Braves Scorecard

This appears to be a text file containing the results of baseball games played between various teams in Major League Baseball (MLB) for the 2016 season. The format of the data is not explicitly stated, but it seems to follow a consistent structure.

Here's an example of how you could parse this data:

1. Split into individual lines: Each line represents the result of a game between two teams.
2. Identify team names: Team names can be identified by their full name, which is usually followed by the score (e.g., "Braves 7 - Mets 3").
3. Extract relevant information: The data can be extracted into various fields, such as:
   • Date of the game
   • Teams involved
   • Score
4. Store in a structured format: Consider storing the data in a CSV (Comma Separated Values) file or a database like MongoDB.

Here's an example of how you could represent this data in Python:

import csv

# Sample data
game_results = [
    "Date,Teams,Score",
    "2016-09-01,Braves,Mets 4-3",
    "2016-09-02,Nats,Braves 12-5",
    # ...
]

# Write to CSV file
with open('game_results.csv', 'w', newline='') as csvfile:
    writer = csv.writer(csvfile)
    writer.writerow(["Date", "Teams", "Score"])  # header row
    for game in game_results[1:]:  # skip first line (header)
        writer.writerow(game.split(','))

# Or store in a database like MongoDB
import pymongo

client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["game_data"]
collection = db["games"]

for game in game_results[1:]:
    doc = {
        "date": game.split(',')[0],
        "teams": [team.strip() for team in game.split(',')[1].split('-')],
        "score": game.split(',')[2]
    }
    collection.insert_one(doc)

This code assumes that the data is stored in a list of strings, where each string represents a line from the file. It writes this data to a CSV file or stores it in a MongoDB database.

Please note that this is just an example, and you may need to modify the code based on your specific requirements. Updated: June 27, 2025 at 12:15 AM