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  "Package": "comperank",
  "Title": "Ranking Methods for Competition Results",
  "Version": "0.1.1.9000",
  "Authors@R": "person(given = \"Evgeni\",\nfamily = \"Chasnovski\",\nrole = c(\"aut\", \"cre\"),\nemail = \"evgeni.chasnovski@gmail.com\",\ncomment = c(ORCID = \"0000-0002-1617-4019\"))",
  "Description": "Compute ranking and rating based on competition results.\nMethods of different nature are implemented: with fixed\nHead-to-Head structure, with variable Head-to-Head structure\nand with iterative nature. All algorithms are taken from the\nbook 'Who’s #1?: The science of rating and ranking' by Amy N.\nLangville and Carl D. Meyer (2012, ISBN:978-0-691-15422-0).",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/echasnovski/comperank",
  "BugReports": "https://github.com/echasnovski/comperank/issues",
  "VignetteBuilder": "knitr",
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  "Repository": "https://echasnovski.r-universe.dev",
  "Date/Publication": "2023-01-08 18:22:44 UTC",
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  "Author": "Evgeni Chasnovski [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-1617-4019>)",
  "Maintainer": "Evgeni Chasnovski <evgeni.chasnovski@gmail.com>",
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    "name": "Evgeni Chasnovski",
    "description": "Data science, Machine learning |\r\nR, Python, Lua |\r\nNeovim plugins"
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    "extra/citation.json",
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      "date": "2018-05-30"
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      "date": "2020-03-03"
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    "add_iterative_ratings",
    "elo",
    "normalize_keener",
    "rank_colley",
    "rank_elo",
    "rank_iterative",
    "rank_keener",
    "rank_markov",
    "rank_massey",
    "rank_od",
    "rate_colley",
    "rate_elo",
    "rate_iterative",
    "rate_keener",
    "rate_markov",
    "rate_massey",
    "rate_od",
    "round_rank",
    "skew_keener",
    "teleport",
    "vote_equal",
    "vote_self"
  ],
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      "title": "Snooker events",
      "object": "snooker_events",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "id",
        "season",
        "name",
        "startDate",
        "endDate",
        "sponsor",
        "type",
        "venue",
        "city",
        "country"
      ],
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      "table": true,
      "tojson": true
    },
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      "title": "Snooker matches",
      "object": "snooker_matches",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "id",
        "eventId",
        "round",
        "player1Id",
        "score1",
        "walkover1",
        "player2Id",
        "score2",
        "walkover2",
        "winnerId",
        "startDate",
        "endDate",
        "scheduledDate",
        "frameScores"
      ],
      "rows": 5192,
      "table": true,
      "tojson": true
    },
    {
      "name": "snooker_players",
      "title": "Snooker players",
      "object": "snooker_players",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "id",
        "name",
        "nationality",
        "sex",
        "born",
        "status"
      ],
      "rows": 487,
      "table": true,
      "tojson": true
    }
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    {
      "page": "comperank-package",
      "title": "comperank: Ranking and Rating Methods for Competition Results",
      "topics": [
        "comperank-package",
        "comperank"
      ]
    },
    {
      "page": "colley",
      "title": "Colley method",
      "topics": [
        "colley",
        "rank_colley",
        "rate_colley"
      ]
    },
    {
      "page": "elo",
      "title": "Elo method",
      "topics": [
        "add_elo_ratings",
        "elo",
        "rank_elo",
        "rate_elo"
      ]
    },
    {
      "page": "iterative",
      "title": "Iterative rating method",
      "topics": [
        "add_iterative_ratings",
        "iterative",
        "rank_iterative",
        "rate_iterative"
      ]
    },
    {
      "page": "keener",
      "title": "Keener method",
      "topics": [
        "keener",
        "normalize_keener",
        "rank_keener",
        "rate_keener",
        "skew_keener"
      ]
    },
    {
      "page": "markov",
      "title": "Markov method",
      "topics": [
        "markov",
        "rank_markov",
        "rate_markov"
      ]
    },
    {
      "page": "massey",
      "title": "Massey method",
      "topics": [
        "massey",
        "rank_massey",
        "rate_massey"
      ]
    },
    {
      "page": "offense-defense",
      "title": "Offense-Defense method",
      "topics": [
        "offense-defense",
        "rank_od",
        "rate_od"
      ]
    },
    {
      "page": "rating-ranking",
      "title": "Definition of Rating and Ranking",
      "topics": [
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    },
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      "title": "Stochastic matrix modifiers",
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        "teleport",
        "vote_equal",
        "vote_self"
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        "Structure of competition results",
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