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Record W4408612055 · doi:10.1177/15270025251323832

Homegrown Heroes: The Impact of Locally Born Hockey Players on Attendance and Revenue in the National Hockey League

2025· article· en· W4408612055 on OpenAlexafffund
Édouard Perron, Min Hu

Bibliographic record

VenueJournal of Sports Economics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsLeagueRevenueAttendanceIce hockeyAdvertisingBusinessEconomicsFinanceEconomic growth

Abstract

fetched live from OpenAlex

This study examines the impact of locally born players on team attendance and revenue in the National Hockey League (NHL). Using data from 31 NHL teams from 2005 to 2018, the study employs a refined definition of locally born players and explores alternative definitions to ensure robustness. Each additional locally born player completing a full season is associated with an increase in home game attendance by approximately 12,000 spectators and $4.8 million in additional revenue. These effects are consistent across geographic regions, including traditional and non-traditional hockey markets. The findings underscore the value of investing and promoting local talent, particularly for teams with lower attendance levels. By fostering stronger community connections and regional loyalty, locally born players enhance team identity, boost fan engagement, and increase game demand. This study provides actionable insights for team management and marketing while advancing the understanding of fan demand dynamics in professional hockey.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.023
GPT teacher head0.308
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2025
Admission routes2
Has abstractyes

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