The Impact of Rule Modifications on Elite Basketball Teams’ Performance

Interpretation of sports rules is a tool widely used by coaches in order to improve performance of their teams and athletes (Gracia et al., 2014; Hill-Haas et al., 2010). Sports rule modifications, such as in court dimensions or the number of active players, may cause an improvement in athletes’ physical conditioning (Cormery et al., 2008; Klusemann et al., 2012; Mikołajec et al., 2012), as well as technical (Delextrat and Martinez, 2014) and tactical skill levels (Sampaio and Maçãs, 2012). The effect of rule modification has always been associated with a variation in performance in different team sports (O'Donoghue, 2009). In particular, rule modifications have been associated with technical, tactical and strategic aspects of performance in competition (Pollard, 2008). From the performance analysis perspective, rule modifications allow analysts to recognise the nonlinear and unpredictable nature of team’s performance when facing these changes. The available research was uniform, highlighting the key performance indicators for winning a game that were mainly dependent on the quantity of field goals made and the defensive rebounds (Sampaio et al., 2015). Most of these studies analysed team’s performance in a specific season. However, they were not focused on a long-term period considering the persistence and consistency of the sport performance profiles (Shafizadeh et al., 2013).

Rule modifications in basketball have been useful to modify dynamics of the game over time (Pluta et al., 2014). These rule modifications, such as those implemented in training through small-sided games, cause adaptations on the part of the athletes and the appearance of new behaviours emerging from the new limitations (Silva et al., 2014). Specifically, rule modifications are necessary for the development of the sport. In particular, new rules allow matching the game to the current players’ demands, both physically and technically. For instance, the increase in the distance of the three-point line was implemented in order to stimulate development in players’ skills and technique (Pluta et al., 2014). Another modification was that due to the improvement in some athletes’ abilities and physical fitness, spaces were created within the paint called no-charge semicircles to avoid violent contact near the basket. Players are continually evolving physically, and athleticism is a characteristic of current defensive and offensive players (e.g., rough contact, aggressive defences and attacks close to the basket). If defensive players tried to occupy a space near the rim in the attacker’s trajectory in order to achieve an offensive foul, the contact would be violent and cause an injury. All of these modifications have caused changes in coaches’ strategies and tactics, as they design their training sessions according to the new regulations and the possible scenarios which might occur during games (García-Rubio et al., 2015).

In basketball, according to the International Basketball Federation (FIBA), rules are periodically and constantly evolving over time. The last important modification of the FIBA basketball rules took place during the 2010/11 season. Among others, the main modifications affected formal aspects of the game, such as the distance of the three-point line, and structural aspects, such as restarting the 24-s shot clock. Previously, during the 2000 season, changes were introduced which concerned the temporal aspects of the game, modifying the time for ball possession from 30 to 24 s, establishing four periods (i.e., quarters) instead of two (i.e., halves) and also changing the duration of these periods from 20 to 10 min each (Cormery et al., 2008). In basketball, rule modifications are oriented towards providing a more attractive game, in which teams could get more ball possession per game, attempt more shots, score more points and, by extension, put on a bigger show. This recent rule modification (2010-2011) in basketball has led to an increase in the number of ball possession and points scored per game, thus achieving the desired effect (Štrumbelj et al., 2013). In this regard, one of the elements that allows studying and recording possible changes in performance patterns are the team’s performance indicators (field-goal shots, rebounds, assists, etc.) from a long-term perspective.

To the best of our knowledge, there are no studies which analyse the evolution of basketball depending on the changes in the rules of the game and their relevance for performance indicators, minimising the effect of situational variables. Likewise, in some sports like basketball, there are some competitions in which the effect of playing as the local team is reduced to its minimal expression. An example of the great international relevance of this type of competition in FIBA basketball is the Copa Del Rey in the Spanish league. In this competition, only the best-qualified teams at the end of the first round of the ACB league regular season (teams with a similar competitive level according to Pluta et al., 2014) participate, and they play on neutral courts in just one eliminatory game.

Taking the aforementioned issues into account, the objectives of this study were i) to characterise and identify the technical-tactical performance indicators which discriminated the effect of rule modifications, and ii) to analyse the persistence of these indicators according to rule modifications over time. This study had two hypotheses. The first was that technical-tactical performance indicators have evolved according to the rule modifications and the second ii) that performance indicators may show persistence over the different seasons.

Means and standard deviations for each rule change are presented in Table 1. The results display, for instance, that the regulation in which more three-point shots were made and attempted was the one where the three-point line was further away (R2011); that the number of ball possession slightly increased throughout the 20 seasons; or that more two-point shots were made and attempted with the initial regulations. ANOVA results along with the Bonferroni post-hoc correction are presented in Table 2. The data display significant differences among regulations in almost all technical-tactical performance indicators, except for points scored, offensive rebounds, three-point percentage, and received and performed blocks. The R1996 and R2011 regulations showed the most differences between them, being the most distanced in time, followed by differences between R2001 and R2011.

Discriminant analysis revealed two statistically significant functions. The first function explained 66% of the variance (Correlation Coefficient = .64), while the second discriminant function explained 34% of the variance (Correlation Coefficient = .51) (Table 1). Structural coefficients of the first discriminant function allowed identification of the two-point shots (SC = .35), three point field goals made (SC = .30) and attempted (SC = .36), one point field goals made (SC = .33) and attempted (SC = .44). The second discriminant reflected the importance of two-point field goals made (SC = .43) and attempted (SC = .41), ball turnovers (SC = .40), ball steals (SC = .36), and received (SC = .34) and committed (SC = .31) fouls. The obtained discriminant functions correctly classified 70% of the cases. Centroids indicated, for function 1, that positive values were associated with the third group of rule periods (R2011), while negative values were related to the base rule period (R1995). The second rule period (R2001) was located in the central area. In the discriminant function 2, periods R1995 and R2011 obtained positive values, while rule period R2001 showed negative values. It seems clear that the discriminant function 2, as differences between rule periods R1995 and R2011 have already been explained, established the differences between rule period R2001 and the rest.

Figure 1 depicts the distribution map of all cases according to the groups of rule periods, created in the space of the two functions. It can be observed that games pertaining to rule period R2001 had better scores in function 2, whereas rule periods R1995 and R2011 had better scores in function 1.

Figure 1

Figure 2 displays the evolution of the number of ball possession, scored points and point differences between the analysed seasons and the associated trend lines. It can be seen how rule modification had an acute effect on the analysed variables, but decreased over time. Additionally, trend lines show that both the number of ball possession and point difference presented a positive tendency, but achieved points decreased over time. This information is completed with that obtained from the analysis of the autocorrelation and the cross-correlation between the discriminant technical-tactical performance indicators according to the modification of ball possession rules (Table 3). In the autocorrelation function, positive autocorrelations were observed in all technical-tactical performance indicators analysed, and they were only significant in ball possession, points scored, two-point field goals made, three-point field goals made and attempted, free throws attempted, and committed fouls. The values do not display stable persistence over time, except for the case of the number of ball possession. Cross-correlation results of ball possession with the rest of the analysed technical-tactical performance indicators display positive correlations for scored points, three-point shots attempted, free throws attempted, steals and turnovers.

Figure 2

The aim of this research was to identify performance indicators that best discriminated among periods of rule changes in basketball and their effects during the period analysed. In this regard, the results display differences in the number of ball possession and an increase of the game pace over the last few years, but points scored did not increase during the analysed time periods. Results allow to partially support the hypothesis that rule modifications generate changes in teams’ performance measured using game statistics. Regarding the evolution of basketball, this sport has changed during the last 20 seasons of the professional Spanish league (ACB League), where 3 periods of time with substantial rule modifications have taken place, all of them with the objective of making a more dynamic, attractive, spectacular and pleasing sport, which could increase both the number of spectators and its popularity (Pluta et al., 2014).

Statistically significant differences have been found between primary technical-tactical performance indicators over time. Nevertheless, technical-tactical performance indicators which maximise the differences between each rule period are scarce. One of the objectives of rule modification is to increase the game pace and therefore, to speed up offensive play in order to increase viewership. This intended objective was not found in the present study, as the aforementioned performance indicators did not discriminate between the analysed periods. For this reason, a complementary analysis was conducted in order to study the persistence of the technical-tactical performance indicators through the changes produced in the regulations, as well as the association of the indicators with the number of ball possession situations over time.

The first rule modification (R2001) characterised the game with a greater number of steals and turnovers, the lowest number of tried and successful two-point shots, as well as an increment in fouls. Steals are an indicator of defensive pressure normally performed by perimeter players (Sampaio et al., 2006). Likewise, this defensive pressure may force attacking players to engage in unnecessary dribbling or bad passes, thus attaining more steals (Ibáñez et al., 2008) or turnovers. In this regard, it has been demonstrated that the more physically fit players can intensify defensive pressure, increasing the chances of steals and turnovers from the opposing team (Dežman et al., 2001). Nevertheless, steals and turnovers decreased following the last rule modification, whereas players have improved their physical and tactical profiles due to a better formative process during training and the rule modifications generating an adaptation of the athletes to game demands (Cormery et al., 2008). This abrupt reversal in the number of steals and turnovers can be explained by the modifications in referee’s criteria (Štrumbelj et al., 2013). In the evolution from regulation period R2001 to R2011, the dimensions of the playing field were modified. In the R2001 period, the three-point line was closer to the basket than in R2011. The effective game space was smaller, making passing more difficult, defensive help was faster thus increasing the number of steals and turnovers compared to R2011. In the next regulation evolution, effective game space was increased as the three-point line moved further away from the basket, which also may explain (referee´s criteria) the lower number of turnovers and steals.

In the current period of the game, R2011, the three-point line moved further away from the basket. This change was motivated by the increase in the use of the 3-point field goal (25.24 vs. 30.65) (Štrumbelj et al., 2013). The balance between the inside and outside game in basketball in order to select a shot, along with the existence of more physical outside players, generate more advantages in three-point shooting (Mavridis et al., 2003). However, the separation of the three-point line has paradoxically induced a slight increment in the use and efficacy (made shots/attempted shots) of this type of a shot. Players have specialised in this type of a shot and are capable to perform successfully in the game (Štrumbelj et al., 2013) as they have developed greater mastery of basketball techniques, skills and decision-making (Pluta et al., 2014). This demonstrates that the game has a greater athletic component in order to generate better passing lines and 1-on-1 actions, which produce mismatches (Erčulj and Štrumbelj, 2015; Skinner, 2012). The increase in the distance of the three-point shot has not been sufficient to diminish the efficacy percentages; in fact, coaches are aware of the importance of precision in this type of shooting, which along with two-point shots, has been one of the most important predictors of victory in the ACB league for 10 seasons (20032013) (Puente et al., 2015). On the other hand, because of the extra effective game space, pressure defence has diminished at the time of performing a shot, as defensive players have to cover more play areas. Three-point shooting defence demands a greater distance to be covered, and thus, higher energy consumption (Erčulj and Štrumbelj, 2015; Ibáñez et al., 2009; Reilly, 1997). As pressure defence decreases, shot efficacy increases (Ibáñez et al., 2009).

A decrease in attempted free throws has been identified throughout the analysed time periods. During the R2001 period, there was a modification of the temporal structure of the game, changing from two 20 min periods to four 10 min periods of play. This modification of the regulations affects the moment at which free throws are performed due to an accumulation of personal fouls, starting from the seventh to the fourth personal foul. The aforementioned rule modification allows teams to increase their pressure defence, commit one extra foul (4+4) without the risk of sending the opponent to the free-throw line. Expert coaches are aware of these circumstances and exploit the opportunities provided by the regulations in order to score points and to break the game pace (Štrumbelj et al., 2013). Also, players have adapted to the new rules, committing less personal fouls than before (Štrumbelj et al., 2013).

The technical-tactical performance indicator which displays the strongest persistence throughout the analysed seasons was the number of ball possession situations. Although the specialised literature shows that the best teams play with a smaller number of possession situations (Ibáñez et al., 2003, 2008), the rules seek to evolve towards a faster game pace. Additionally, coaches seek to reduce the game pace during the most important matches, like qualifications for the finals or a match that would have a direct impact on the future of the team (García et al., 2013; Sampaio and Janeira, 2003). The Copa Del Rey championship has a single-elimination format, in which coaches risk less and have better control of the game pace. In fact, results show that when the game pace increases, the number of turnovers also increases significantly. It has also been demonstrated that when the game pace is higher, inaccuracies keep increasing, thus incrementing the number of steals and fouls committed (Sampaio et al., 2010). Due to this, those teams with better physical and tactical preparation, such as in the NBA, impose a very fast game pace with the aim of obtaining a high score advantage during the first half of the match (Sampaio et al., 2010). Nevertheless, in European league single-elimination games, where teams might be ruled out of the competition, teams decide on a slower game pace. Additionally, the increment in the number of two- and three-point shots when the pace is increased does not modify the success percentage of the aforementioned shots.

Through the analysis of performance in basketball, coaches can obtain valid and reliable information regarding their own teams, their opponents, and, in this case, the competition. In this study, significant differences were found in some of the technical-tactical performance indicators among the different rule changes. Thus, a reflective analysis about the modifications of game conditions that the rule change implies should be mandatory (Pluta et al., 2014) in order to validate it. In this sense, according to the ecological systems theory, sports performance is an adaptive process between players and teams in time and space (Travassos et al., 2013). To modify the structural elements of the game regulations, such as temporal or spatial aspects, without establishing measures which modify the interaction between players and teams with functional elements, space and time (Grehaigne et al., 1997), teams must conduct those adaptations which best serve their objectives. These modifications change the players’ behaviours in a different manner, as they are the ones who adapt their behaviours and decisions in function of their own expertise, skills, and opponents (Arias et al., 2011). Regulation evolution modifies the structural rules of basketball; nevertheless, players and coaches are the ones who determine functional behaviour in basketball — in other words, the way in which they use the structural rules in order to connect themselves with the field, the game time, opponents and teammates (Arias et al., 2011). Coaches should use these findings to i) create different training scenarios, ii) manage the functional behaviours of players with the structural rules, and iii) take advantage of being aware of rule modifications and the strategies affected.

Finally, there are some limitations that should be addressed in future research. Static analysis simplifies the information into its elementary components using the final game-related statistics. Therefore, future research should be controlled for technical, tactical and physical information, such as series of discrete events, physical performances and the interactions affected by the quality of the opposition.