MétaCan
Menu
Back to cohort
Record W2563571202 · doi:10.1080/14660970.2016.1267627

The importance of domestic football leagues to international performance: predicting FIFA points

2016· article· en· W2563571202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSoccer and Society · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsLeagueFootballLimitingFootball teamSports economicsDemographic economicsPolitical scienceBusinessMarketingEconomicsEngineeringLaw

Abstract

fetched live from OpenAlex

This paper estimates the importance of domestic professional and semi-professional football clubs to the performance of national team sides in earning FIFA points. It is likely the case that the pathway to further development and a spot on the national team for a young player is, at least initially, through a domestic football league. Yet the stage of development of football leagues differs markedly across nations. This paper finds that the presence and development of these leagues is a significant contributor to FIFA points for the national side, but with diminishing returns. Most recently, the largest effect is found for the nations that play in the African (CAF) and Oceania (OFC) zones, while the other four zones (AFC, CONCACAF, CONMEBOL and UEFA) share smaller positive effects. Even in the presence of limiting economic and demographic factors, the road to international football success is through the development of domestic leagues.

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.

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)0.001
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 score0.071
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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