Angels Scorecard

This is a large text file containing the schedule of games for the American League (AL) teams in Major League Baseball (MLB) from September 1 to September 29, 2002. The format is a list of each team's schedule, with the date and time of each game.

To parse this data, you can use various programming techniques such as:

1. Tokenization: Splitting the text into individual words or tokens.
2. Regular expressions: Using patterns to extract specific information from the text.
3. Natural Language Processing (NLP): Analyzing the text using NLP techniques to identify the teams, dates, and times.

Here is an example of how you can use Python to parse this data:

import re

# Load the schedule into a list of lines
schedule = [line.strip() for line in open('schedule.txt').readlines()]

# Define a function to extract team names from the text
def extract_team_name(text):
    # Use regular expression to match team name (e.g., "New York Yankees")
    pattern = r'([A-Za-z\s]+)\s*(\d{1,2}|\w+|-)'
    matches = re.findall(pattern, text)
    return [match[0] for match in matches]

# Extract team names from the schedule
teams = []
for line in schedule:
    teams.extend(extract_team_name(line))

# Print the extracted team names
print(teams)

This code will output a list of team names extracted from the schedule.

Alternatively, you can use NLP techniques to analyze the text and extract relevant information. For example, you can use the spaCy library in Python to perform named entity recognition (NER) on the text.

import spacy

# Load the schedule into a list of lines
schedule = [line.strip() for line in open('schedule.txt').readlines()]

# Process the schedule using spaCy NER
nlp = spacy.load("en_core_web_sm")
doc = nlp(" ".join(schedule))

# Extract team names from the processed text
team_names = []
for entity in doc.ents:
    if entity.label_ == "TEAM":
        team_names.append(entity.text)

print(team_names)

This code will output a list of team names extracted from the schedule using NER.

Note that these are just examples, and you may need to modify the code to suit your specific requirements. Updated: August 3, 2025 at 9:40 AM