Tigers Scorecard

This text appears to be a large amount of data in the format of a baseball team's season statistics. The data includes information about each game played by the team, such as:

• Date of the game
• Opponent's name
• Score (home team score first)
• Number of runs scored by the home team
• Number of runs scored by the visiting team
• Win/Loss column indicating whether the home team won or lost

To analyze this data, I can provide some insights using Python:

import pandas as pd

# Define a function to parse the data and create a DataFrame
def parse_data(data):
    lines = [line.strip() for line in data.split('\n')]
    df = []
    for i in range(0, len(lines), 6): # assuming each game has 5 lines
        row = {
            'Date': lines[i+1],
            'Opponent': lines[i+2][:-3], # remove parentheses and convert to string
            'Score': f"{lines[i+4]} - {lines[i+5]}",
            'Runs Home': int(lines[i+4].split('-')[0]),
            'Runs Visiting': int(lines[i+4].split('-')[1])
        }
        df.append(row)
    return pd.DataFrame(df)

# Parse the data
data = """
         Date           Opponent      Score       Runs Home   Runs Visiting
0  07/13/2002  Angels 4-3         7             10              6
1  07/14/2002  Orioles 9-8         11             5              9
2  07/15/2002  Yankees 3-2          6             4              2
3  07/16/2002  Twins 10-1         13             7               0
4  07/17/2002  White Sox 5-3          8             9              5
5  07/18/2002  Royals 6-5          11             4              7
6  07/19/2002  Indians 1-0         12             8               0
7  07/20/2002  Twins 3-10         13             5              14
8  07/21/2002  Red Sox 4-9          6             3               9
9  07/22/2002  Blue Jays 3-1         10             7                1
10 07/23/2002  Yankees 8-0         15             5                0
11 07/24/2002  Mets 4-5          12             6               5
12 07/25/2002  Red Sox 3-0         14             9               0
13 07/26/2002  Blue Jays 7-8          8             6               8
14 07/27/2002  Yankees 4-1         16             7                1
15 07/28/2002  Indians 9-5          12             5               9
"""

# Parse the data and print summary statistics
df = parse_data(data)
print(df.head())
print("Number of games played:", len(df))
print("Total runs scored:", df['Runs Home'].sum() + df['Runs Visiting'].sum())

Note that I made some assumptions about the structure of the data (e.g. each game has 5 lines, with a specific format). You may need to adjust this code if your actual data is different.

Also note that I used pandas library for creating and manipulating the DataFrame.

Please let me know if you have any further questions or would like to perform additional analysis on this data! Updated: August 3, 2025 at 10:07 AM