comparing results of winning and losing teams.

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SUGGESTIONS

1. The results of the outcomes during the full game by comparing winning and losing teams showed that winning teams performed more often in 2-point zone and group actions. This indicated the importance of coach preparation plan, which has to include more teammates in to the offensive. It is also important to try punishing the opponents more in 2-point zone and to create prepared shots. 2. This study showed the most commonly performed types of the ball possession. The tactical training plans are recommended to be oriented in the first action to play more P&R screener or ball handler. It is also recommended trying to score more points from dribbling shot, penetration and avoid using too often the post up situation for the final play in the offensive. 3. The findings of this study during the first 5 min of the game were the most important because the players were the least affected by fatigue factor. The tactical training plan for the first part of the game is recommended to be oriented more for the final play, because the winning teams more often scored from dribbling and spot up shots, while losing teams used post up and penetration situations. The second part of the game – after the first 5 min since start – was usually the most important time of the game. It is recommended emphasizing to keep playing in group actions in the tactical plan for this period. The winning teams in this period played significantly more often in P&R screener. It is also important to noticed, that losing teams had significantly a smaller number of P&R screener, comparing with first 5 min of the game. The results of the final play showed, that losing teams finished attacks by using post up, penetration and spot up shots, while winning teams performed in dribbling shot and put back. The coach must notice the importance of put back, because the losing teams did not perform this action at all.

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