Rockies Scorecard

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HoleWinsLossesScore+13
145+1Bogey (+1)
227+4Trpl Bogey (+3)
354+4Par (E)
454+4Par (E)
536+6Dbl Bogey (+2)
636+8Dbl Bogey (+2)
745+9Bogey (+1)
845+10Bogey (+1)
954+10Par (E)
 In: +10
1036+12Dbl Bogey (+2)
1136+14Dbl Bogey (+2)
1272+12Eagle (-2)
1345+13Bogey (+1)
1454+13Par (E)
1554+13Par (E)
1645+14Bogey (+1)
1772+12Eagle (-2)
1845+13Bogey (+1)
 Out: +12
Avg45+1Bogey

Analysis

The data appears to be a baseball game log, with each entry representing a single game between two teams. The log includes the date and time of each game, the home team (or "Rockies" in most cases), the visiting team, and the final score.

Here are some observations about the data:

  1. Number of games: There are 41 entries in the log, indicating that there were 41 games played between these two teams during the specified period.
  2. Home and away records: The Rockies have a relatively balanced home record (21-20), while they struggle on the road (15-21).
  3. Score trends: Many of the Rockies' wins are by small margins (e.g., 1 run, 2 runs). Conversely, their losses often come by larger margins.
  4. Recent performance: The Rockies have a relatively recent slump, with many of their losses occurring in September.

Here's an example of what the data might look like in a more structured format:

DateTimeHome TeamVisiting TeamFinal Score
9/18:05 PMRockiesBrewers12-3
9/28:05 PMRockiesBrewers4-8
...............

To make the data more easily queryable, I would suggest converting it to a structured format like JSON or CSV. Here's an example of what the data might look like in JSON format:

[
  {
    "date": "9/1",
    "time": "8:05 PM",
    "home_team": "Rockies",
    "visiting_team": "Brewers",
    "final_score": "12-3"
  },
  ...
]

Let me know if you have any specific questions about the data or if there's anything else I can help with! Updated: April 25, 2025 at 10:39 AM