ArticleFrontiers in physiology2022
Pre-shot combinations and game-related statistics discriminating between winners and losers depending on the game location during the NBA COVID-19 season.
Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Winning beyond scoring: an explainable machine learning framework for identifying key performance indicators in the Chinese Basketball Association.BMC sports science, medicine & rehabilitation · 2026Article
- Article
- Inflammation in COVID-19 and the Effects of Non-Pharmacological Interventions during the Pandemic: A Review.International journal of molecular sciences · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Basketball in performance depends on numerous factors, where a stable trend was identified by winning teams with better performances in shooting effectiveness and rebounding. However, there is a need for a better understanding of pre-shot combinations that lead to these performance trends. This study aimed to analyze NBA teams' game-related statistics, pre-shooting combinations, and pick-and-roll differences between winning and losing teams (considering the context: playing at home, away, or in a neutral court) during the COVID-19 season. A retrospective cross-sectional study on the 2019-2020 NBA season (906 games) was carried out. Game-related statistics were gathered from the private company InStat (https://basketball.instatscout.com/). The discriminant analysis and binary logistic regression models were run in order to discriminate the most important features of winning teams depending on the game location. The results showed that defensive rebounds and three-point shooting percentage remained the most important variables that best discriminated winners and losers independently of the game location context. The main results showed that winning teams had a better shooting percentage based on three-pointers, catch-and-shot actions, cuts, pick-and-roll efficacy, and uncontested shots based on a better collective behavior after a successful space creation dynamic through a tactical functional unit. At the same time, teams would need players with the ability to clear those possessions in which the opponents force to an isolation or a contested shot. From a practical application perspective, coaches should focus on composing a team with good shooters, skilled players in isolations, and a good game-time pick-and-roll strategy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.