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  "Title": "Ranking Teams by Elo Rating and Comparable Methods",
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  "Description": "A flexible framework for calculating Elo ratings and\nresulting rankings of any two-team-per-matchup system (chess,\nsports leagues, 'Go', etc.). This implementation is capable of\nevaluating a variety of matchups, Elo rating updates, and win\nprobabilities, all based on the basic Elo rating system. It\nalso includes methods to benchmark performance, including\nlogistic regression and Markov chain models.",
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  "Author": "Ethan Heinzen [aut, cre]",
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    "extra/citation.json",
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      "date": "2017-08-16"
    },
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      "date": "2017-11-20"
    },
    {
      "version": "1.0.1",
      "date": "2017-12-14"
    },
    {
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    },
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      "date": "2022-02-04"
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    "adjust",
    "brier",
    "elo.calc",
    "elo.colley",
    "elo.glm",
    "elo.markovchain",
    "elo.model.frame",
    "elo.prob",
    "elo.run",
    "elo.run.multiteam",
    "elo.update",
    "elo.winpct",
    "favored",
    "final.elos",
    "group",
    "is.score",
    "k",
    "mov",
    "mse",
    "multiteam",
    "neutral",
    "players",
    "rank.teams",
    "regress",
    "score"
  ],
  "_datasets": [
    {
      "name": "tournament",
      "title": "'tournament': Mock data for examples",
      "object": "tournament",
      "class": [
        "data.frame"
      ],
      "fields": [
        "team.Home",
        "team.Visitor",
        "points.Home",
        "points.Visitor",
        "week",
        "half"
      ],
      "rows": 56,
      "table": true,
      "tojson": true
    },
    {
      "name": "tournament.multiteam",
      "title": "'tournament.multiteam': Mock data for examples",
      "object": "tournament.multiteam",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "week",
        "half",
        "Place_1",
        "Place_2",
        "Place_3",
        "Place_4"
      ],
      "rows": 28,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "auc.elo",
      "title": "Calculate AUC on an 'elo.run' object",
      "topics": [
        "auc.elo",
        "auc.elo.colley",
        "auc.elo.glm",
        "auc.elo.markovchain",
        "auc.elo.run",
        "auc.elo.running",
        "auc.elo.winpct"
      ]
    },
    {
      "page": "elo",
      "title": "The Elo Package",
      "topics": [
        "elo-package",
        "elo"
      ]
    },
    {
      "page": "elo.calc",
      "title": "Post-update Elo values",
      "topics": [
        "elo.calc",
        "elo.calc.default",
        "elo.calc.formula"
      ]
    },
    {
      "page": "elo.colley",
      "title": "Compute a Colley matrix model for a matchup.",
      "topics": [
        "elo.colley"
      ]
    },
    {
      "page": "elo.glm",
      "title": "Compute a (usually logistic) regression model for a series of matches.",
      "topics": [
        "elo.glm"
      ]
    },
    {
      "page": "elo.markovchain",
      "title": "Compute a Markov chain model for a series of matches.",
      "topics": [
        "elo.markovchain"
      ]
    },
    {
      "page": "elo.model.frame",
      "title": "Interpret formulas in 'elo' functions",
      "topics": [
        "elo.model.frame"
      ]
    },
    {
      "page": "elo.mov",
      "title": "Create a \"margin of victory\" column",
      "topics": [
        "elo.mov",
        "mov"
      ]
    },
    {
      "page": "elo.mse",
      "title": "Calculate the mean square error",
      "topics": [
        "brier",
        "elo.mse",
        "mse",
        "mse.elo.colley",
        "mse.elo.glm",
        "mse.elo.markovchain",
        "mse.elo.run",
        "mse.elo.running",
        "mse.elo.winpct"
      ]
    },
    {
      "page": "elo.prob",
      "title": "Elo probability",
      "topics": [
        "elo.prob",
        "elo.prob.default",
        "elo.prob.elo.multiteam.matrix",
        "elo.prob.formula"
      ]
    },
    {
      "page": "elo.run",
      "title": "Calculate running Elos for a series of matches.",
      "topics": [
        "elo.run"
      ]
    },
    {
      "page": "elo.run.helpers",
      "title": "Helper functions for 'elo.run'",
      "topics": [
        "as.data.frame.elo.run",
        "as.matrix.elo.run",
        "as.matrix.elo.run.regressed",
        "elo.run.helpers",
        "final.elos",
        "final.elos.elo.run",
        "final.elos.elo.run.regressed"
      ]
    },
    {
      "page": "elo.run.multiteam",
      "title": "Calculate running Elos for a series of multi-team matches.",
      "topics": [
        "elo.run.multiteam"
      ]
    },
    {
      "page": "elo.update",
      "title": "Elo updates",
      "topics": [
        "elo.update",
        "elo.update.default",
        "elo.update.formula"
      ]
    },
    {
      "page": "elo.winpct",
      "title": "Compute a (usually logistic) regression based on win percentage for a series of matches.",
      "topics": [
        "elo.winpct"
      ]
    },
    {
      "page": "favored.elo",
      "title": "Classify teams that are favored to win",
      "topics": [
        "favored",
        "favored.default",
        "favored.elo",
        "favored.elo.colley",
        "favored.elo.glm",
        "favored.elo.markovchain",
        "favored.elo.run",
        "favored.elo.running",
        "favored.elo.winpct"
      ]
    },
    {
      "page": "fitted.elo",
      "title": "Extract model values",
      "topics": [
        "fitted.elo",
        "fitted.elo.colley",
        "fitted.elo.glm",
        "fitted.elo.markovchain",
        "fitted.elo.run",
        "fitted.elo.running",
        "fitted.elo.winpct",
        "residuals.elo.run"
      ]
    },
    {
      "page": "formula.specials",
      "title": "Details on 'elo' formulas and the specials therein",
      "topics": [
        "adjust",
        "formula.specials",
        "group",
        "k",
        "multiteam",
        "neutral",
        "players",
        "regress"
      ]
    },
    {
      "page": "predict.elo",
      "title": "Make Predictions on an 'elo' Object",
      "topics": [
        "predict.elo",
        "predict.elo.colley",
        "predict.elo.glm",
        "predict.elo.markovchain",
        "predict.elo.run",
        "predict.elo.run.multiteam",
        "predict.elo.run.regressed",
        "predict.elo.running",
        "predict.elo.winpct"
      ]
    },
    {
      "page": "rank.teams",
      "title": "Rank teams",
      "topics": [
        "rank.teams",
        "rank.teams.elo.colley",
        "rank.teams.elo.glm",
        "rank.teams.elo.markovchain",
        "rank.teams.elo.run",
        "rank.teams.elo.run.regressed",
        "rank.teams.elo.winpct"
      ]
    },
    {
      "page": "score",
      "title": "Create a 1/0/0.5 win \"indicator\"",
      "topics": [
        "is.score",
        "score"
      ]
    },
    {
      "page": "summary.elo",
      "title": "Summarize an 'elo' Object",
      "topics": [
        "summary.elo",
        "summary.elo.colley",
        "summary.elo.glm",
        "summary.elo.markovchain",
        "summary.elo.run",
        "summary.elo.winpct"
      ]
    },
    {
      "page": "tournament",
      "title": "'tournament': Mock data for examples",
      "topics": [
        "tournament"
      ]
    },
    {
      "page": "tournament.multiteam",
      "title": "'tournament.multiteam': Mock data for examples",
      "topics": [
        "tournament.multiteam"
      ]
    }
  ],
  "_readme": "https://github.com/eheinzen/elo/raw/HEAD/README.md",
  "_rundeps": [
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      "source": "players.Rmd",
      "filename": "players.html",
      "title": "Adjusting for Players in the Elo Framework",
      "author": "Ethan Heinzen",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Adjusting for Players in the Elo Framework",
        "Another Application"
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      "created": "2023-09-19 01:55:58",
      "modified": "2023-09-19 01:55:58",
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      "source": "running_elos.Rmd",
      "filename": "running_elos.html",
      "title": "Calculating Running Elo Updates",
      "author": "Ethan Heinzen",
      "engine": "knitr::rmarkdown",
      "headings": [
        "The elo.run() function",
        "With two variable Elos",
        "With a fixed-Elo opponent",
        "Regress Elos back to the mean",
        "Group matches",
        "elo.run.multiteam()",
        "Helper functions",
        "Making Predictions",
        "Advanced: custom probability and updates",
        "Final Thoughts"
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      "created": "2020-10-21 21:22:36",
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      "title": "Comparison Methods",
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      "headings": [
        "Comparison Models",
        "Win/Loss Logistic Regression",
        "Logistic Regression",
        "Markov Chain",
        "A note about LRMC",
        "Colley Matrix Method",
        "Modeling Margin of Victory Instead of Wins"
      ],
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      "modified": "2023-08-22 17:04:16",
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      "source": "intro.Rmd",
      "filename": "intro.html",
      "title": "Introduction to Elo Rankings and the 'elo' Package",
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      "engine": "knitr::rmarkdown",
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        "Introduction to Elo Rankings",
        "The elo Package",
        "Naming Schema",
        "Basic Functions",
        "Formula Interface",
        "Final Thoughts"
      ],
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      "modified": "2020-10-21 21:22:36",
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