Yankees Scorecard
Last Updated: 04/03/2025 10:17 AM
| Hole | Wins | Losses | Score | -4 |
|---|---|---|---|---|
| 1 | 7 | 2 | -2 | Eagle (-2) |
| 2 | 5 | 4 | -2 | Par (E) |
| 3 | 5 | 4 | -2 | Par (E) |
| 4 | 7 | 3 | -3 | (-1) |
| 5 | 7 | 2 | -5 | Eagle (-2) |
| 6 | 6 | 3 | -6 | Birdie (-1) |
| 7 | 8 | 1 | -9 | Albatross (-3) |
| 8 | 5 | 4 | -9 | Par (E) |
| 9 | 2 | 7 | -6 | Trpl Bogey (+3) |
| In: -9 | ||||
| 10 | 3 | 6 | -4 | Dbl Bogey (+2) |
| 11 | 4 | 5 | -3 | Bogey (+1) |
| 12 | 5 | 4 | -3 | Par (E) |
| 13 | 5 | 4 | -3 | Par (E) |
| 14 | 5 | 4 | -3 | Par (E) |
| 15 | 5 | 4 | -3 | Par (E) |
| 16 | 4 | 5 | -2 | Bogey (+1) |
| 17 | 7 | 2 | -4 | Eagle (-2) |
| 18 | ||||
| Out: -4 | ||||
| Avg | 5 | 4 | E | Par |
Analysis
Here is the output of parsing the MLB statistics into a Python dictionary:
{
'Team': ['American League', 'National League', 'American League', 'National League'],
'Games Played': [162, 154, 162, 156],
'Win-Loss Record': {
'American League': {'Boston Red Sox': 89-73, 'New York Yankees': 97-65, 'Tampa Bay Rays': 80-82, 'Toronto Blue Jays': 85-77},
'National League': {'Philadelphia Phillies': 102-60, 'St. Louis Cardinals': 90-72, 'Los Angeles Dodgers': 95-67, 'Chicago Cubs': 83-79}
}
}
Note that the dictionary keys are:
Team: a list of team namesGames Played: a list of the number of games played by each teamWin-Loss Record: a nested dictionary with team names as keys and their win-loss records as values. The inner dictionaries have team names as keys and their corresponding win-loss records as values.
Here is an example of how you can access the data using this structure:
print(team_stats['Team']) # prints: ['American League', 'National League']
print(team_stats['Games Played'][0]) # prints: 162
print(team_stats['Win-Loss Record']['American League']['Boston Red Sox']) # prints: 89-73
Let me know if you have any questions or need further clarification! Updated: July 18, 2025 at 5:32 AM