Game of Football

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

3 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (9 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Game Plan: What AI can do for Football, and What Football can do for AI
  18 Nov 2020 1 repository listed
  The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball, basketball, and tennis.
• Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking
  5 Sep 2019 1 repository listed
  We first solve the detection task for an image using fully convolutional encoder-decoder architecture, and later, we use it as an input to our temporal models and jointly learn the detection task in sequences of images.
• Google Research Football: A Novel Reinforcement Learning Environment
  25 Jul 2019 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  Recent progress in the field of reinforcement learning has been accelerated by virtual learning environments such as video games, where novel algorithms and ideas can be quickly tested in a safe and reproducible manner.
• Modelling Association Football Scores and Inefficiencies in the Football Betting Market
  1 Jan 1997 1 repository listed
  A parametric model is developed and fitted to English league and cup football data from 1992 to 1995.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.