Based on the <hint> provided about "confusion in interpreting timestamp values," and the information gathered from the 'datacard.md' and 'games.csv', we can identify specific issues related to timestamp representation in the dataset. 

### Issue 1:
**Issue:** Ambiguous Timestamp Format  
**Evidence:** The 'games.csv' file contains columns `created_at` and `last_move_at` with values such as `1.504210e+12` and `1.504130e+12`.  
**Description:** The timestamps in the dataset, as represented in the columns `created_at` and `last_move_at`, use a numerical format that could be ambiguous to users. It is not immediately clear if these timestamps are in Unix timestamp format (seconds since the Unix epoch), milliseconds since the epoch, or another format altogether. Given that conventional Unix timestamps are typically 10 digits long and these values are significantly larger, there might be confusion whether these need to be converted or interpreted differently (e.g., milliseconds or microseconds since the epoch).

### Issue 2:
**Issue:** Lack of Timestamp Information in Datacard  
**Evidence:** The 'datacard.md' mentions "Start Time" and "End Time" but does not specify the format or standard used for these timestamps.  
**Description:** The datacard provided with the dataset fails to describe the format and interpretation of the timestamp fields (`created_at` and `last_move_at`) found in the dataset. For appropriate analysis and use of the dataset, it is crucial that the timestamp format be clearly documented. This omission can lead to misinterpretation of the data, such as misunderstanding the actual date and time games were started and finished, which can impact analyses focused on time-based patterns or trends.

These issues highlight the importance of clear documentation and use of standard, easily interpretable timestamp formats in data management and sharing.