{
  "annotation_id": "2c18dc78-8757-4244-a94b-906572147fe8",
  "date_created": "2026-03-02T18:01:11.094000Z",
  "date_modified": "2026-03-02T18:01:11.094000Z",
  "file_hash": "294aeb0ccbeea8c3a41a8ee9cbb3beee74ab38088acc2c22cf2d145101367e58",
  "private": false,
  "record": {
    "abstract": "We introduce a Bayesian mean-value approach for ranking all college football\nteams using only win-loss data. This approach is unique in that the prior\ndistribution necessary to handle undefeated and winless teams is calculated\nself-consistently. Furthermore, we will show statistics supporting the validity\nof the prior distribution. Finally, a brief comparison with other football\nrankings will be presented.",
    "arxiv_id": "physics/0607064",
    "authors": [
      "James R. Ashburn",
      "Paul M. Colvert"
    ],
    "categories": [
      "physics.pop-ph",
      "physics.data-an"
    ],
    "title": "A Bayesian Mean-Value Approach with a Self-Consistently Determined Prior   Distribution for the Ranking of College Football Teams",
    "url": "https://arxiv.org/abs/physics/0607064"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "104b949b-b64d-4e99-8663-711491a3a568",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}