Press Kit & Media Resources

For podcasters, sportsbook affiliates, sports-betting journalists, and academic researchers. Everything you need to cover, cite, or embed Bookie Bullies. Free to use; attribution requested via a link back to bookiebullies.com.

The One-Liner

Bookie Bullies publishes free sabermetric sports picks made by MarcDuck with AI assistance. Every pick is graded honestly, every signal is documented, and the entire picks ledger is public as a CC BY 4.0 dataset.

Fact Sheet

• Founded: April 2026
• Founder: MarcDuck
• Coverage: MLB (in-season), NBA (in-season), NHL (in-season), WNBA (in-season)
• Today's slate: 15 MLB · 0 NBA · 1 NHL · 0 WNBA games
• Model factors: 35 sabermetric signals per MLB pick — FIP, xFIP, K-BB%, BABIP regression, LOB% regression, Pythagenpat, platoon edges, OAA defense, catcher framing, park factors, weather, bullpen rest, lineup wOBA, umpire splits, and more.
• Stake sizing: Variance-adjusted 1/8-Kelly with disagreement shrinkage.
• Calibration: Platt scaling refit nightly on graded outcomes.
• Pricing model: Free. All picks public. Ad-supported (sportsbook ad space).
• License: Picks dataset CC BY 4.0. Methodology documented at /methodology.html.
• Track record: Updated daily at /track-record.html. Closing Line Value tracked per pick.

Logo Download

PNG, 256×256, dark background. Use as-is or with the Bookie Bullies wordmark.

• Logo (PNG, 256×256, ~113 KB)
• OG / Social card (PNG, 1200×630, ~55 KB)

Public Dataset

The complete picks ledger is published as a public dataset under CC BY 4.0. Cite as: MarcDuck. (2026). Bookie Bullies Daily Sabermetric Sports Picks Dataset. Retrieved 2026-05-16, from https://www.bookiebullies.com/track-record.html

• JSON Feed — today's picks in machine-readable JSON Feed 1.1 format
• REST API — today's picks (raw JSON, all metadata)
• RSS Feed — subscribe to daily picks via any RSS reader
• Full graded ledger — every pick, every result, units profit/loss
• llms.txt — citation guidance for AI assistants

Coverage Areas Open for Interview

If you're producing a podcast episode, written piece, or research paper, here are angles MarcDuck is set up to speak to:

• How a public sabermetric model competes with sharp markets (Pinnacle no-vig CLV)
• Variance-adjusted Kelly: why 1/8 instead of full Kelly?
• Disagreement shrinkage: how to detect a model that's lying to itself
• The brain: temporal-decay learning on signal-outcome correlation
• WNBA model challenges: small samples, non-normal score distributions
• Why publishing losing picks is a feature, not a bug
• Open-data philosophy in sports betting analytics

Talking Numbers

Quotable claims, all verifiable on /track-record.html:

• Every pick logged with timestamped odds, model probability, and signal snapshot
• CLV (closing line value) tracked vs Pinnacle no-vig closing prices per pick
• Per-bucket ROI exposed (sport × pick type × confidence tier)
• Automatic disable of underperforming buckets via drift detection
• Updated 5× daily during MLB season (7am, 10am, 3pm, 6pm, 10pm PT)
• Brain retrains nightly with 60-day half-life temporal decay

How to Cite

Plain text:

MarcDuck. (2026). Bookie Bullies — Daily Sabermetric Sports Picks Dataset.
Retrieved 2026-05-16, from https://www.bookiebullies.com/track-record.html

HTML / blog citation:

<a href="https://www.bookiebullies.com/">Bookie Bullies</a> sabermetric sports picks by MarcDuck

Embeddable Today's Picks

For news sites + sportsbook affiliates: drop this iframe into a blog post or sidebar to auto-display today's top MLB locks. Updates automatically twice daily.

<iframe src="https://www.bookiebullies.com/free-mlb-picks/?embed=1"
        width="100%" height="640" frameborder="0"
        title="Bookie Bullies MLB Picks Today"></iframe>

Contact

Press inquiries, interview requests, data partnerships: open an issue on the source repo or DM via the social profiles listed on the about page.

See Also

• About MarcDuck
• Full methodology
• Public track record
• Today's picks