Updated 2022 May.

calculateErrorOfTestData.py

@@ -0,0 +1,78 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import pandas as pd
+import json
+
+def getPrediction(jsonPrediction, weekNumber, homeTeam, awayTeam):
+    for i in range(len(jsonPrediction)):
+        if jsonPrediction[i]['Round Number'] == weekNumber and jsonPrediction[i]['Home Team'] == homeTeam and jsonPrediction[i]['Away Team'] == awayTeam:
+            return jsonPrediction[i]
+
+    return None
+
+def getErrors(resultsDataFileName='epl-2021.csv',
+        predictedFileName='epl-predictions-stats.json', afterWeek=15):
+    results = pd.read_csv(resultsDataFileName)
+    predicted = json.load(open('epl-predictions-stats.json'))['games']
+
+    meanSquaredError = 0.0
+    correctAnswers = 0
+    totalResults = 0
+    isWin = 0
+    isTie = 0
+    for i in range(len(results)):
+
+        if results['Round Number'][i] < 11:
+            continue
+
+        homeScore = 0
+        awayScore = 0
+        try:
+            scores = results.Result[i].split('-')
+            homeScore = int(scores[0])
+            awayScore = int(scores[1])
+        except:
+            continue
+
+        totalResults += 1
+
+        p = getPrediction(predicted, results['Round Number'][i], results['Home Team'][i], results['Away Team'][i])
+        homeWinP = p['home_win']
+        awayWinP = p['away_win']
+        tieP = p['tie']
+        prediction = 0
+        if awayWinP > homeWinP and awayWinP > tieP:
+            prediction = 1
+        elif tieP > homeWinP and tieP > awayWinP:
+            prediction = 2
+
+        if (homeScore > awayScore and prediction == 0) or (awayScore > homeScore and prediction == 1) or (homeScore == awayScore and prediction == 2):
+            correctAnswers += 1
+
+        correctGuess = [0.0, 0.0, 0.0]
+        if homeScore > awayScore:
+            isWin += 1
+            correctGuess[0] = 1.0
+        elif awayScore > homeScore:
+            isWin += 1
+            correctGuess[1] = 1.0
+        elif homeScore == awayScore:
+            isTie += 1
+            correctGuess[2] = 1.0
+
+        diff = np.array(correctGuess) - np.array([homeWinP, awayWinP, tieP])
+
+        meanSquaredError += (diff * diff).sum() / 3.0
+
+    return (meanSquaredError / totalResults, correctAnswers/totalResults, isWin, isTie)
+
+
+def main(resultsDataFileName='epl-2021.csv',
+        predictedFileName='epl-predictions-stats.json'):
+    (meanSquaredError, percentCorrect, isWin, isTie) = getErrors(resultsDataFileName, predictedFileName)
+    print(meanSquaredError, percentCorrect, isWin, isTie)
+
+
+if __name__ == '__main__':
+    main()