vsajja / rotowhale

rotowhale

Demo: https://rotowhale.netlify.app

The MLB Player Rater is a simple front-end only project that loads player ratings from a static JSON data file and displays them using datatables.net.

Using Datatables, we can quickly add the ability to search, filter and export our data. We can also automatically group players into tiers (T1, T2, T3, etc.) based on a calculated vScore for each player position.

A vScore is simply a zScore calculation, which allows us to compare players and their performance to date. The static JSON file containing the generated player ratings, rotoScores and vScores can be found under data/player_ratings.json. This file was created using a scheduled Jenkins job that consumes the MLB Stats API and does all the calculations automatically. More on this later.

data/player_ratings.json

{
  "data": [
    {
      "pitchingScore": 294.0,
      "vScore": 7.741556930893517,
      "rotoScore": 1285.979,
      "nameFirst": "Shohei",
      "pitchHand": "R",
      "mlbDebutDate": "2018-03-29",
      "weight": 210,
      "birthCity": "Oshu",
      "birthDate": "1994-07-05",
      "heightFt": 6,
      "nameLast": "Ohtani",
      "bats": "L",
      "mlbPlayerId": 660271,
      "heightInches": 4,
      "jerseyNumber": 17,
      "birthCountry": "Japan",
      "seasonPitchingStats": {
        ... <snipped>
      },
      "seasonHittingStats": {
        ... <snipped>

      },
      "position": "P",
      "age": 27,
      "hittingScore": 991.979
    }
    ... <snipped>
    ]
}

how is the player_ratins.json file generated?

The player_ratings.json file is generated using the following basic stages.

Stage 1: Use the MLB Stats API to get the current fantasy baseball player pool (40 man rosters) and their seasonal hitting/pitching stats

1. MLB Stats API: getMLBTeams()
2. MLB Stats API: get40ManRosters(mlbTeamId)
3. MLB Stats API: getPlayerHittingStats(mlbPlayerId)
4. MLB Stats API: getPlayerPitchingStats(mlbPlayerId)

Stage 2: Calculate a hittingScore, pitchingScore and rotoScore

5. Calculate: hittingScore = calculateHittingScore(mlbPlayerId)
6. Calculate: pitchingScore = calculatePitchingScore(mlbPlayerId)
7. Calculate: rotoScore = pitchingScore + hittingScore

Stage 3: Once we have a set of rotoScores for a player set, we can calculate the zScore.

// variables to calculate standard deviation
def rotoScores = players.collect { (it['hittingScore'].toDouble() + it['pitchingScore'].toDouble()) }
def rotoScoresSquared = rotoScores.collect { it * it }
def rotoScoresSquaredSum = rotoScoresSquared.sum()

def populationSize = rotoScores.size()

def totalRotoScoresSquared = rotoScores.sum() * rotoScores.sum()

def standardDeviation = Math.sqrt(
    (((populationSize * rotoScoresSquaredSum) - totalRotoScoresSquared) / (populationSize * populationSize)).doubleValue())

def mean = rotoScores.sum() / rotoScores.size()

ratedCatchers = catchers.collect { catcher ->
    double rotoScore = (catcher['hittingScore'] + catcher['pitchingScore'])

    def vScore = ((rotoScore - mean) / standardDeviation)

    catcher.put('vScore', vScore)
    return catcher
}

ratedPlayers.add(ratedCatchers)

Design

HTML5 Up template called Massively.

MLB Stats API

Please note that use of MLB data from the MLB Stats API (the data/player_ratings.json file) is subject to the following copyright agreement.

"Copyright 2021 MLB Advanced Media, L.P. Use of any content on this page acknowledges agreement to the terms posted here http://gdx.mlb.com/components/copyright.txt"