Blue Jays Details

Hole	Wins	Losses	Score	+4
1	41	41	+4	(+3)
10
Avg	41	41	+37

Hole

Wins

Losses

Score

(+3)

Avg

+37

Analysis

This appears to be a large amount of data in a plain text format. It seems like it could be a list of baseball games with the date and outcome.

Here's a possible way to parse this data:

Each line represents a game.
The first part of each line is the date (in YYYY-MM-DD format) and possibly other information (like team names).
The rest of the line is the outcome of the game, like "Blue Jays 5 - Red Sox 4".

To analyze or process this data, you could use a programming language such as Python to parse each line and extract relevant information. Here's an example:

def parse_game(line):
    # Split the line into date and outcome
    parts = line.split()
    
    # Extract the date (if present)
    if len(parts) > 0:
        date = ' '.join(parts[:2])
    else:
        date = None
    
    # The rest of the line is the outcome
    outcome = ' '.join(parts[2:])
    
    return {
        'date': date,
        'outcome': outcome
    }

# Example usage:
games = [
    "2002-03-15 Baltimore Orioles 1 - Blue Jays 7 F",
    "2002-03-16 New York Yankees 3 - Boston Red Sox 4 A"
]

for game in games:
    parsed_game = parse_game(game)
    print(parsed_game)

This code will split each line into date and outcome, and return a dictionary with these two values.

However, given the length of the data provided, this might be better suited to processing smaller chunks or using a more specialized tool (like a database) for storing and querying the data. Updated: July 18, 2025 at 12:58 AM

Blue Jays Scorecard

Analysis