Correcting Common Issues in Team vs Team Analysis: A Guide to Improving Aggregate Points Calculations

Based on the provided code snippet, there are a few issues that could be causing the incorrect results:

Incorrect Aggregation: In the original code, output['average'] = (output['home_score'] + output['away_score'])/2 is trying to calculate the average of both home_score and away_score columns. However, when grouping by both teams, you should be using the correct column for each team.
Instead, you should use output['average'] = (output['away_score'] + output['home_score'])/2 to correctly calculate the average points scored by each team against another team.
Indexing and Groupby: When grouping by both teams, you need to ensure that the correct columns are being used.
In the corrected code snippet, output.groupby(['home_team', 'away_team']).aggregate({...}) is correctly grouping by both teams.
Corrected Code:

def avg_scored_allowed(df):
    # Calculate the average points scored for each team
    output = df.groupby(['home_team', 'away_team']).aggregate({
        'home_score': 'mean',
        'away_score': 'mean'
    })

    # Correctly calculate the average points scored by each team against another team
    output['average'] = (output['away_score'] + output['home_score'])/2

    return output

Example Usage:

# Sample DataFrame
df = pd.DataFrame({
    'home_team': ['S.S. Felice Scandone', 'Pallacanestro Varese', 'Pallacanestro Biella', 'Pallacanestro Cantù',
                 'Guerino Vanoli Basket', 'Mens Sana 1871 Basket', 'Victoria Libertas', 'New Basket Brindisi',
                 'Pallacanestro Treviso', 'Pallacanestro Virtus Roma'],
    'away_team': ['Pallacanestro Varese', 'JuveCaserta Basket', 'Teramo Basket', 'S.S. Felice Scandone',
                 'Guerino Vanoli Basket', 'New Basket Brindisi', 'Olimpia Milano', 'Pallacanestro Treviso',
                 'Victoria Libertas', 'Pallacanestro Cantù'],
    'home_score': [85, 87, 77, 79, 64, 92, 73, 72, 89, 66],
    'away_score': [69, 86, 70, 71, 75, 61, 78, 81, 91, 66]
})

# Calculate average points scored for each team
result = avg_scored_allowed(df)

print(result)

This should give you the correct results for the average points scored by each team against another team.

Last modified on 2024-08-20