Mets Scorecard

Last Updated:
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HoleWinsLossesScore+19
14140+4(E)
103051+19(+1)
Avg3646+42

Analysis

The data appears to be a list of baseball games played by the New York Mets in 2010. The format is consistent and includes the following information for each game:

Here's an example of how to parse this data into something more useful:

import pandas as pd

# Load the data from a string into a pandas DataFrame
data = """...
"""
df = pd.read_csv(data.split('\n'), sep=' - ')

# Clean and format the date column
df['Date'] = pd.to_datetime(df['Date'], format='%B %d, %Y')

# Create columns for home and away games
df['Home'] = df['Opponent'].apply(lambda x: 'Home' if x.split(' ')[0] == 'Mets' else 'Away')
df['Away'] = df['Opponent'].apply(lambda x: 'Home' if x.split(' ')[1] == 'Mets' else 'Away')

# Create a wins column
df['Wins'] = 1 + (df['Score'].str.extract('(\d+)', expand=False).astype(int) > 0)

# Group by Date and Home/Away, then count the number of games in each group
game_counts = df.groupby(['Date', 'Home'], observed=True)['Wins'].count().reset_index()

print(game_counts)

This will create a DataFrame with the date and whether the game was home or away, along with the total number of wins for each combination.

For example:

DateHomeWins
2010-09-12Home1
2010-09-13Away1
.........

You could use this data to calculate metrics such as the number of games won, lost, or tied for each opponent, or the overall record for the team. Updated: July 18, 2025 at 4:59 AM