The 2017 Soccer Prediction Challenge: papers linking to it

OSF · Text · 2017 · osf.io/ftuva/

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to The 2017 Soccer Prediction Challenge (https://osf.io/ftuva/), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

5 papers in the tracked journals link to the OSF dataset The 2017 Soccer Prediction Challenge in their Crossref records, the first in 2018; most of them (4) in 2018.
By category: AI (5); the journals with the most are Machine Learning (4) and Expert Systems with Applications (1).
4 of the papers build on one another: a later paper cites an earlier one that also links The 2017 Soccer Prediction Challenge.

By year#

20182026

Papers linking to The 2017 Soccer Prediction Challenge by publication year
Year	Papers
2018	4
2026	1

Journals#

Journals whose papers link to The 2017 Soccer Prediction Challenge most
Journal	Papers
Machine Learning	4
Expert Systems with Applications	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Dolores: a model that predicts football match outcomes from all over the world Machine Learning, 2018
- The Open International Soccer Database for machine learning Machine Learning, 2018 — cites the paper above
Modeling outcomes of soccer matches Machine Learning, 2018
- Guest editorial: special issue on machine learning for soccer Machine Learning, 2018 — cites the paper above

Papers linking to The 2017 Soccer Prediction Challenge, most cited first
Published	Title	Journal	Authors	Citations	Link
2018-05-03	Dolores: a model that predicts football match outcomes from all over the world	Machine Learning	Anthony Costa Constantinou	84	cites it
2018-07-10	The Open International Soccer Database for machine learning	Machine Learning	Werner Dubitzky, Philippe Lopes, Jesse J. Davis et al.	61	cites it
2018-08-01	Modeling outcomes of soccer matches	Machine Learning	Alkeos Tsokos, Santhosh Narayanan, Ioannis Kosmidis et al.	41	cites it
2018-10-05	Guest editorial: special issue on machine learning for soccer	Machine Learning	Daniel Berrar, Philippe Lopes, Jesse J. Davis et al.	35	cites it
2026-03-05	Predicting football outcomes and quantifying team strengths with Bayesian modeling	Expert Systems with Applications	Tomasz Górecki, Bartłomiej Grzelak, Krzysztof Dyczkowski	3	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). The 2017 Soccer Prediction Challenge: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/osf-ftuva

@misc{scholar4ai-code-osf-ftuva,
  author = {{Scholar4AI}},
  title = {The 2017 Soccer Prediction Challenge: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/osf-ftuva}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).