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Record W3158202483 · doi:10.1093/sleep/zsab072.294

295 Impacts of travel distance and travel direction on back-to-back games in the National Basketball Association (NBA)

2021· article· en· W3158202483 on OpenAlexaff
Jonathan Charest, Charles Samuels, Célyne Bastien, Doug Lawson, Michael A. Grandner

Bibliographic record

VenueSLEEP · 2021
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsUniversité LavalCanadian Sleep & Circadian Network
Fundersnot available
KeywordsBasketballBack musclesAdvertisingAssociation (psychology)Sequence (biology)GeographyDemographyPsychologyDemographic economicsBusinessMedicinePhysical therapySociologyEconomics

Abstract

fetched live from OpenAlex

Abstract Introduction Travel fatigue and circadian disruptions are known factors that can hinder performance in professional athletes. The present exploratory study focused on investigating the impact of travel distance and direction on back-to-back games over the 2013–2020 seasons in the National Basketball Association (NBA). Methods Data from away and home games of back-to-back sequences, in two different cities, from the 2013 to 2020 seasons in the National Basketball Association were included in this study. Information from every selected game was retrieved from the official website of the NBA (www.nba.com). The outcomes were based on winning percentage with additional covariates including the direction of travel (eastward or westward) and the distance travelled (0-500km – 501-1000km – 1001-1500km – 1501km and more). If a team played both games of a back-to-back sequence on the road, they were considered Away-Away; if a team played the first game of a back-to-back sequence at home they were considered Home-Away; if a team played the first game of a back-to-back sequence on the road they were considered Away-Home. Results The sequence Away-Home significantly increases the likelihood of winning compared to the Away-Away and Home-Away sequences 54.4% (95%CI: 54.4,54.5); 39.2% (95%CI: 37.2,41.2), and 36.8%, (95%CI: 36.7,36.8), respectively. Following a road game, when teams travel back home, every additional 500km reduces the likelihood of winning by approximately 4% (p = 0.038). Finally, after withdrawing the Away-Home sequence, travelling eastward significantly increases the chance of winning (p = 0.024) compared to westward travel but has no significant impact on the probability of winning compared to neutral time zone travel (p = 0.091). Conclusion The accumulation of travel fatigue and the chronic circadian desynchronization that occurs over the NBA season can acutely disturb sleep and recovery. It appears that tailored sleep and recovery strategies need to be dynamically developed throughout the season to overcome the different challenges of the NBA schedule. Support (if any):

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.231
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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