The math behind the line.
Mongoose Bets runs 2,500 Monte Carlo simulations per MLB game to expose where sportsbook lines disagree with the model. No tipster picks. No black-box scores. We show our work.
What is Monte Carlo simulation?
Monte Carlo simulation is a way to estimate the probability of an outcome by playing it out thousands of times with realistic randomness. Instead of asking "will the Yankees win tonight?" a Monte Carlo model asks "if we played this game 2,500 times under tonight's exact conditions, how often would the Yankees win?"
Baseball is a near-perfect fit for this approach. Every plate appearance is a discrete event with a measurable probability distribution (this batter against this pitcher, with this defense, in this park, in this weather). Stack 9 innings of those events, run the whole game 2,500 times, and you get a real probability distribution — not a single guess.
What the model ingests, every game
Each of the 2,500 simulations per game runs batter-by-batter, inning-by-inning, with these inputs feeding every plate-appearance probability:
Pitcher quality & pitch mix
ERA, WHIP, K/9, BB/9, HR/9, handedness splits, recent form.
Batter splits & BvP history
Season stats, vs LHP/RHP splits, career line against the opposing pitcher (sample-weighted).
Park factors
Coors Field plays nothing like Oracle Park. HR rate, hit rate, and run scoring all park-adjusted.
Weather (live forecast at first pitch)
Wind speed, direction, temperature, humidity. A 15 mph wind blowing out at Wrigley changes everything.
Home plate umpire
Strike zone size, K%, BB%, runs/game tendency — built into game-level scoring expectations.
Bullpen fatigue & quality
Pitches thrown last 3 days, leverage availability, reliever quality once the starter exits.
From probability to edge
A probability edge is the model probability minus a stated market reference probability, measured in percentage points. The reference may be the raw implied probability of the offered odds or a vig-free market estimate; check the board’s label. A gap against a vig-free reference alone does not establish positive expected value at the price you can actually take.
Offered odds of +140 imply a breakeven probability of 41.67%. Removing vig requires the prices for the other outcomes and a stated method; you cannot infer a vig-free probability from one side alone. A vig-free estimate is a market reference, not the breakeven probability of the offered price.
For a win-or-lose bet with no push, expected return on stake is model probability × decimal odds − 1. Multiply by 100 to express it as EV%. A bet is positive EV under the model only when its probability exceeds the breakeven probability of the offered odds. The estimate depends on the model being accurate; it is not a guaranteed profit.
Worked example
Illustrative example, not a current pick: suppose a model gives a home run a 38% probability and the offered price is +320 (decimal odds 4.20).
The raw breakeven probability is 1 ÷ 4.20 = 23.81%. The model is 14.19 percentage points above that threshold; this is a probability gap, not EV%.
Expected return on stake = 0.38 × 4.20 − 1 = 0.596, or +59.6%. On a $100 stake that is $59.60 of expected profit under the model, with no guarantee of the outcome.
Counterexample: a 28.4% model probability at +140 (decimal 2.40) gives 0.284 × 2.40 − 1 = −31.84% expected return. It remains negative EV even if that model probability exceeds a separate vig-free reference of 23.1%.
Check an offered price in the EV calculatorThe Best Bets page shows model estimates alongside available prices across DraftKings, FanDuel, BetMGM, and other major books. Kelly Criterion sizing is also computed so you can manage the edge against your bankroll.
Galaxy Insight: see the disagreement
Most analytics tools collapse a sim to a single number ("Yankees 63% to win") and call it a day. We plot all 2,500 sim outcomes as points on the joint score distribution — the Sim Outcome Galaxy. You can literally see where the cluster of likely outcomes lands relative to the book's lines.
When the cluster sits firmly to one side of the total runs line, that's the edge made visible. No formula necessary — the picture is the math.
What Mongoose is not
We're not a tipster.
We don't sell picks at $49 a pop. We show the math behind every edge so you can decide.
We're not a black box.
Every prop has its sim probability, the book's implied probability, and the resulting EV visible on the page.
We're not a thin everything-sport tool.
MLB, NFL, CFB, NHL, NBA, WNBA, and PGA each run on their own model. We add a sport when we can model it properly, not to pad the list.
We're not a sportsbook.
We tell you where the edge is. You place the bet on whichever book is offering the best line.
Common questions
What is Monte Carlo simulation in sports betting?+
Monte Carlo simulation estimates the probability of an outcome by playing it out thousands of times with realistic randomness. For MLB, Mongoose Bets runs 2,500 simulations per game using player and matchup inputs, then aggregates the outcomes into model win probabilities, predicted scores, and player projections.
How does Mongoose Bets find +EV bets?+
For a win-or-lose bet with no push, expected return on stake is model probability × decimal odds − 1. Multiply by 100 to express it as EV%. A bet is positive EV under the model only when its probability exceeds the breakeven probability of the offered odds. The estimate depends on the model being accurate; it is not a guaranteed profit.
Why does Mongoose simulate 2,500 times per game (and not more)?+
At a model probability of 50%, 2,500 independent simulations have a Monte Carlo standard error of about 1 percentage point and an approximate 95% sampling interval of ±1.96 percentage points. This measures simulation noise conditional on the model, not predictive accuracy. More simulations reduce sampling noise; they do not fix incorrect inputs or model assumptions.
How is Mongoose different from tipster sites and DFS optimizers?+
Mongoose models baseball games from player and matchup inputs, then publishes probabilities and projections alongside sportsbook prices. Its DFS tools use those player projections for lineup research. Model output lets you inspect the assumptions behind a selection, but does not by itself demonstrate a profitable betting strategy.
What does "edge" mean in MLB betting?+
A probability edge is the model probability minus a stated market reference probability, measured in percentage points. The reference may be the raw implied probability of the offered odds or a vig-free market estimate; check the board’s label. A gap against a vig-free reference alone does not establish positive expected value at the price you can actually take.
Does Mongoose Bets accept wagers?+
No. Mongoose Bets is an analytics and research platform, not a sportsbook. It publishes model estimates and sportsbook-price comparisons; it does not accept or settle wagers.
Original research & comparisons
Research · April 20, 2026
13 Days, 8,742 Edges: Mapping MLB Prop Market Mispricings
Every +EV opportunity our model flagged in the first three weeks of the 2026 season — broken down by bet type, sportsbook, edge size, and odds tier. 64 games, 460 players, eight sportsbooks.
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What each tab does
The ten-second map of the site. Every tab also has its own ⓘ Methodology button with the full story.
Games
Every game simulated before first pitch — win odds, projected scores, and where the books look wrong.
Prop Central
Every player prop with live odds, sim probability, and model edge — the whole board, sortable.
HR Zone
Every hitter scored 0–100 for home run potential, re-priced live as the odds move.
CheatSheets
Done-for-you sheets: the model's strongest plays for each market, rebuilt daily.
Live Results
Every published pick graded against what actually happened — wins and misses alike.
Player Research
Leaderboards, matchups, streaks, and full player profiles in one hub.
DFS Lab
FanDuel + DraftKings salaries, sim projections, ownership, and a lineup optimizer.
Value Bets
Games ranked by the size and count of sim-vs-book mispricings.
Bullpen
Reliever workloads and rest days — which bullpens are gassed tonight.
NRFI
First-inning sim probabilities and the pitcher matchups behind them.
My Tracked Bets
Your saved bets, graded automatically as games go final, with running P&L.
See the math in action
Today's biggest edges
Every value bet on tonight's MLB slate, ranked by sim-derived expected value.
Or browse
Tonight's MLB games
Win probabilities, predicted scores, and the Sim Outcome Galaxy for every game on the board.
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