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 2 projections

awayhomequarterbacksmarket mlimpml edge%spreadspr pricespr edgetotalojuicet_edge
Detroit LionsBuffalo BillsJared Goff / Josh AllenDET +190DET 32,3% / BUF 67,7%DET +3,2% / BUF -3,2%-4,5-110-0,654-1100,8
Green Bay PackersNew York JetsJordan Love / Geno SmithGB -185GB 63,1% / NYJ 36,9%GB +3,6% / NYJ -3,6%4100-1,444,5-1102,5
Minnesota VikingsChicago BearsCarson Wentz / Caleb WilliamsMIN +210MIN 30,6% / CHI 69,4%MIN +2,1% / CHI -2,1%-5,5-110-0,548,5-110-0,4
Pittsburgh SteelersNew England PatriotsAaron Rodgers / Drake MayePIT +200PIT 30,6% / NE 69,4%PIT +5,3% / NE -5,3%-5-110-1,441,5-1100,8
Carolina PanthersAtlanta FalconsBryce Young / Michael PenixATL +120CAR 54,1% / ATL 45,9%CAR -10,2% / ATL +10,2%2,5-1103,743,5-1102,5
Cleveland BrownsTampa Bay BuccaneersDeshaun Watson / Baker MayfieldCLE +375CLE 18,5% / TB 81,5%CLE +2,8% / TB -2,8%-8,5-1100,641-1103,9
Cincinnati BengalsHouston TexansJoe Burrow / C.J. StroudHOU -145CIN 43,3% / HOU 56,7%CIN -4,4% / HOU +4,4%-2,5-1101,746,5-1100,4
New Orleans SaintsBaltimore RavensTyler Shough / Lamar JacksonBAL -420NO 17,9% / BAL 82,1%NO -1,6% / BAL +1,6%-8,5-110347-1100,9
Philadelphia EaglesTennessee TitansJalen Hurts / Cam WardPHI -320PHI 74,9% / TEN 25,1%PHI +3,7% / TEN -3,7%7100-3,239-1102,8
Las Vegas RaidersLos Angeles ChargersKirk Cousins / Justin HerbertLAC -300LV 24,4% / LAC 75,6%LV -3,1% / LAC +3,1%-6,5-1102,243,5-110-0,5
Jacksonville JaguarsDenver BroncosTrevor Lawrence / Bo NixJAC +130JAC 42,9% / DEN 57,1%JAC +3,1% / DEN -3,1%-2,5-120-0,845,5-110-0,6
Washington CommandersDallas CowboysJayden Daniels / Dak PrescottWAS +190WAS 33,5% / DAL 66,5%WAS +3,8% / DAL -3,8%-4-110-0,350,5-1105,5
Seattle SeahawksArizona CardinalsSam Darnold / Jacoby BrissettSEA -215SEA 67,8% / ARI 32,2%SEA +3,5% / ARI -3,5%4,5-110-1,941-1102,5
Miami DolphinsSan Francisco 49ersMalik Willis / Brock PurdyMIA +675MIA 10,5% / SF 89,5%MIA +2,9% / SF -2,9%-13-1101,245,5-1103,1
Indianapolis ColtsKansas City ChiefsDaniel Jones / Patrick MahomesKC -300IND 24,7% / KC 75,3%IND -1,5% / KC +1,5%-6,5-1051,546,5-1102,2
New York GiantsLos Angeles RamsJaxson Dart / Matthew StaffordLAR -340NYG 23,9% / LAR 76,1%NYG -1,6% / LAR +1,6%-7-105248-1100,6

MLB Daily Projections 09/16

awayhomestartersmarket mlimpedge%totalojuicet_edge%
Chicago White SoxCleveland GuardiansAnthony Kay / Parker MessickCHW +150CHW 38,7% / CLE 61,3%CHW +1,3% / CLE -1,3%7,5-115-5,6
San Francisco GiantsSt. Louis CardinalsAnthony Molina* / Matthew LiberatoreSFG +135SFG 41,1% / STL 58,9%SFG +0,2% / STL -0,2%8,5115-6,4
New York YankeesMinnesota TwinsCarlos Rodón / Zebby MatthewsMIN +127NYY 57,0% / MIN 43,0%NYY -4,4% / MIN +4,4%7,5-12010,9
Detroit TigersToronto Blue JaysKeider Montero / Max ScherzerDET +111DET 46,7% / TOR 53,3%DET +2,4% / TOR -2,4%8,5100-1,3
AthleticsTampa Bay RaysBrady Basso / Nick MartinezATH +161ATH 37,2% / TBR 62,8%ATH +2,1% / TBR -2,1%7,5-1343,6
Milwaukee BrewersPittsburgh PiratesLogan Henderson / Jared JonesPIT +119MIL 55,4% / PIT 44,6%MIL -4,1% / PIT +4,1%7,5-1044,8
Los Angeles DodgersCincinnati RedsBlake Snell / Andrew AbbottCIN +178LAD 64,6% / CIN 35,4%LAD -4,1% / CIN +4,1%8,5-1041,8
Philadelphia PhilliesWashington NationalsZack Wheeler / Jared SimpsonWSN +170PHI 63,3% / WSN 36,7%PHI -4,2% / WSN +4,2%8,5-1073,2
Baltimore OriolesNew York MetsChris Bassitt / Robert StockNYM -134BAL 43,8% / NYM 56,2%BAL -2,2% / NYM +2,2%8,5-1151,8
Atlanta BravesChicago CubsJR Ritchie / Shota ImanagaCHC -136ATL 44,1% / CHC 55,9%ATL -0,2% / CHC +0,2%7,5-120-1
Boston Red SoxTexas RangersJake Bennett / MacKenzie GoreTEX -104BOS 49,5% / TEX 50,5%BOS -0,9% / TEX +0,9%7,5-1201,2
Kansas City RoyalsHouston AstrosDaniel Lynch IV / Cristian JavierKCR +125KCR 43,4% / HOU 56,6%KCR +0,9% / HOU -0,9%8,5-1150,4
San Diego PadresColorado RockiesRobbie Ray / Mason AdamsCOL +150SDP 60,9% / COL 39,1%SDP -6,3% / COL +6,3%11,5104-9
Seattle MarinersLos Angeles AngelsGeorge Kirby / Yusei KikuchiLAA +118SEA 54,9% / LAA 45,1%SEA -1,5% / LAA +1,5%7,5-1258,6
Miami MarlinsArizona DiamondbacksRyan Gusto / Merrill KellyARI -126MIA 45,3% / ARI 54,7%MIA -1,1% / ARI +1,1%9,5116-1

Other recommended US-friendly bookmakers:
Sportsbetting.agEverygame.euMyBookie

🧠 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 →

An oddsmaker and data analyst working on sports betting projections using dual monitors and machine learning code.