Extending Behavior Analysis to Sports: Using Precision Teaching and Fluency Building to Advance Basketball Skills

The following is based on research presented at the 45th Annual Association for Behavior Analysis International in Chicago, IL, by Wesley J. Lowery, Natalie Parks, Kirk Kirby, Rick Kubina, and Beverly Kirby, Team ABA LLC

Introduction

Youth sports are a great way to keep children healthy, active, and to increase the opportunities for socialization with age appropriate peers. Families have shown an increase of interest in helping their children develop their skills as athletes within youth sports. Because of this trend, youth sports academies, sport camps, private lessons, and organized sports have increased across a variety of sports and skill levels. One of the toughest challenges that families or coaches face is the efficacy of the practice time. Rashall (1975) gathered data across a variety of sports showing that much of a player’s time during team practice is spent on activities that do not help improve the player’s performance. For example, the majority of the practice time is spent waiting in line during drills, listening to instruction, transitioning, talking amongst themselves while waiting their turn, or listening to feedback that is directed for another player. In fact, it is estimated that only 30% of team practice is spent building the player’s specific skills. Families and coaches are beginning to look for strategies that will not only make practices more efficient, but also for ways to improvement athletic performance in shorter amounts of time.

Early research in behavior analysis that targeted athletes evaluated the effects of reinforcement and descriptive feedback with athletes.  Komaki (1977) evaluated the effects of a descriptive feedback and frequent contingent reinforcement in the form of recognition and feedback for desired play execution for five pop warner football players. The results showed a 20% increase in three of the five players suggesting that behavioral specification and reinforcement contingency of desired play execution is an effective approach to coaching.   Furthermore, Stokes (2010) evaluating the effects of multiple coaching strategies which included performance feedback with and without video modeling, and training using acoustical guidance (TAG) for pass blocking for five high school varsity football players.  The results showed that feedback with video model improved the player’s performance; however, TAG was consistently the most effective coaching strategies for each of the player. This study suggests that the immediacy of the feedback from TAG may have influenced the execution of the target behavior. Also, TAG may have influenced performance by providing reinforcement for the precursor behaviors in the blocking behavior chain.

Related to basketball, Kladopoulos and McComas (2001) evaluated the effects of instruction and feedback across three NCAA Division II college basketball players. The dependent measures evaluated were proper form shooting and made foul shots. During intervention, the coach reviewed the description of proper form and the player was required to take ten practice shots. Descriptive praise was provided for proper form and no corrective feedback was given for incorrect form. The results showed that each player improved in proper form of foul shots. However, two of the three players showed consistent improvement in made foul shots with proper form. These results suggest that specific training and feedback influenced improvement in proper form and performance.

The purpose of the current study was to evaluate the effects of behavior fluency training along with precision teaching to increase the accuracy and fluency of free throw shooting with four high school varsity basketball players. Training a behavior to fluency is commonly described as a mastered task, easy to perform, complete skill without thought or hesitation, or second nature. Binder (1996) discusses behavior fluency as the combination of accuracy plus speed with an individual performing a skill within their natural environment. In other words, training completing the skill without thought or hesitation. During this study, the researchers introduced precision teaching to evaluate and monitor the player performance. 

Method

Participants. Participants included four males who attended the local high school. Each participant played basketball for at least 4 years and was enrolled in the high school basketball program. Two participants were sophomores, one was a junior, and one was a senior. Participants were selected based on their volunteering to participate in the study.

Setting. All sessions took place in one of 3 gyms at a local high school. One gym was the main gym, which was surrounded by bleachers one floor above the gym. The other two gyms were also full court, but did not have any seats or bleachers. Each practice session took place on half of one of the three courts in the high school.

Materials. During each practice session, the following materials were used by the basketball players: 1 ball rack, 8-12 basketballs, ½ of a basketball court. Researchers used a timer, pencil and paper data collection, a video camera, a whistle, and two counters for each behavior that was measured.

Dependent Variables. Two dependent variables were measured during this study. First, rate of acceleration was measured to determine the rate of improvement of foul shooting. Next, the rate of deceleration was measured to determine the deterioration of foul shooting. 

Treatment Conditions

BST Peer Training. Before fluency practice begin, the instructors taught and reviewed the Behavior Skill Training Model (BST) with the players to provide feedback to each other. The players were instructed to provide corrective feedback along with praise for correct form. The players were then shown a model of someone providing feedback to a player and finally were asked to provide the feedback themselves. Each player was provided feedback about the feedback they provided a player until mastery was achieved.

First Condition. During the first condition of fluency practices, each player completed three 30-second focused practice sessions of shooting foul shots. Each player was told at the beginning of each practice session to shoot as many free throws as possible while trying to be as accurate as possible. At the end of the 30 seconds, the player received feedback from a trained peer or instructor. This pattern was repeated until three 30-second focused practice sessions were complete. Data were collected on the number of shots that went into the basket and the number of shots that did not go into the basket. These data were then graphed on a standard celebration chart.

Second Condition. The second condition of fluency practices was exactly the same as the first condition except players completed five rounds of focused practice sessions instead of three. Players were also assigned weekly acceleration aims at a X1.25 acceleration. These aims were reviewed with each of the player before the fluency practice by the instructor stating the number of shots, they should make within the 30 seconds.

Third condition: Endurance and Accuracy Training (Marker Training). In this condition, players completed three 30-second focused practice sessions and received feedback immediately following the completion of the focused practice session. Following feedback, they shot a basketball at a marker on the wall as fast as they could for 30 seconds. After this, they returned to the 30-second focused practice session.

Results

Tremain. During the phase one, Tremain averaged 11 made shots during the first round, 10 made shots during the last round, and averaged 14 made shots for his best performance with an acceleration of x1.07 and a deceleration of x1.04.  During the phase two, Tremain averaged 11 made shots in the first round, 18 made shots during the last round, average 20 made shots for best performance, with an acceleration of ÷1.51 and a deceleration of x1.26. During phase three, Tremain averaged 13 made shots during the first round, averaged 9 made shots during the last round, average 14 made shots for his best performance with an acceleration of ÷1.17 and deceleration of x1.66.

Benjamin. During phase one, Benjamin averaged 13 made shots during the first rounds, 15 made shots for the last round, and averaged 17 made shots for best performance with performed at an acceleration rate of x1.04 and a deceleration rate of ÷1.06. During phase two, Benjamin averaged 16 made shots in the first round, averaged 15 made shots in the last round and averaged 20 made shots for best performance with an acceleration of x1.02 and deceleration of ÷1.07  During phase three, Benjamin averaged 18 made shots during the first round, averaged 19 made shots in the last round, and averaged 19 made shots for best performance with an acceleration of x1.26 and deceleration of x1.37  Limited data were collected for the second phase to determine an acceleration and deceleration. During the third condition, Benjamin performed at an acceleration rate of x1.01 and a deceleration rate of x1.04.

Jason. During phase one, Jason averaged 12 made shots during the first round, averaged 14 made shots during the last round, average 17 made shots for best performance with an acceleration rate of x1.07 and a deceleration rate of ÷1.01. During Phase two, Jason averaged 17 made shots for the first round, averaged 16 made shots for the last final, and averaged 21 for best performance with an acceleration of x1.14 and deceleration of ÷1.01. For phase three, Jason averaged 14 made shots during the first round, averaged 15 made shots during the last round, and averaged 16 made shots for best performance with an acceleration of x1.52 and a deceleration of x1.

Quay. During phase one, Quay average 13 made shots for the first round, averaged 12 made shots for the last round, averaged 15 made shots for best performance with and acceleration of ÷1 and deceleration of ÷1.04. During the phase two, Quay averaged 11 made shots for the first round, averaged 12 made shots for the last round, averaged 16 made shots for best performance with an acceleration of x1.14 and deceleration of ÷1.1. Quay did not participate in phase three.

Table 1. Acceleration and Deceleration performance for players across each phase.

Discussion

The results from this research show that fluency training with athletes has great potential at increasing player performance. Overall, each player’s shot accuracy and fluency improved over the course of the project, with the most accelerated results observe in Phase 2. One anecdotal observation was that players seemed to fatigue over time, effecting their overall accuracy and fluency. As a result, it may be beneficial to train both in fluency of the specific skill as well as endurance to prevent fatigue over time. Endurance training was implemented for 3 of the 4 participants in phase three of the study and results indicated that 2 of the 3 athletes continued to improve in their accuracy. However, due to limited time, additional data should be gathered to explore the effects of endurance training along with skill fluency training. .

There are a few limitations of this study. First, the amount of time spent in phase 3 of the study was limited. Further research should be conducted to fully examine the effects of fatigue and endurance training on the overall fluency of specific skills. Additionally, the research on how to set acceleration aims is limited to academic skills and it is unknown if the aims that were set were realistic. Additional data should be collected to determine fluent levels of each skill at each playing level in a sport. A third limitation of the study is the limited time the researchers spent with the players. Sessions took place after practice and could not be expanded due to the limited time. The sessions were also interrupted by games, snow days, and cancelled practices for the team. These interruptions to practices could have impacted the rate at which players improved. Further investigation of the frequency of sessions necessary to make maximum progress should be conducted. Finally, the players did not spend much time learning the BST model to provide feedback to one another. This led to spending more time between each practice session reviewing feedback with the target player than completing fluency drills.

Overall this type of training is beneficial for all levels of athletes. It is beneficial for athletes that perform at a high level of competition. Top recruit athletes who are able to perform the most difficult skills with fluency will give them the edge over their competitors. On the inverse, players that may not have the “it” factor will be able to develop a specific skill and become a top recruit for the one skill (e.g., superior ball handler, sharp shooter corner specialist, or lock down defender).

References

Binder, C. (1996). Behavioral Fluency: Evolution of a New Paradigm. The Behavior Analyst,19(2), 163-197. doi:10.1007/bf03393163

Kladopoulos, C. N., & Mccomas, J. J. (2001). The effects of form training on foul-shooting performance in members of a womens college basketball team. Journal of Applied Behavior Analysis,34(3), 329-332. doi:10.1901/jaba.2001.34-329

Lindsley, O. R. (1992). Precision teaching: Discoveries and effects. Journal of Applied Behavior Analysis,25(1), 51-57. doi:10.1901/jaba.1992.25-51

Mckenzie, T. L., & Rushall, B. S. (1974). Effects of self-recording on attendance and performance in a competitive swimming training environment. Journal of Applied Behavior Analysis,7(2), 199-206. doi:10.1901/jaba.1974.7-199

Obrien, F., & Azrin, N. H. (1970). Behavioral engineering: Control of posture by informational feedback1. Journal of Applied Behavior Analysis,3(4), 235-240. doi:10.1901/jaba.1970.3-235

Organized sports not enough to fulfill activity requirements. (2017, May 23). Retrieved from http://www.sciencedaily.com/releases/2017/05/170523095422.htm

Rushall, B. S., & Pettinger, J. (1969). An Evaluation of the Effect of Various Reinforcers used as Motivators in Swimming. Research Quarterly. American Association for Health, Physical Education and Recreation,40(3), 540-545. doi:10.1080/10671188.1969.10614875

Wes Lowery MS, BCBA www.TeamABAllc.com

Earning both a Bachelor of Science and then a Master of Science degree at the University of North Texas, he co-founded Behaviorist Uniting for Health & Fitness, (BUHF) an innovative research lab during his final graduate year under the guidance of Dr. Jon Pinkston. He further supplemented his formal training to become a supervising Board-Certified Behavioral Analyst, creating and managing teams providing a broad range of services for families throughout Texas. During this time, pushing the limits of what he learned, then adding a passion for improving the health of children at risk of obesity, as well as working to improve athletic performance through behavioral modification to unleash the full potential of people of all ages in all walks of life.