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  "Title": "Softball Run Expectancy using Markov Chains and Simulation",
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  "Authors@R": "c(\nperson(\"Annie\", \"Sauer\", role = c(\"aut\", \"cre\"), email = \"anniees@vt.edu\"),\nperson(\"Sierra\", \"Merkes\", role = \"aut\", email = \"smerkes@vt.edu\"))",
  "Description": "Implements two methods of estimating runs scored in a\nsoftball scenario: (1) theoretical expectation using discrete\nMarkov chains and (2) empirical distribution using multinomial\nrandom simulation.  Scores are based on player-specific input\nprobabilities (out, single, double, triple, walk, and homerun).\nOptional inputs include probability of attempting a steal,\nprobability of succeeding in an attempted steal, and an\nindicator of whether a player is \"fast\" (e.g. the player could\nstretch home).  These probabilities may be calculated from\ncommon player statistics that are publicly available on team's\nwebpages. Scores are evaluated based on a nine-player lineup\nand may be used to compare lineups, evaluate base scenarios,\nand compare the offensive potential of individual players.\nManuscript forthcoming.  See Bukiet & Harold (1997)\n<doi:10.1287/opre.45.1.14> for implementation of discrete\nMarkov chains.",
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  "Author": "Annie Sauer [aut, cre], Sierra Merkes [aut]",
  "Maintainer": "Annie Sauer <anniees@vt.edu>",
  "Repository": "https://anniesbooth.r-universe.dev",
  "Date/Publication": "2021-03-22 04:10:02 UTC",
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