Quantitative Projections from a Data-Driven Oddsmaker (MLB, NFL & NBA)
Welcome to the sports betting projection hub at MavenSports.io — a toolset built to mimic how a sharp oddsmaker prices games.
This isn’t a tip sheet. It’s the raw output of a custom, machine-learning oddsmaker model that simulates every MLB and NBA matchup to generate true win probabilities, fair odds, and edge values.
If you’re building your own model, looking to exploit inefficiencies, or just reverse-engineering the market, this is your data-native launchpad.
New to the site? Get to know MavenSports.io →
🧠 How This Oddsmaker Sports Betting Model Works
Our system is designed to simulate what a quantitative bookmaker would produce behind the curtain.
Inputs:
- Player & team-level performance data (historical and current)
- Advanced metrics: expected runs, shot quality, pace, etc.
- Market baselines: Pinnacle opening lines (overnight)
- Contextual modifiers: travel, back-to-backs, lineup news, injury impact
Outputs:
- Win Probabilities for each team
- Fair Odds derived from win% (using no-vig math)
- Edge % — how much value exists vs. the current market price
⚙️ Using the Data Like a Quant Oddsmaker
Treat this page as a modeling sandbox. Here’s how to extract maximum value:
- Compare Our Fair Odds to Market Lines: This is pure line evaluation — no guesswork.
- Look at the Edge Column:
- +3% or more = statistically relevant value
- 0–1% = market is too sharp — pass
- Blend It Into Your Workflow: Use it to validate your models, price shop, or flag suspicious line moves.
NFL Week 1 projections
| away | home | quarterbacks | market ml | imp | ml edge% | spread | spr price | spr edge | total | ojuice | t_edge% |
| New England Patriots | Seattle Seahawks | Drake Maye / Sam Darnold | SEA -180 | NE 36,4% / SEA 63,6% | NE -4,3% / SEA +4,3% | -3,5 | 100 | 2,7 | 44,0 | -110 | 2,4 |
| San Francisco 49ers | Los Angeles Rams | Brock Purdy / Matthew Stafford | LAR -190 | SF 36,0% / LAR 64,0% | SF -3,3% / LAR +3,3% | -3,5 | -110 | 1,8 | 48,0 | -110 | -0,3 |
| Cleveland Browns | Jacksonville Jaguars | Shedeur Sanders / Trevor Lawrence | JAC -370 | CLE 21,5% / JAC 78,5% | CLE -2,9% / JAC +2,9% | -8,0 | -110 | 3,4 | 40,5 | -110 | 6,7 |
| Tampa Bay Buccaneers | Cincinnati Bengals | Baker Mayfield / Joe Burrow | TB +185 | TB 34,9% / CIN 65,1% | TB +2,4% / CIN -2,4% | -3,5 | -110 | 0,7 | 50,0 | -110 | 4,0 |
| Baltimore Ravens | Indianapolis Colts | Lamar Jackson / Daniel Jones | IND +165 | BAL 63,3% / IND 36,7% | BAL -0,1% / IND +0,1% | 3,5 | -110 | -0,2 | 47,5 | -110 | 5,6 |
| Atlanta Falcons | Pittsburgh Steelers | Michael Penix / Aaron Rodgers | PIT -170 | ATL 37,7% / PIT 62,3% | ATL -4,2% / PIT +4,2% | -3,5 | 100 | 2,0 | 41,5 | -110 | 6,9 |
| Buffalo Bills | Houston Texans | Josh Allen / C.J. Stroud | HOU +100 | BUF 47,7% / HOU 52,3% | BUF -6,9% / HOU +6,9% | 1,0 | -110 | 2,7 | 44,5 | -110 | 1,3 |
| Chicago Bears | Carolina Panthers | Caleb Williams / Bryce Young | CHI -150 | CHI 60,2% / CAR 39,8% | CHI +0,2% / CAR -0,2% | 3,0 | -105 | -0,4 | 47,0 | -110 | 3,4 |
| New York Jets | Tennessee Titans | Geno Smith / Cam Ward | TEN -125 | NYJ 43,9% / TEN 56,1% | NYJ -3,3% / TEN +3,3% | -1,5 | -110 | 0,8 | 39,5 | -110 | 20,6 |
| New Orleans Saints | Detroit Lions | Tyler Shough / Jared Goff | DET -310 | NO 21,6% / DET 78,4% | NO -5,9% / DET +5,9% | -7,0 | -105 | 3,8 | 50,0 | -110 | 4,1 |
| Arizona Cardinals | Los Angeles Chargers | Jacoby Brissett / Justin Herbert | ARI +450 | ARI 18,7% / LAC 81,3% | ARI +0,7% / LAC -0,7% | -10,0 | -105 | 2,2 | 47,0 | -110 | 4,4 |
| Miami Dolphins | Las Vegas Raiders | Malik Willis / Kirk Cousins | MIA +170 | MIA 39,9% / LV 60,1% | MIA +3,9% / LV -3,9% | -3,5 | -105 | -0,7 | 40,5 | -110 | 6,7 |
| Washington Commanders | Philadelphia Eagles | Jayden Daniels / Jalen Hurts | PHI -225 | WAS 30,2% / PHI 69,8% | WAS -5,3% / PHI +5,3% | -4,5 | -110 | 3,1 | 44,5 | -110 | 4,6 |
| Green Bay Packers | Minnesota Vikings | Jordan Love / Kyler Murray | MIN -120 | GB 49,0% / MIN 51,0% | GB -3,6% / MIN +3,6% | -1,5 | -110 | 0,5 | 46,0 | -110 | -3,9 |
| Dallas Cowboys | New York Giants | Dak Prescott / Jaxson Dart | NYG +140 | DAL 58,5% / NYG 41,5% | DAL -2,3% / NYG +2,3% | 3,0 | -110 | 0,9 | 48,0 | -110 | 8,1 |
MLB Daily Projections 09/10
| away | home | starters | market ml | imp | edge% | total | ojuice | t_edge% |
| Tampa Bay Rays | Atlanta Braves | Nick Martinez / Martín Pérez | TBR +106 | TBR 47,5% / ATL 52,5% | TBR +0,4% / ATL -0,4% | 8,5 | 104 | -9,7 |
| Houston Astros | Philadelphia Phillies | Cristian Javier / Zack Wheeler | HOU +161 | HOU 37,6% / PHI 62,4% | HOU +1,0% / PHI -1,0% | 8,5 | -104 | 3,8 |
| Texas Rangers | Seattle Mariners | Jacob deGrom / Logan Gilbert | TEX +115 | TEX 45,6% / SEA 54,4% | TEX +2,7% / SEA -2,7% | 6,5 | -124 | 1,8 |
| Colorado Rockies | New York Yankees | Ryan Feltner / Max Fried | COL +280 | COL 25,7% / NYY 74,3% | COL +3,9% / NYY -3,9% | 8,5 | -115 | 6,3 |
| Pittsburgh Pirates | Chicago White Sox | Jared Jones / Hagen Smith* | PIT -110 | PIT 50,4% / CHW 49,6% | PIT +1,2% / CHW -1,2% | 7,5 | -115 | 11 |
Other recommended US-friendly bookmakers:
Sportsbetting.ag. Everygame.eu, MyBookie
🧠 Behind the Model: From Market to Machine
We built this projection engine to mirror how modern oddsmakers think:
- Market as signal → sharp lines anchor the model
- Model as simulation → game dynamics drive probabilities
- Player input → Adjustments based on starting pitcher quality, lineup shifts, and real-world nuance
Our model is validated against closing line value and historical return on equity over multi-season datasets.
Got more questions? Check out our FAQ →
