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Record W2892236608 · doi:10.1177/155862351000500404

Franchise Values in North American Professional Sports Leagues: Evidence from the Repeat Sales Method

2010· article· en· W2892236608 on OpenAlexaff
Brad R. Humphreys, Yang Seung Lee

Bibliographic record

VenueInternational Journal of Sport Finance · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFranchiseLeagueIndex (typography)Volatility (finance)Quality (philosophy)Price indexEconomicsHedonic indexAdvertisingMarketingEconometricsBusiness

Abstract

fetched live from OpenAlex

We develop a quality adjusted professional sports franchise price index for North America based on the repeat sale method and a hybrid method originally applied to house prices. For the repeat sale method, the index reflects trends in the general price of franchises holding market, facility and team quality constant. The constant quality constant assumption in the repeat sale model may affect the price index, so we also use a hybrid model as an alternative. The repeat sale method price index exhibits considerable volatility but no upward trend over time, unlike previous quality adjusted price indexes based on hedonic models. The lack of an upward trend in the index indicates that franchise quality drives observed increases in prices over the past 40 years. The hybrid method exhibits price index shows a steady increase beginning in about 1990. This difference can be explained by changes in market population and facility characteristics.

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)0.007
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.287
Teacher spread0.264 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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