Evidence map›Paper›PMID 39585923›Full record

ArticlePloS one2024

Analysis of quantile regression for race time in standard distance triathlons.

Junhui Zhao, Yongfang Ma, Xiaoxiao Hu

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Junhui ZhaoDepartment of Sports Teaching and Research, Lanzhou University, Gansu, China.ORCID 0000-0001-5808-5519
Yongfang MaSchool of Mathematics and Statistics, Center for Data Science, Lanzhou University, Gansu, China.
Xiaoxiao HuSchool of Mathematics and Statistics, Center for Data Science, Lanzhou University, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to quantitatively analyze the impact of split times on overall performance in standard distance triathlon events. It also examines how environmental factors such as water type, temperature, and altitude affect overall race outcomes.

methodsQuantile regression was employed to analyze the race records of 1,580 triathletes participating in 46 standard distance events in China.

resultsSwim time significantly influences race performance among the top 50% of elite athletes (p < 0.05). For slower elite athletes, bike time is more critical. Temperature has a positive effect on race times, while altitude also shows a significant positive impact, with race times decreasing as altitude increases (up to 1,600 meters in this study's dataset). River water enhances race times compared to still water, whereas sea water generally slows athletes down.

conclusionThe influence of split times and environmental factors on overall race rime varies according to the athletes' performance levels. To optimize results, training plans and race strategies should be tailored to each athlete's capabilities. Additionally, understanding and adapting to environmental conditions in advance is crucial.

Indexed as

Athletic PerformanceBicyclingSwimmingAltitudeAthletesChinaFemaleHumansMaleRegression AnalysisRunningTemperatureTime Factors

Identifiers

PMID39585923
PMCPMC11588204

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.