About Cradl

AI-powered NCAA lacrosse analysis

What is Cradl?

Cradl is an AI-powered analysis tool for NCAA Division I Men's Lacrosse. We combine real-time odds, three seasons of game data, box score stats, and a custom Elo model — then feed it all to AI to produce sharp, data-driven matchup breakdowns.

Cradl is not a sportsbook — we don't accept wagers or pay out winnings. All analysis is for informational and entertainment purposes only.

How It Works

• Live odds — DraftKings-preferred spreads, totals, and moneylines via The Odds API, updated every 30 minutes
• Historical stats — three seasons (2024–present) of NCAA lacrosse results, scores, and box scores
• Statistical model — generates predicted spreads, totals, and win probabilities for every matchup
• AI analysis — Claude synthesizes all data into a single breakdown with edge ratings and picks for spread, total, and moneyline

The Model

Every analysis is built on a multi-layer statistical model that evaluates both teams before AI generates the final breakdown:

• Power ratings — Elo-style ratings (1500 = average) for every D1 team, updated after each game with opponent-adjusted margins, per-team home advantage, and 50% season regression toward conference average
• Spread prediction — converts the power rating gap into an expected margin, adjusted by Process Quality differential
• Total prediction — uses venue-specific offensive and defensive splits (home offense at home, away defense on road) with a pace adjustment relative to the league average
• Process Quality (PQ) — a 0–100 composite score from opponent-adjusted box score stats: faceoff %, ground balls, clear %, shot accuracy, and extra-man offense %
• Venue splits — goals scored and allowed at home vs on the road for each team
• Opponent-adjusted stats — how a team performs relative to what their opponents typically allow, not just raw averages
• Strength of schedule — opponent win %, RPI, and record broken down by tier (elite, solid, weak)
• Trends — win streaks, scoring trajectory (last 3 vs season average), O/U trends, margin distributions, and volatility
• Line movement — how odds shift from open to current, signaling where money is going
• Head-to-head history — prior matchups and scoring margins from the last three seasons

The model compares its predicted spread and total against the market line, and flags the gap as Strong, Moderate, or Slight. AI then evaluates whether supporting signals (splits, trajectory, PQ, rest, tier record) converge to confirm or contradict that edge.

Edge Ratings & Confidence

• Edge Rating — Strong, Moderate, or Slight based on the gap between the model prediction and the market line
• Confidence — High (gap + 2 supporting signals), Medium (gap + 1 signal), or Low (gap only or conflicting data)
• Picks Tracker — every AI pick is logged and graded against actual results so you can track accuracy over time

Data Sources

• The Odds API — real-time moneyline, spread, and total odds from licensed sportsbooks (DraftKings preferred)
• ESPN — historical game scores, team records, schedules, and live scores
• NCAA / Sidearm Sports — box scores including player stats, faceoffs, ground balls, and goalie saves
• Anthropic Claude — AI analysis engine that synthesizes all model outputs and data into readable insights

Built by Blaine McMahon

Cradl is a solo project built by Blaine McMahon — a computer engineering grad and former lacrosse player at UMass Lowell who wanted better tools for analyzing NCAA matchups. If you have questions or feedback, reach out at [email protected].