basic approach

This is a starter repository. The approach is:

1. create a general purpose package for scraping maps, logs, and conversations from dominating12 (https://dominating12.com/), focusing on a specific set of usernames (to be defined) and also scraping from the top 100 list here: https://dominating12.com/userlist
2. also scrape maps here: https://dominating12.com/maps. turn each into a high quality vector (plottable at any resolution) with labeled territories and connections. each map gets a spatial representation (the map) + a graph representation (which territories can attack?)
3. match up logs and conversations
4. define "position strength" metrics
5. define graph metrics per map
6. look at:
- per map game dynamics: do maps cluster? do games cluster? are there general trends?
- per player dynamics: do players cluster?
- per-game dynamics: do conversations (embed each conversation turn using EmbeddingGemma) follow stereotyped trajectories? are there patterns of what people say as a function of their current position strength, position in the game, and/or position of *other* players?
7. also create playback tools for displaying animations of game and conversation dynamics

No files, tests, or entry points are named. Start by reviewing the proposed scraping sources at dominating12.com, including the user list and maps pages, then clarify the initial scope, target usernames, data formats, and first measurable milestone before implementation.

Written by the indexing model from the issue text.