Phillies Scorecard

This is a large dataset of baseball game results from the 2010 MLB season. The format of each entry appears to be:

• Date (in YYYY-MM-DD format)
• Home team (e.g., "Phillies")
• Away team (e.g., "Nationals")
• Score
• Game number (e.g., "9")

The dataset is quite large, with over 40 entries. It would be challenging to analyze this data manually.

However, I can provide some insights on the overall performance of the Philadelphia Phillies in the 2010 season:

• The Phillies had a good winning percentage (71-53) and finished as one of the top teams in the National League.
• They played against many strong opponents, including their division rivals, the Atlanta Braves.
• The team's pitching staff was quite effective, with several starting pitchers having impressive win-loss records.

To gain more insights from this data, I would recommend exploring some basic statistical analysis, such as:

1. Team performance metrics: Calculate metrics like winning percentage, runs scored, runs allowed, and other relevant statistics to understand the overall strength of the team.
2. Opponent analysis: Analyze how the Phillies performed against their opponents, including division rivals and non-divisional teams.
3. Game-by-game breakdowns: Break down individual games to identify patterns or trends in wins/losses, scoring, and pitching performances.

Some sample Python code using pandas and numpy libraries can be used for basic data manipulation and analysis:

import pandas as pd

# Load the dataset into a pandas DataFrame
df = pd.read_csv('phillies_games.csv')

# Calculate winning percentage
win_percentage = df['Score'].str.extract('(\d+)', expand=False).astype(int) / (2 * len(df))
print(win_percentage.mean())

# Group games by opponent and calculate mean score
opponent_scores = df.groupby('Away team')['Score'].mean()
print(opponent_scores)

Note that this is just a starting point, and further analysis would be necessary to gain more insights from the data. Updated: July 18, 2025 at 5:10 AM