NFL/miner_dashboard.py at main · sportstensor/NFL · GitHub

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from retrieve_data import get_data, scale_data, prep_pred_input
from model import load_or_run_model
from retrieve_data import update_current_team_database
import numpy as np

def activate():

    data = get_data()

    scalers, X_scaled, y_scaled = scale_data(data)

    model = load_or_run_model(scalers, X_scaled, y_scaled)

    ### This is where the new predictions will get read in ###
    list_of_fixtures = [
        {'DATE': '2024-09-06', 'HT': 'Kansas City Chiefs', 'AT' : 'Baltimore Ravens'},
        {'DATE': '2024-09-07', 'HT': 'Philadelphia Eagles', 'AT' : 'Green Bay Packers'}
        ]

    for fixture in list_of_fixtures:

        pred_input, hist_score = prep_pred_input(fixture, scalers)

        predicted_outcome = model.predict(pred_input)

        home_pred_unrounded = scalers['HT_SC'].inverse_transform(predicted_outcome[:, 0].reshape(-1, 1))[0][0]
        away_pred_unrounded = scalers['AT_SC'].inverse_transform(predicted_outcome[:, 1].reshape(-1, 1))[0][0]

        home_pred = round(home_pred_unrounded)
        away_pred = round(away_pred_unrounded)

        if home_pred == away_pred and home_pred_unrounded > away_pred_unrounded:
            away_pred -= 1
        elif home_pred == away_pred and home_pred_unrounded < away_pred_unrounded:
            home_pred -= 1

        print(fixture['HT'], ':', fixture['AT'], ' predicted score... ', home_pred, ':', away_pred, 'actual score :', hist_score)

activate()

def update_current_data():

    update_current_team_database()

    print('Ready to create new predictions.')