MMC vs CORR vs CorrWMetaModel

Tournament
2

Data download:

#!/usr/bin/env python3

from numerapi import NumerAPI
import pandas as pd
import json

napi = NumerAPI(
    #    public_id='',
    #    secret_key='',
    verbosity="info")

START_ROUND = 300
END_ROUND = 614
TOURNAMENT = 8

query = """
  query($roundNumber: Int!, $tournament: Int!) {
    roundDetails (roundNumber: $roundNumber, tournament: $tournament) {
      roundId
      roundNumber
      tournament
      roundTarget
      status
      isDaily
      roundResolved
      roundResolveTime
      totalStakes
      totalAtStake
      totalPayout
      payoutFactor
      totalSubmitted
      models {
        roundId
        modelName
        selectedStakeValue
        payoutSettled
        tc
        tcPercentile
        mmc
        mmcPercentile
        v2Corr20
        v2Corr20Percentile
        corrWMetaModel
        fncV3
        fncV4
      }
   }
}
"""

allPerfs = []
rounds = []
for round_num in range(START_ROUND, END_ROUND+1):

    print("roundNumber   ", round_num)

    arguments = {'roundNumber': round_num, 'tournament': TOURNAMENT}
    roundDetails = napi.raw_query(query, arguments)['data']['roundDetails']

    perf = pd.DataFrame(roundDetails['models'])
    perf['roundNumber'] = round_num
    perf['isDaily'] = roundDetails['isDaily']
    allPerfs.append(perf)

    r = {k: v for k, v in roundDetails.items() if k != 'models'}
    rounds.append(r)

pd.DataFrame(rounds).to_csv(f'round-details-{START_ROUND}-{END_ROUND}.csv', index=False)
pd.DataFrame(pd.concat(allPerfs)).to_csv(f'round-{START_ROUND}-{END_ROUND}.csv', index=False)