| Literature DB >> 32148591 |
Arturo Quílez Maimón1, Javier Courel-Ibáñez2, Francisco Javier Rojas Ruíz1.
Abstract
The aim of this study was to review and organise current literature about the basketball pass and find the main factors that influence its learning skills and performance. Thirty-seven studies were included after the screening process. The documents were classified into main research topics. This review identified the following conclusions: (i) the assessment of passing performance should be made under uncertain and variable conditions to obtain information on players' responses to competitive scenarios, (ii) it is advisable to incorporate new and random activities to facilitate the transference of learning to the competition, (iii) it is recommended to include overwhelming factors during the practice to minimise the effect of pressure and choking, (iv) optimal physical conditioning is essential to maintain passing performance during a basketball game, (v) small sided games and changing environments stand as the best training situations to improve passing skills. Furthermore, limited information is available about biomechanical aspects and physical conditioning training programs to improve passing skills in basketball. Likewise, there is sparse data on passing skills development in children.Entities:
Keywords: learning; skills; tactics; team sports; technique
Year: 2020 PMID: 32148591 PMCID: PMC7052720 DOI: 10.2478/hukin-2019-0088
Source DB: PubMed Journal: J Hum Kinet ISSN: 1640-5544 Impact factor: 2.193
Figure 1PRISMA flowchart illustrating research at each stage.
Summary of studies exploring the basketball pass (2002 to 2011)
| Year, 1st author | Area | Situation Game | Sample cohort and | Key Finding(s) |
|---|---|---|---|---|
| 2002, Perkos | Motor skills | Match | n = 62 novice players U14 (M) | - Efficacy of passing skills acquisition through an instructional self-talk |
| 2003, Iglesias | Performance Analysis Motor skills | Match | n = 12 players U15 (M) | - Training under real conditions improves success percentage and decision making in basketball pass. |
| 2006, Lyons | conditioning Physical Motor skills | Analytic | n = 20 players S (B) | - High intensity exercises improve players´ skills. |
| Performance Analysis | Match | n = 184 players U16 (M) | - Point guards make a higher number of passes than other positions. | |
| 2007, Bogdanis | Physical conditioning | SSG | n = 27 players U16 (B) | - Passing skills increased in a basketball regular drill context compared with a non-basketball drill context within physical conditioning aspects. |
| 2008, Coelho-e- Silva | Biomechanics | Match | n = 59 players U16 (B) | - Only height was positively correlated with passing skills |
| 2008, Gordon | Mental factor | Analytic | n = 18 players S (B) | - No difference between optimism/pessimism regarding self-efficacy. |
| Performance Analysis | Match | n = 145 S (records M) | - Assists are the best predictor of best teams. | |
| 2009, Delextrat | Physical conditioning | Match | n = 30 players S (F) | - Specific fitness and passing skills training must be undertaken according to the playing position. - Point guards pass significantly better than rest of positions. |
| 2009, Hill | Mental factor Motor skills | Match | n = 4 psychologists S (B) | - The player perceives that his resources are insufficient to meet the demands of the situation, what leads to choking. |
| Performance Analysis | Match | n = 223 games U20 (B) | - The main statistic was related to turnovers, so that winning teams had better pass skills than losing teams. | |
| 2010, Ortega | Motor skills | Match | n = 102 coaches U14 players (B) | - U14 Players need to devote more time to pass and progression than the rest of Basic Tactical Media Collective (BTMC) to achieve better performance |
| 2010, Porter | Motor skills | Analytic | n = 60 students S (B) | - A contextual interference program facilitates skill learning. |
| Performance Analysis | Match | n = 198 players S (M) | - Stronger teams were superior in terms of passes; important players made fewer errors at passing. |
S: Senior, U20: Under 20 years old, U18: Under 18 years old, etc; M = Male, F = Female, B = Both, Male and Female.
Summary of studies exploring the basketball pass (2012 to 2014)
| Year, 1st author | Area | Situation Game | Sample cohort and | Key Finding(s) |
|---|---|---|---|---|
| 2011, Izzo | Biomechanics | Match | n = 150 games U18 (M) | - Two handed chest pass is the most used (39,9%); one handed bouncing pass (11,2%) is the faster basketball pass. |
| 2012, Afsanepurak | Performance Analysis Motor skills | Match | n = 45 players U15 (M) | - Retention and transfer scores of the groups with contextual interference were significantly better. |
| 2012, Arias | Performance Analysis Motor skills | SSG | n = 54 players U11 (M) | - Reduction of ball mass (440 g) enabled the children to go from paying attention to ball to handling to aspects of game interpretation. |
| 2012, Nikolaos | Physical conditioning | Analytic | n = 26 players S (B) | - Improvement in players’ passing skills following the implementation of a balance and proprioception routine. |
| 2012, Shafe | Biomechanics | Match | n = 3 players U18 (M) | - Overthrown pass set as the best pass to execute in a fast break. |
| 2013, Ahmed | Physical conditioning | Analytic | n = 24 players U18 (M) | - Passing accuracy decrease when upper fatigue appears. |
| 2013, Conte | Motor skills | SSG | n = 21 players U11 (B) | - Passing skills are better acquired by performing an understanding education. |
| 2013, Courel- Ibáñez | Performance Analysis | Match | n = 1,324 possessions S (M) | - When inside pass is done, teams achieve a larger amount of points. - A passer location and immediate receiver action determinate a successful inside pass. |
| 2013, García | Performance Analysis | Match | n = 323 games S (M) | - Winning teams had a larger number of assists than losing teams. |
| 2013, Gómez | Performance Analysis | Match | n = 7,234 possessions S (M) | - Larger number of passes, is one of the main performance indicator in predicting effectiveness in basketball. |
| 2013, Sachanidi | Motor skills | Match | n = 33 players U16 (M) | - Passing efficiency in games could predict final performance of the athlete. |
| 2014, Tahmasebi | Motor skills | Analytic | n = 72 students S (B) | - Motivational self-task helps to improve precision in passing |
S: Senior, U20: Under 20 years old, U18: Under 18 years old, etc; M = Male, F = Female, B = Both, Male and Female).
Summary of studies exploring the basketball pass (2015 to 2017)
| Year, 1st author | Area | Game Situation | Sample and cohort | Key Finding(s) |
|---|---|---|---|---|
| 2015, Cárdenas | Performance Analysis | Match | n = 172 fast breaks S (M) | - Elite teams usually made maximum two passes (96.4%). - Fast break successfulness increased when the initial action was a pass. |
| Performance Analysis | SSG | n = 23 players U18 (M) | - No-dribble-game-drill condition elicited a greater physiological demand and a higher number of passes than the regular-drill one. | |
| 2015, Csapo | Performance Analysis | Match | n1 = 18 coaches n2 = 20 players S (M) | - Players selected "pass" regardless of the previous performance when they faced increased defensive pressure. |
| 2015, Galatti | Mental factor | Match | n = 7 players S (F) | - Excellent performance is directly related with tactic training and group cohesion. |
| 2015, Gómez | Mental factor | Match | n = 147 closed games S (B) | - Mental interventions should be undertaken during the last critical minutes to avoid negative consequences. |
| 2015, Kinrade | Mental factor | SSG | n = 38 players S (M) | - Ruminative thoughts lead to worse performance when making complex decisions under pressure. |
| 2016, Conte | Performance Analysis | SSG | n = 21 players U18(B) | - The 2 vs 2 condition showed a higher number of passes and a higher success ratio than 4 vs 4 condition. |
| 2016, Courel- Ibáñez | Performance Analysis | Match | n = 4,207 possessions S (M) | - Attacks including an inside pass were 1.4 to 2.0 times more effective. - A dynamic reception attitude from the weak side is suggested to enhance scoring options. |
| 2016, Jiménez | Motor skills | Match | n = 46 players U18 (F) | - Results support Contextual Interference (CI) effect in pass learning skill acquisition |
| 2016, Marmarinos | Performance Analysis | Match | n = 12,376 pick & rolls S (M) | - Pick and roll effectiveness could predict the final score. |
| 2017, Quílez | Biomechanics | Analytic | n = 10 players S (M) | - Uncertainty increases reaction time in basketball pass. |
S: Senior, U20: Under 20 years old, U18: Under 18 years old, etc; M = Male, F = Female, B = Both, Male and Female).