Differences in Using Step-Back Between Euroleague and NBA

LITHUANIAN SPORTS UNIVERSITY FACULTY OF SPORT BIOMEDICINE INTERNATIONAL MASTER’S IN PERFORMANCE ANALYSIS OF SPORTS

OVIDIJUS KOKANAUSKAS

Differences in using step-back between Euroleague and NBA.

FINAL MASTER’S THESIS

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CONFIRMATION OF INDEPENDENT COMPOSITION OF THE THESIS I hereby declare, that the present final Master’s thesis (entitlement): DIFFERENCES IN USING STEP-BACK BETWEEN EUROLEAGUE AND NBA. 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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2 TABLE OF CONTENTS INTRODUCTION ...... 6 1 LITERATURE REVIEW ...... 7 1.1 Basketball ...... 7 1.2 NBA and Euroleague differences ...... 7 1.3 Player positions ...... 8 1.4 Performance analysis ...... 9 1.5 Shooting action ...... 11 2 RESEARCH METHODOLOGY AND ORGANIZATION ...... 13 2.1 Research object ...... 13 2.2 Research strategy and logic ...... 13 2.3 The nature of research ...... 13 2.4 Contingent of research subjects...... 13 2.5 Research methods...... 13 2.6 Research organization ...... 14 2.7 Methods of statistical analysis...... 14 3 RESEARCH FINDINGS ...... 15 4 CONSIDERATIONS ...... 19 CONCLUSIONS ...... 23 SUGGESTIONS OR RECCOMENDATIONS ...... 24 REFERENCES ...... 25

3 ABSTRACT

Differences in using the step-back between Euroleague and NBA.

The aim of this study was to descriptively assess the step-back actions in Euroleague and NBA basketball leagues in 2018-2019 season, and to assess whether the contextual factors (players position, league, shot type, quarter, defenders’ position) are predictors of step-back effectiveness (successful/unsuccessful). Video analysis was the main research method of this investigation. Video footage of 2018-2019 basketball season, from 20 Euroleague and 20 NBA games (n=40) were randomly selected and analyzed. Contextual factor: players position (Guard, Forward, Center), league (Euroleague, NBA), shot type (2pt, 3pt), quarter (Q1, Q2, Q3, Q4) and defenders position (Guard, Forward, Center), were selected as the predictors of step-back effectiveness. The results of descriptive statistics showed that NBA players took 96 step backs and Euroleague players shot 65. From all players guards took the step-back shots most often: 73.8% out of all step-backs recorded in Euroleague, and 70.8% in NBA. On the other hand, forwards were the ones that had the highest accuracy (%) of step-backs: 52.9% in Euroleague and 54.2% in NBA. Out of the selected contextual factors, only statistically significant predictor that provides more possibility of a successful step-back shot was the 2nd quarter compared with the 4th quarter (p=0.019) [Odds ratio (95% CI) = 0.322 (0.125; 0828)].

Key words: basketball, performance analysis, professional leagues, contextual factors

4 SANTRAUKA

„Step-back“ metimo naudojimo skirtumai tarp Eurolygos ir NBA.

Šio tyrimo tikslas buvo apibūdinančiai įvertinti „step-back“ veiksmus Eurolygos ir NBA krepšinio lygose 2018–2019 metų sezone ir įvertinti, ar kontekstiniai veiksniai (žaidėjų pozicija, lyga, metimo tipas, kėlinys, gynėjo pozicija) nuspėja „step-back“ metimo efektyvumą (sėkmingas / nesėkmingas metimas). Vaizdo analizė buvo pagrindinis šio tyrimo metodas. Atsitiktiniu būdu buvo atrinkti ir išanalizuoti vaizdo įrašai iš 2018–2019 metų krepšinio sezono: 20 Eurolygos rungtynių ir 20 NBA rungtynių (n = 40). Kontekstinis veiksnys: žaidėjų pozicija (gynėja, puolėjas, centras), lyga (Eurolyga, NBA), metimo tipas (dvitaškis, tritaškis), kėlinys (Q1, Q2, Q3, Q4) ir gynėjo pozicija (gynėjas, puolėjas, centras) buvo pasirinkta kaip „step-back“ metimo efektyvumo prognozuotojai. Aprašomosios statistikos rezultatai parodė, kad NBA žaidėjai metė 96 metimus, o Eurolygos žaidėjai 65 metimus. Gynėjai dažniausiai atliko „step-back“ metimą: 73,8 proc. iš visų Eurolygoje užfiksuotų „step-back“ metimų ir 70,8 proc. iš NBA. Kita vertus, puolėjai buvo tie, kurie metė šiuos metimus tiksliausiai (%): 52,9% Eurolygoje ir 54,2% NBA. Vis dėlto, iš pasirinktų kontekstinių veiksnių vienintelis statistiškai reikšmingas prognozuojantis veiksnys, suteikiantis daugiau sėkmingo „step-back“ metimo galimybių, buvo antras (2) kėlinys, lyginant su ketvirtu (4) kėliniu (p = 0,019) [Odds ratio (95% CI) = 0,322 (0,125; 0828)].

Raktiniai žodžiai: krepšinis, sportinės veiklos analizė, profesionalios lygos, kontekstiniai faktoriai

5 INTRODUCTION

In recent years, analytics has started to revolutionize the game of basketball: quantitative analyses of the game inform team strategy, management of player health and fitness, and how teams draft, sign, and trade players (Terner & Franks, 2020). Statistical analyses allow coaches to evaluate the effectiveness of individual, group and team play. Identification of the strong and weak points of a team or an athlete, as well as the elements that need improvement, is the key to permanent progress in performance (Esteves, Mikolajec, Schelling, Sampaio, 2021; Gryko, Mikalajec, Maszczyk, Cao & Adamczyk, 2018). Game statistics provide us with only limited insight and no information about the technical aspects of the shots. The lack of directly related work is understandable, because data on the technical execution of basketball shots are not readily available. In recent years, there have been substantial advancements in automated player and ball tracking. Technology implemented in the NBA, is capable of (semi-)automated recognition of such technical elements as shot type and defensive spacing, and these data are already being used in research. For other technical aspects and basketball competitions other than the NBA, researchers currently have no choice but to manually collect the data by visually inspecting games (Erčulj & Štrumbelj, 2015). In order to improve their teams’ performance, coaches have to determine which factors most differentiate a successful team from an unsuccessful team in both, the Euroleague (Özmen, 2016) and the NBA (Dehesa et al., 2019). Shooting is probably the best-known fundamental skill in basketball – every player is interested in scoring (Krause & Nelson, 2018). Shot selection is also driven by situational factors, strategy, and the ability of a player’s teammates (Terner & Franks, 2020). The step- back or hop-back jump shot requires shooters to alter their jump-shot footwork, especially against excellent defenders, from a basket penetration move to set up the shot. The basket penetration move clears space for a jump shot, such as three-pointer. In order to create space from the defender and take a balanced shot, the shooter needs to develop advanced footwork and ballhandling skills (Krause & Nelson, 2018). It seems that step-back shot is getting more and more popular, however there is no research yet investigating this shot type. The aim of this study was to descriptively assess the step-back actions in Euroleague and NBA basketball leagues in 2018-2019 season, and to assess whether the contextual factors (players position, league, shot type, quarter, defenders’ position) are predictors of step-back effectiveness (successful/unsuccessful).

6 1 LITERATURE REVIEW

1.1 Basketball

Basketball is a court-based sport characterized by intermittent high intensity efforts (Conte et al., 2015; Conte, Tessitore, Smiley, Thomas & Favero, 2016). During basketball games, players are repeatedly required to perform rapid specific movements in association with unique technical actions according to specific tactics (Conte et al., 2015). Basketball is a team sport characterized by the execution of series of skills in multiple situations occurring across the game. In particular, game-related statistics are fundamental and their level might depend on the players’ characteristics and training experience (Lorenzo, Lorenzo, Conte & Gimenez, 2019). Coaches and scouts are constantly searching for better methods of player evaluation and basketball is no exception. There are many aspects of an elite player that an analyst must consider when performing their analysis: offensive and defensive ability, personality, among others. Often, players are subject to defensive pressure and the more skilled and experienced players might be able to anticipate events and perform unhurried actions as a result of their improved ability to “read the game” (Sampaio, Godoy & Feu, 2004). Many of these skills, especially those pertaining to offense and defense, can be quantified using statistical measures (Piette, Anand & Zhang, 2010).

1.2 NBA and Euroleague differences

The National Basketball Association (NBA) is consensually considered the most popular and competitive basketball league in the world. The competition is organized into two conferences and six divisions, with a regular season comprising 82 games for each team (Mateus et al., 2018). The National Basketball Association (NBA) is the most worldwide competitive basketball league. The competition is extremely congested requiring multidisciplinary approaches to provide accurate information about players and teams’ performance over the season. Therefore, contemporary basketball performance analysis demands from players and teams the combination of physical fitness profiles (Gonzalez, et al., 2013) with technical and tactical indicators (Mangine, et al., 2014) during the season. Basketball experts are unanimous that the National Basketball Association (NBA) league features most of the best players in the world and is where the highest level of basketball is played. However, most experts are also of the opinion that the differences between NBA teams and top European teams, most of which play in the Euroleague, arguably the second-best

7 competition, are decreasing. Games between NBA and European teams are few and far between, for promotional purposes and lacking competitiveness. Therefore, a direct comparison of teams’ or players’ performance and quality across competitions is difficult, in most cases based on expert opinion and often speculative. Comparisons are additionally complicated by non-negligible differences in rules, the most important being game duration, three-point shot arc distance, and three second violation in defense in the NBA (Mandic, Jakovljevic, Erčulj & Štrumbelj, 2019). The Euroleague is a high-level competition composed by the teams that won their domestic league and other top teams from the highly ranked national leagues, played in a tournament system that ends in a final four format. Alongside this competition, all participants compete in their respective national and/or international championships (i.e. national championships with teams from same country or international championships with teams from different geographic areas — Balkan Peninsula and the Adriatic Sea), which raises several management concerns and contrasting factors (such as game rules, schedule fixing, playing styles, opponents’ quality, familiarity towards game facilities, competitiveness, and psychosocial environment) where individual and teams performances may be affected (Pollard & Gomez, 2013; Gomez, Lorenzo, Ibanez & Sampaio, 2013; Sampaio, Lago, Casais & Leite, 2010). According to the international FIBA rules, the game of basketball is played between two teams, with 12 players on each team. The game is divided into two halves, each half consisting of two 10-minutes quarters, with a 2-minute break between quarters and a 15-minute half-time. In the NBA, the main distinction from the FIBA rules is that the quarter is played for 12 minutes, making the total game 8 minutes longer. The dimensions of a FIBA court are slightly smaller than that of the NBA. An NBA court measures in at 29.65 m x 15.24 m, while a FIBA court comes in at 28 m x 15 m. Also, the 3-point line distance to the basket is different: 6.75m (6.60 on baseline) in FIBA court and 7.24m (6.70 on baseline) in an NBA court. The live play is stopped once an incidence occurs, such as a foul, ball out-of-bounds or time-out. On average, despite the approximate 2-hour duration of the game, less than 50% of the total time is spent in live play (McInnes, Carlson, Jones & Mckenna, 1995). During the live play, five players of each team compete, while the other seven serve as no-limit substitutions.

1.3 Player positions

Due to the characteristics of the game, players of different anthropometry are specifically positioned on the court. Taller players are traditionally positioned closer to the basket and shorter players play on the perimeter. The guards (i.e. point guards and shooting

8 guards) are responsible for the ball control, offensive play coordination, and shooting from a long distance. The forwards (i.e. small forwards and power forwards) are in charge of both long- and short range shooting, whereas the small forwards often shoot from various positions, especially corners. On the other hand, the power forwards use their height and mass to play more aggressively, closer to the basket. Finally, the centers are the tallest players that mainly play very close to the basket (low-post plays) for close-range shots, while they play an important role in orchestrating the team in defense. Both the power forwards and the centers have important roles in catching defensive and offensive rebounds (Drinkwater, Pyne & McKenna, 2008). Radu (2015) described basketball positions as when on court, each player fulfils a specific role that is dictated by his or her position in the team and the area of court he or she is playing while on attack. This position is closely linked to the player’s physical make- up – in other words, their height – together with their specific skills and abilities. As a general rule, the taller a player is, the closer to the basket he or she plays. This position – called ‘pivot’ or ‘center’ or ‘post player’ – is usually filled by the tallest player in the team. They are also referred to as ‘position 5 players. At the other end of the height scale, the smallest players are called ‘guards’ and their area of action is away from the basket (quite frequently at the top of the 3-point semicircle); they are also known as ‘position 1’ or ‘position 2’ players. If a player’s height is fairly average, these players are asked to play ‘forward’ position (which is also referred to as ‘position 3’ or ‘position 4’ player).

1.4 Performance analysis

In the last decade, team sports have experienced an accelerating growth and evolution in technological developments (e.g., wearable, small, and inter-device connection), influencing the daily work from researchers to practitioners in the sports science area. Thanks to this development, new and specific tools have been created to use in team sports science and medicine that are safer, less invasive and with high validity and reliability (Rico-Gonzalez, Los Arcos, Rojas-Valverde, Clemente & Pino-Ortega, 2020; Verhagen, Clarsen & Bahr, 2014). The creation of these technological tools led to the development of different software to capture and analyze up to a thousand data per second in up to 400 variables after or in real-time from different dimensions (technical, tactical, conditional) (Bonomi, 2013). The analysis and interpretation of a large amount of data derived from new technological devices in a short time represent a supreme challenge to the team sports’ scientists (Rojas-Valverde, Gomez-Carmona, Gutierrez-Vargas & Pino-Ortega, 2019). These data sets or combinations of data sets must be managed as big data due to its volume, complexity, variability; that requires special data

9 management, processing and analysis (Costa, 2014). Sports performance is the expression of complex interactions between physiological fitness, psychological preparedness, physical development, biomechanical proficiency, and tactical awareness, amongst several others (Glazier, 2015). The performance analysis in team sports involves the exploration of different types of variables (technical, tactical, conditional), being a challenge to the realization of a modeling process that allows the global understanding of the team behavior. The application of sport science to basketball settings has recently grown, leading to an increased number of investigations quantifying the players’ technical and tactical demands during games (Lorenzo, Gomez, Ortega, Ibanez & Sampaio, 2010). Statistics in sports have been an important tool for coaches to evaluate the team and player sports performance (Hughes & Franks, 2004; Ortega, Villarejo & Palao, 2009; Leite, Baker & Sampaio, 2009; Oliver, 2005). Throughout the years of competitive basketball, numerous methods of game registration and analysis have been created, with the objective to precisely and objectively evaluate particular players and the whole team. These methods evolved from simple stat sheets, filled out by hand during the game by assistant coaches to fully computerized procedures that automatically register all of the significant variables of the game and calculate the necessary indices (Lorenzo et al., 2010 ; Oliver, 2005). Currently, basketball is one of the most analyzed sport disciplines. The analyses of the statistical reports allow coaches to evaluate the technical and tactical efficiency of players and teams, and to compare them during single game performance, as well as during the whole season. They also help players to develop basketball skills based on recorded factors (Gomez, Lorenzo, Sampaio & Ibanez, 2009; Gomez et al., 2010 ; Ibanez et al., 2008 ; Sampaio & Janeira, 2003 ; Oliver, 2005). More recent studies have been exploring contextual factors such as game location (home and away), game type (regular season and playoff), game final score differences (close, balanced and unbalanced games), players’ gender (men and women), level of competition (Euroleague, National Basketball Association, etc.) and age (senior and junior) to establish better understanding of performance analysis (Lorenzo, Gomez, Ortega, Ibanez & Sampaio, 2010). Most of the game related statistics depends on multifactorial variables (i.e., offensive and defensive tactics) determining a complex dynamic system during games, which is difficult to control in its totality. The use of performance analysis in sport with the determination of the most important game related statistics during the game aims to improve the team performance, increasing the knowledge of the performance of each player. Specifically, game-related statistics are key tools for basketball coaches providing reliable information about teams’ performance such as those distinguishing between successful and unsuccessful teams (Lorenzo et al., 2019). The decisions made by the coach when the score is

10 very close, particularly towards the end of the game, can win or lose basketball games. Choosing the best tactical intervention requires detailed domain knowledge regarding players’ strengths and weaknesses and probability assessments of success for different offensive and defensive strategies. Statistical evidence of player performances are routinely used to facilitate this tactical decision making but little is known about which factors discriminate success and failure during these crucial periods where there is very little difference in the scoring patterns of the two teams (Csataljay, James, Hughes & Dancs, 2012).

1.5 Shooting action

Arguably the most salient aspect of player performance is the ability to score. There are two key factors which drive scoring ability: the ability to selectively identify the highest value scoring options (shot selection) and the ability to make a shot, conditioned on an attempt (shot efficiency). A player’s shot attempts and his or her ability to make them are typically related. In Basketball on Paper, Dean Oliver proposes the notion of a “skill curve,” which roughly reflects the inverse relationship between a player’s shot volume and shot efficiency (Oliver, 2004, Skinner, 2010, Goldman & Rao, 2011). Goldsberry (2012; 2019) gain further insight into shooting behavior by visualizing how both player shot selection and efficiency vary spatially with a so-called “shot chart.”. Many of the authors emphasized the importance of 2-point shots (Choi, O’Donoghue & Hughes, 2006; Reano, Calvo & Toro, 2006a, 2006b; Ibanez, Garcia, Feu, Lorenzo & Sampaio, 2009; Lorenzo et al., 2010; Sampaio & Janeira, 2003) and 3-point shooting performance (Choi et al., 2006; Csataljay, O’Donoghue, Hughes & Dancs, 2009; Gomez et al., 2006a, 2006b; Ibanez et al., 2009) as distinguishing factors that contribute to successful team performance. The non-free-throw basketball shot (or field goal) is the primary way of scoring and one of the most frequent and important technical elements in competitive basketball (Hay, 1993). The shot is the game action in which the rest of the players' actions culminate, as it is the only action that allows them to achieve the goal of the game, to score. In this action, several factors intervene which condition its execution. Researchers analyze more variables than those that are collected in the traditional statistics of a game, such as technique, defensive pressure, previous actions, player position, etc. (Ibáñez, García, Cañadas, Parejo, & Feu, 2008; Ortega, Cárdenas, Sainz de Baranda & Palao 2006). In the game of basketball, the shot is the main action of the attacker; in fact, it is the instrument by which players translate them into points the offensive actions of own team (Raiola & Disanto, 2016). Players shoot using different techniques, the choice of which is influenced by several factors, such as distance, angle, player type, etc. In order to be an effective basketball shooter, a player must

11 be trained in choosing the appropriate technique and executing it. And, because practice time is limited, the techniques that have to be utilized more frequently in competition should be practised more frequently as well (Erčulj & Štrumbelj, 2015).

12 2 RESEARCH METHODOLOGY AND ORGANIZATION

2.1 Research object

Basketball step-back shot. 2.2 Research strategy and logic

Research strategy was to randomly select 40 games, 20 from Euroleague and 20 from NBA, to gather the step-back data. For randomization every game, that fits the selection criteria was assigned a number, and randomly selected using an online tool (https://numbergenerator.org). Last season, before the COVID-19 pandemic happened, was selected (2018-2019) for the data collection. Video analysis is one of the most common methods used to evaluate the performance of both the individual players and the teams during a competition (Hughes & Bartlett, 2002). In order to be an effective basketball shooter, a player must be trained in choosing the appropriate technique and executing it. And, because practice time is limited, the techniques that have to be utilized more frequently in competition should be practised more frequently as well. Therefore, as a first step towards improving the quality of the basketball training process, a better understanding of which basketball shot techniques are executed more frequently in competition and in which situations is required (Erčulj & Štrumbelj, 2015).

2.3 The nature of research

The nature of research is observational study. 2.4 Contingent of research subjects

A total of 40 games (n=40), 20 games from Euroleague and 20 NBA games were randomly selected and analyzed.

2.5 Research methods

Video analysis was the main research method of this investigation. Video footage of 2018-2019 basketball season was manually analyzed. In order to analyze more teams in both leagues, not more than 3 games were selected of the same team. Also, only close games, where the final score difference was 9 points or less (Lorenzo et al., 2010), were analyzed. No games with overtimes (when the score is tied after 4 quarters) were selected for this research. Contextual factor: players position (Guard, Forward, Center), league (Euroleague,

13 NBA), shot type (2pt, 3pt), quarter (Q1, Q2, Q3, Q4) and defenders position (Guard, Forward, Center), were selected as the predictors of step-back effectiveness.

2.6 Research organization

The experiment’s ethics approval was confirmed by the Lithuania Sports University ethics committee, Protocol No. SMTEK-4.

2.7 Methods of statistical analysis

Descriptive statistics was calculated for step-back action in Euroleague and NBA. Additionally, multivariate binary logistic regression was applied in order to find out whether the contextual factors (league, playing position, shot type, quarter and defenders position) can have an effect on the outcome of a step-back action (successful/unsuccessful shot). All analysis was performed using Jamovi (version 1.6) computer software, retrieved from https://www.jamovi.org. P-value was set at <0.05.

14 3 RESEARCH FINDINGS

30 Number of SB Numberof 20

0 Guards Forwards Centers

Euroleague NBA

Figure 1. Number of SB in Euroleague and NBA and by player positions (guards, forwards and centers). *Note: SB – step-back

The results of descriptive statistics showed that a total 65 step-backs in Euroleague and 96 step-backs in NBA were recorded. Out of 65 step-back shots taken in Euroleague, 48 (73.8% of all shots) were taken by guards, 17 (26.2% of all shots) by forwards and 0 by centers. In comparison in the NBA, out of 96 total step-back shots, guards shot 68 (70.8% of all shots), forwards 24 (25% of all shots) times and centers took 4 shots (4.2% of all) (Figure 1).

20 SB accuracy (%) accuracy SB

0 Guards Forwards Centers

Euroleague NBA

Figure 2. Step-back accuracy (%) by playing positions in Euroleague and NBA.

Guards were the least accurate shooting step-backs in both leagues and forwards did it most accurately also in both leagues. Guards made 39.6% of the step-back they shots, forwards – 52.9 in Euroleague. In NBA guards made 41.2% of their shots, forwards – 54.2% and centers 50% (Figure 2).

40 35 30 25 20

15 Number of SB Numberof 10 5 0 G F C G F C G F C Guards Forwards Centers

Euroleague NBA

Figure 3. Number of SB by player positions (G, F, C) divided according to the defending player position (G, F, C) in Euroleague and NBA. *Note: G – guard, F – Forward, C – center; SB – step-back

Out of 48 step-back shots taken by guards, 32 of them were taken against the same positions player on defense (guards), 11 against forwards and 5 against centers, in Euroleague. In NBA guards took 38 step-backs out of 68 against guards, 18 against forwards and 12 against centers. Out of 17 total step-backs forwards shot 1 against guards, 12 against forwards and 4 against centers in Euroleague. In NBA forwards took 4 out of 24 step-backs against guards, 18 against forwards and 2 against centers. There was no step-back recorded by center position player in Euroleague. On the other hand, in NBA centers took 2 step-backs against forwards and 2 against centers (Figure 3).

16 100 90 80 70 60 50 40 Number of SB Numberof 30 20 10 0 Euroleague NBA

2-point 3point

Figure 4. Number of 2-point and 3-point step-backs in Euroleague and NBA. *Note: SB – step-back

A total of 33 2-point and 33 3-point step-back shots were taken in Euroleague. In comparison, 40 2-point and 56 3-point step-backs were shot in NBA (Figure 4).

15 Number of SB Numberof 10

0 Q1 Q2 Q3 Q4

Euroleague NBA

Figure 5. Number of step-back shots in different quarters (1, 2, 3, 4) in Euroleague and NBA. *Note: SB – step-back; Q1 – 1st quarter; Q2 – 2nd quarter; Q3 – 3rd quarter; Q4 – 4th quarter

In Euroleague 11 step-back shots (16.9% out of all step-backs) the least out of all quarters, were taken in the 1st quarter. By contrary the most, 31 step-backs (32.3% out of all) were shot in the 1st quarter in the NBA. 17 step-back (26.2% out of all) shot in the 2nd quarter

17 in Euroleague. In NBA, in the 2nd quarter 21 step-backs were taken (21.9% out of all step- backs). The most step-backs – 20 (30.8% out of all) were shot in the 3rd quarter in the Euroleague. In NBA, in the 3rd quarter 21 step-backs were taken (21.9% out of all step-backs). In Euroleague 4th quarter – 17 step-backs (26.2% of all). In NBA 4th quarter – 23 step-backs (23.9% of all shots) were taken (Figure 5).

Table 1. Contextual factors as predictors of step-back (SB) effectiveness (successful vs. unsuccessful shot)

Predictor Estimate SE Z p Odds 95% Confidence ratio Interval Lower Upper Position: 2 - 1 -0,0999 0,46 -0,217 0,828 0,905 0,367 3,624 3 - 1 -0,1166 1,066 -0,109 0,913 0,89 0,11 7,187 Shot type: 3 -2 0,621 0,371 1,676 0,094 1,861 0,900 3,846 Quarter: 1 - 4 0,3992 0,476 0,838 0,402 1,491 0,586 3,791 2 - 4 -1,1341 0,482 -2,351 0,019* 0,322 0,125 0,828 3 - 4 1,19E- 0,466 2,66E- 1,000 1,000 0,401 2,492 04 04 Defenders position: 2 - 1 -0,4534 0,429 -1,058 0,290 0,635 0,274 1,472 3 - 1 0,0899 0,517 0,174 0,862 1,094 0,397 3,012 League: NBA - -0,2256 0,353 -0,638 0,523 0,798 0,399 1,595 Euroleague * indicates p=0.019

Results revealed that the only statistically significant predictor that provides more possibility of a successful step-back shot was the 2nd quarter compared with the 4th quarter (p=0.019) [Odds ratio (95% CI) = 0.322 (0.125; 0828)] (Figure 1).

18 4 CONSIDERATIONS

More step-back shots were recorded in NBA than in Euroleague. The main factors which influence sports results in the NBA indicated in the present study are much more connected with offense than defense (Mikolajec et al., 2013). Research findings can be partially explained due to a major difference is in game pace. Other authors highlight this as the most evident difference between the two competitions. European basketball is more tactical (and becoming even more), based on longer positional and tactical offense, while the NBA has shorter possessions, less emphasis defense and tactical play and, as a consequence, more turnovers, transition play and, some would argue, more attractive basketball for the average viewer. The number of possessions per game is significantly higher in the NBA. A difference in the number of possessions is expected, due to a longer quarter (12 minutes in the NBA versus 10 minutes in the Euroleague). However, the ratio 107.4 ± 0.3 (NBA) over 83.0 ± 0.4 (Euroleague) is approximately 130% and exceeds the expected 120%. That is, the difference cannot be accounted for only by differences in game length, which implies a faster pace in the NBA. Therefore, the pace of the game (even after adjusting for playing time) is quicker in the NBA (Mandic et al., 2019). Other authors found that a higher number of field goals made and missed by the NBA sub-group, also associated with a greater number of attempts. Therefore, players competing in the NBA have higher participation rates in offense, when compared to their Euroleague counterparts (Paulauskas, Masiulis, Vaquera, Figueira & Sampaio, 2018). The accuracy in shooting field-goals is a relevant factor to achieve success in a game, because these are variables that represent individual and collective offensive effectiveness (Garcia, Ibanez, De Santos, Leite & Sampaio, 2013; Malarranha, Figueira, Leite & Sampaio, 2013). The current results show a higher number of field goals made and missed by the NBA sub-group, also associated with a greater number of attempts. Therefore, players competing in the NBA have higher participation rates in offense, when compared to their Euroleague counterparts (Paulauskas et al., 2018). These findings by other authors justify the results of more frequent step-back shots in NBA than in Euroleague. In addition, the insights by dynamic and self-organized perspectives aiming to understand emergent behaviors (Bourbousson, Seve, & McGarry, 2010; Esteves, et al., 2016; Leite, et al., 2014) suggest that the entire basketball team’s behavior is widely depended on how a player interacts with his/her teammates, the opponents and the game context. Indeed, basketball may be the arduous game to characterize individual players’ performance, since each one is critically influenced by the other players on the court, of the own and opposing

19 team alike (Lutz, 2012). The physiological, tactical, and game-related indicators appear as examples of factors that are well related to the behavioral changes across game quarters (Gomez, Lorenzo, Ibanez, & Sampaio, 2013; Scanlan, et al., 2015). Also, it seems predictable that specific playing positions may provide dissimilarities in how the game and player interactions change over the course of time (Dehesa et al., 2019). Our research revealed that guards were the ones who shot the step-back shot most often out of all position players. Similar findings show that guards attempt more shots from long range than centres, especially three- point shots (Sampaio, Janeira, Ibanez & Lorenzo, 2006). Other authors state that, no doubt it is visible that guards are the leaders in shot and made three pointers, it could be because that guards are responsible to exploit the situations in the offence outside the three-point line, such as last seconds of the shot clock situations, in which a shot is inevitable (Miller & Barlett, 1996). Scoring three-point shots is the main offensive task given to perimeter players; that is, to point guards (Position 1), shooting guards (Position 2) and small forwards (Position 3) (Mikolajec et al., 2021). The results showed that 3-point step-back shots were more frequent both in Euroleague and especially in NBA, where the difference between 2-point and 3-point step-backs was even bigger. Increasement in 3-point shots in basketball, was also found by other authors. The presence of both mid-range shots and long-distance shots in the combination of variables with the highest effect on the game outcome in the EuroLeague indicates the importance of balanced positional effectiveness (Mikolajec et al, 2021). The possessions that no longer end in two-point attempts in the NBA are replaced by three-point attempts. Without changes to the three-point arc, the number of three-point attempts has almost doubled in the NBA in the observed period. This indicates a substantial shift in how the game is played in the NBA. A similar trend of more three-point shots is observable in the Euroleague as well but the magnitude is half smaller. The increased number of three-point attempts is due to fewer free- throw attempts as the number of two-point attempts was consistent throughout the period (Mandic et al., 2019). On the other hand, same authors also found that analysis of playoff data, however, reveals that NBA basketball becomes more similar to European basketball in the playoffs, which feature the best teams and a higher level of competitiveness. Authors argue that this is indirect evidence that NBA teams do not play at their highest level during the regular season, either to conserve strength or because winning is not the only imperative. However, once winning becomes more important, teams put more emphasis on tactical play and defence. This is something that European teams do more consistently, as there are no substantial differences between regular season and playoff games. Arguably, this could also be due to the

20 fact that teams play fewer games in the Euroleague and individual games are more important. However, decreasing structural and quantitative differences as observed through game statistics, do not imply that the absolute difference in quality has also decreased. The absolute quality is more difficult to measure directly. Indirect evidence from international competitions, where team USA typically dominates, implies that the difference between top NBA players and top European players is still substantial. Another indirect indicator of this is purely financial. NBA median salary is at the level of Euroleague star players and NBA stars earn 10 times more, not including sponsorships. Arguably, most Euroleague players that are good enough to play in the NBA end up playing in the NBA (Mandic et al., 2019). Results, revealing that 2nd quarter, when compared with the 4th quarter, could be a predictor of a successful step-back shot, are hard to reason. So far there were not any evidence why a particular quarter could lead to better scoring. Abdelkrim et al. (2007) reported that the first and third quarters of a men's basketball game were played at higher exercise intensity than the second and fourth quarters. The findings from Garcia et al. (2020) indicate that the physical match demands are different between game quarters and playing positions in professional basketball. However, these researches do not provide any justification, for the results regarding step-backs in different quarters. In any action of the game of basketball, both the attacker and the defender will never have certainty as to the mode of action of the opponent, the choices are always defensive and offensive will always be determined by the behavior of the opponent. Any player is able to see the game, but not everyone understands the various game situations, because knowing how to recognize the technical and tactical elements that develop during the phases of the game is a complex process that involves a series of actions cognitive and technical tactics interdependent among them. A player capable of recognizing what is happening technically and tactically on the ground, it is certainly more capable than others to understand in advance the intentions of the opponents; this puts him in a position to choose which key to play effectively perform in a given game situation. The elements, therefore, able to put players in a position to play well and be able to express an optimal sports performance are represented by the understanding of game situations, from being able to choose which fundamental and know how to perform well (Altavilla & Raiola, 2014). The advantage in major competitions lies with the teams displaying the highest level of shooting effectiveness (Mikalajec et al., 2021). In the game of basketball, the purpose of an offensive set is to generate a high-quality shot opportunity. Thus, a successful play ends with some player from the offensive team being given the opportunity to take a reasonably high-

21 percentage shot (Skinner, 2012). Having one or more players in field that they can realize high percentages of shots, brings a significant advantage at their team and disfavoring therefore, tactically and psychologically, the opponents complicating them defensive duties (Raiola & Tafuri, 2015). Seen through the lens of coaches, fans, and commentators, basketball is a complex sport that requires considerable analysis to understand and respond to its many nuances (Gabel & Redner, 2012). Numerical evaluation of basketball players has long been based on box score statistics. Such evaluations, by nature of the limited data set from which they draw, generally center around a player’s contributions to the five positive statistics—points, rebounds, assists, steals, and blocks—while neglecting more nuanced aspects of the player’s value, such as his/her ability to make high quality (non-assist) passes, or set good screens, or rotate effectively on defense. These less easily quantifiable aspects of a player’s performance are traditionally evaluated only qualitatively, informed by the intuition of a coach or analyst who has spent a significant amount of time watching the players perform (Skinner & Guy, 2015). Basketball is a game with complex spatio-temporal dynamics and strategies. With the availability of new sources of data, increasing computational capability, and methodological innovation, our ability to characterize these dynamics with statistical and machine learning models is improving. In line with these trends, it is believed that basketball analytics will continue to move away from a focus on box-score based metrics and towards models for inferring (latent) aspects of team and player performance from rich spatio-temporal data (Terner & Franks, 2020).

22 CONCLUSIONS

The aim of this study was to descriptively assess the step-back actions in Euroleague and NBA basketball leagues in 2018-2019 season, and to assess whether the contextual factors (players position, league, shot type, quarter, defenders’ position) are predictors of step-back effectiveness (successful/unsuccessful). To conclude, the results showed that NBA players use step-back shot more often than Euroleague players. Guards shot the step-back most out of all three position players. Step-back shot is most frequently used against the same position defender. In Euroleague players selected to shoot 2-point and 3-point step-backs almost identically, on the other hand 3-point step-back shots were more frequent than 2-point step- backs in NBA. Lowest number of step-backs were taken in the 1st quarter of Euroleague games, in contrary the most occurred in the NBA games. Finally, only the 2nd quarter compared with 4th quarter could predict a better possibility of an effective (successful) step-back shot.

23 SUGGESTIONS OR RECCOMENDATIONS

1. First suggestion would be to follow up on this research, and check to see if the step- back differences change in playoffs. Because there already is evidence, that NBA playoff basketball becomes more similar to the Euroleague basketball (Mandic et al., 2019). So further research regarding playoff data would be necessary. 2. Second suggestion would be to include situational variables in the research, to find out how they influence step-back. The effect of situational variables (shot location, transition/set, etc.) on shot types and shot success were found to be very similar (Erčulj & Štrumbelj, 2015). As was argued the game location is a key factor in elite basketball (Pollard and Gómez, 2013), but particularly it is quite evident in the NBA league (Jones, 2008). 3. For further step-back investigations, since it seems that this type of shot is getting more popular in nowadays basketball, would be interesting to see the transition of this shot, from youth basketball into professional basketball, and how it changes through the years.

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