About SandlotSharp

Why This Exists

SandlotSharp started as a personal frustration. Sports betting “experts” everywhere — and almost none of them publish a real, timestamped, auditable track record. Results get cherry-picked. Losing streaks vanish. The only thing transparent is the price of the subscription.

The goal here is the opposite: build a model with actual edge, show every pick publicly before the game, and let the numbers speak for themselves over time. If the model is good, the record will show it. If it isn’t, that will show too — and we’ll fix it.

How the Model Works

SandlotSharp focuses on MLB first-inning outcomes — specifically YRFI (Yes Run First Inning) and NRFI (No Run First Inning). The first inning has more predictive structure than most markets: starter quality is known, lineup tendencies are consistent, and park/weather effects are measurable.

The scoring engine analyzes:

• Pitcher F1 performance — each starter’s historical first-inning scoreless rate, sample-size adjusted
• ERA, WHIP, and BB/9 — overall pitcher quality indicators
• Park factors — ballpark run-scoring environment (Colorado is very different from Petco)
• Weather — temperature and wind speed for outdoor games
• Matchup combos — compound signals like “both pitchers F1 ≤45% in a hitter park” that have demonstrated elevated win rates in backtesting
• Team offense — first-inning scoring rates, platoon splits, and back-to-back fatigue

Each game receives an edge score (0–100) and a recommendation tier (Strong / Mild / Lean / Skip). AI-generated reasoning explains the decisive factors in plain language for every pick.

Transparency Is the Point

Every pick is posted by 8am PT before the first pitch — no retroactive editing, no hiding losses. The Record page shows the full live track record since June 12, 2026, plus the 60-day backtest used to validate the model before launch.

The methodology is disclosed. The rules that govern scoring — what counts as a primary factor, how sample sizes affect F1 rate confidence, what triggers a hard disqualification — are all versioned and updated transparently when the model changes.

A Note on Risk

A 61% backtest win rate is meaningful — but it is not a guarantee. Sports outcomes involve variance that no model eliminates. SandlotSharp is an informational tool, not a financial advisor or sportsbook. Please read our full Risk Disclosure & Disclaimer before wagering — and never bet more than you can afford to lose.