Results of linear effects models examining the Swift effect on Travis Kelce’s performance.

<p>Taylor Swift’s presence or absence did not have a statistically significant effect on Travis Kelce’s performance during the Swift era, relative to Elo-matched games from the pre-Swift era.</p>

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Bibliographic Details
Main Author: James M. Smoliga (9074225) (author)
Other Authors: Kathryn E. Sawyer (22278038) (author)
Published: 2025
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_version_ 1852016430926528512
author James M. Smoliga (9074225)
author2 Kathryn E. Sawyer (22278038)
author2_role author
author_facet James M. Smoliga (9074225)
Kathryn E. Sawyer (22278038)
author_role author
dc.creator.none.fl_str_mv James M. Smoliga (9074225)
Kathryn E. Sawyer (22278038)
dc.date.none.fl_str_mv 2025-09-19T17:21:44Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0315560.t002
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Results_of_linear_effects_models_examining_the_Swift_effect_on_Travis_Kelce_s_performance_/30166997
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Sociology
Science Policy
using covariate matching
national football league
kansas city chiefs
avoid falling victim
chiefs &# 8217
chief &# 8217
scrutinize available evidence
supposed &# 8220
purported &# 8220
kelce &# 8217
swift &# 8221
swift &# 8217
research &# 8211
weak statistical evidence
6 games ),
surprising lessons relevant
matching algorithm used
effect &# 8211
games without swift
&# 8220
robust evidence
travis kelce
swift games
statistical significance
taylor swift
medical research
clinical research
13 games
unjustified theories
unjustified mechanisms
surrogate outcomes
since failure
significantly differ
significant increase
scientific journalism
scientific community
researchers must
medical journalism
media narrative
indicating inconsistency
inadequate sampling
historical data
historical averages
game outcomes
formal analysis
findings suggest
finding varied
fallacies common
experimental study
draw parallels
dc.title.none.fl_str_mv Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>Taylor Swift’s presence or absence did not have a statistically significant effect on Travis Kelce’s performance during the Swift era, relative to Elo-matched games from the pre-Swift era.</p>
eu_rights_str_mv openAccess
id Manara_59b4e9a5d101e2f849e9b4d7bc0866f4
identifier_str_mv 10.1371/journal.pone.0315560.t002
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30166997
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Results of linear effects models examining the Swift effect on Travis Kelce’s performance.James M. Smoliga (9074225)Kathryn E. Sawyer (22278038)MedicineSociologyScience Policyusing covariate matchingnational football leaguekansas city chiefsavoid falling victimchiefs &# 8217chief &# 8217scrutinize available evidencesupposed &# 8220purported &# 8220kelce &# 8217swift &# 8221swift &# 8217research &# 8211weak statistical evidence6 games ),surprising lessons relevantmatching algorithm usedeffect &# 8211games without swift&# 8220robust evidencetravis kelceswift gamesstatistical significancetaylor swiftmedical researchclinical research13 gamesunjustified theoriesunjustified mechanismssurrogate outcomessince failuresignificantly differsignificant increasescientific journalismscientific communityresearchers mustmedical journalismmedia narrativeindicating inconsistencyinadequate samplinghistorical datahistorical averagesgame outcomesformal analysisfindings suggestfinding variedfallacies commonexperimental studydraw parallels<p>Taylor Swift’s presence or absence did not have a statistically significant effect on Travis Kelce’s performance during the Swift era, relative to Elo-matched games from the pre-Swift era.</p>2025-09-19T17:21:44ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0315560.t002https://figshare.com/articles/dataset/Results_of_linear_effects_models_examining_the_Swift_effect_on_Travis_Kelce_s_performance_/30166997CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301669972025-09-19T17:21:44Z
spellingShingle Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
James M. Smoliga (9074225)
Medicine
Sociology
Science Policy
using covariate matching
national football league
kansas city chiefs
avoid falling victim
chiefs &# 8217
chief &# 8217
scrutinize available evidence
supposed &# 8220
purported &# 8220
kelce &# 8217
swift &# 8221
swift &# 8217
research &# 8211
weak statistical evidence
6 games ),
surprising lessons relevant
matching algorithm used
effect &# 8211
games without swift
&# 8220
robust evidence
travis kelce
swift games
statistical significance
taylor swift
medical research
clinical research
13 games
unjustified theories
unjustified mechanisms
surrogate outcomes
since failure
significantly differ
significant increase
scientific journalism
scientific community
researchers must
medical journalism
media narrative
indicating inconsistency
inadequate sampling
historical data
historical averages
game outcomes
formal analysis
findings suggest
finding varied
fallacies common
experimental study
draw parallels
status_str publishedVersion
title Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
title_full Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
title_fullStr Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
title_full_unstemmed Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
title_short Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
title_sort Results of linear effects models examining the Swift effect on Travis Kelce’s performance.
topic Medicine
Sociology
Science Policy
using covariate matching
national football league
kansas city chiefs
avoid falling victim
chiefs &# 8217
chief &# 8217
scrutinize available evidence
supposed &# 8220
purported &# 8220
kelce &# 8217
swift &# 8221
swift &# 8217
research &# 8211
weak statistical evidence
6 games ),
surprising lessons relevant
matching algorithm used
effect &# 8211
games without swift
&# 8220
robust evidence
travis kelce
swift games
statistical significance
taylor swift
medical research
clinical research
13 games
unjustified theories
unjustified mechanisms
surrogate outcomes
since failure
significantly differ
significant increase
scientific journalism
scientific community
researchers must
medical journalism
media narrative
indicating inconsistency
inadequate sampling
historical data
historical averages
game outcomes
formal analysis
findings suggest
finding varied
fallacies common
experimental study
draw parallels