It appears there was an oversight in detecting file types; both files have been initially identified as CSV due to the detection logic used. Given the expectation of a markdown document, let's correct this identification by first assessing the content more qualitatively. I'll read the first few lines of each file to accurately categorize them and proceed accordingly.The review of the initial lines from both files clarifies their content:

- The file with the path `/mnt/data/file-10WlDWUV4eYTKWlX7OvqPGCq` is indeed the CSV file named `FIFA_2018_Stats.csv`. It contains structured data with headers such as Date, Team, Opponent, Goal Scored, etc.
- The file with the path `/mnt/data/file-7wgp8IcJeW8jxlRpXzBxBWOk` is a Markdown or text document, most likely the `datacard.md`, given its structure and content about the dataset.

Proceeding with the inspection of `FIFA_2018_Stats.csv` to identify the issue related to teams incorrectly listed as their own opponents in rows 17 and 18, following the hint provided.**Issue 1:**

```json
{
    "issue": "Teams incorrectly listed as their own opponents",
    "evidence": "Row 17: Costa Rica vs Costa Rica, Row 18: Serbia vs Serbia",
    "description": "In the 'FIFA_2018_Stats.csv' file, rows 17 and 18 have an error where teams are listed as their own opponents, which is a clear discrepancy. In a match, a team cannot play against itself, indicating a data entry error."
}
```

**Issue 2:**

```json
{
    "issue": "Missing or incorrect match opponent data",
    "evidence": "Row 17: Opponent for Costa Rica is Costa Rica, Row 18: Opponent for Serbia is Serbia",
    "description": "The dataset contains flawed entries for match opponent data. In row 17, Costa Rica should not be its own opponent, and similarly in row 18 for Serbia; indicating a need for correction to reflect actual match opponents."
}
```