nfl_draft

2026 NFL Draft simulator with:

• a Python CLI for draft simulation and team lookup
• a static web UI for GitHub Pages (round-by-round and team-by-team views)

By default, the CLI tries to load real 2026 draft picks from the nfl_data_py package (sourced from the nflverse project). This data becomes available after the draft concludes. Until then, the CLI falls back to a simulated draft using real 2026 player names from the public Mock-Draft-Database dataset (or generated placeholders if that source is also unavailable).

Setup

Install Python dependencies:

pip install -r requirements.txt

Use Python 3.11 for dependency compatibility (nfl-data-py currently resolves to pandas<2, which is not installable on Python 3.12 in this workflow).

Python CLI usage

Run a full 7-round draft (real picks when available, simulation otherwise)

python nfl_draft.py

The header line (# Source: …) tells you whether you are viewing real picks from nfl_data_py or a simulated draft.

View picks for a single team (example: Dallas Cowboys)

python nfl_draft.py --team "Dallas Cowboys"

GitHub Actions – draft data refresh

The Update Draft Data workflow (.github/workflows/update_draft.yml) refreshes docs/draft_data.json on each push to main/master (including merges) and can also be run manually from Actions → Update Draft Data → Run workflow:

1. It installs the Python dependencies from requirements.txt.
2. It runs generate_data.py, which tries nfl_data_py first and falls back to a simulation when real picks are not yet available.
3. If the generated file changed, it commits and pushes the update to the repository. GitHub Pages then serves the fresh data immediately.

To run the data generation locally:

python generate_data.py

This writes docs/draft_data.json, which the web UI fetches on load.

Web UI (GitHub Pages)

The web app is in /docs:

• /docs/index.html
• /docs/app.js
• /docs/styles.css

Features:

• Round by round view: choose a round and see all 32 picks
• Team by team view: choose a team and see all 7 picks

To publish on GitHub Pages for this repository:

1. Go to Settings → Pages
2. Set source to Deploy from a branch
3. Select your branch and the /docs folder
4. Save and open the generated site URL

To include it from jjesse.github.io, link to the published nfl_draft page.

Draft pick order

The simulator always uses the correct team ordering for every pick, including traded picks. The pick order is resolved through the following fallback chain:

1. nflverse data release – get_draft_order(year) fetches the completed draft order from the [nflverse-data draft_picks release] (https://github.com/nflverse/nflverse-data/releases/tag/draft_picks). This CSV is updated after each draft concludes and uses the same team abbreviations as the rest of the codebase.
2. Hardcoded 2026 order – When nflverse data is not yet available (i.e., the draft has not concluded), a built-in 2026 order is used:
   • Round 1 picks 1–24 are the officially announced order (including all traded picks such as "Los Angeles Rams from Atlanta Falcons via trade").
   • Round 1 picks 25–32 are estimated from 2025 season standings.
   • Rounds 2–7 use an approximate inverse-standings order for all 32 teams (including teams that traded away their Round 1 pick).

The source field in docs/draft_data.json (and the # Source: header in CLI output) tells you which data was used.

Drafttek prospect data

The simulator uses the Drafttek 2026 top-600 big board as the primary player pool for simulated drafts. The data is stored locally so no internet access is required at runtime:

• drafttek_2026_top600_with_bio.csv – ranked prospect list with position, college, height, weight, class, and bio URL.
• drafttek_2026_top600_with_bio.json – the same data in JSON format.

The simulation fallback order is:

1. Real picks from nfl_data_py (used after the draft concludes).
2. Drafttek top-600 CSV (primary simulation source, sorted by rank).
3. Mock-Draft-Database remote CSV (secondary simulation source).
4. Generated placeholders (Prospect 001, Prospect 002, …).

Refreshing the Drafttek data

scrape_draftek_bio.py is a standalone utility script that re-scrapes the DraftTek big board and overwrites the two data files above. Run it manually when you want to pull fresh rankings:

pip install requests beautifulsoup4 pandas tqdm
python scrape_draftek_bio.py

After running the scraper, commit the updated CSV/JSON files and run python generate_data.py to regenerate docs/draft_data.json.

Run tests

python -m unittest discover -s tests -v