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Tutorials
Guided, step-by-step walkthroughs for every lab and core concept. Each tutorial links to the lab it teaches so you can follow along. Everything here is educational and synthetic — no picks, no wagers.
How Novus Odds simulations work
The end-to-end mental model: a seeded RNG, a synthetic price, an underlying true probability, and thousands of resolved events.
4 steps →
Reading a Novus breakdown
Decode edge, EV, vig, ROI, and drawdown — the shared vocabulary behind every lab panel.
4 steps →
Run your first Odds Lab experiment
Configure a synthetic two-outcome market, pick a selection filter, and read the buckets, equity curve, and discrepancy panel.
4 steps →
Compare staking strategies in Strategy Lab
Hold the market tape fixed and swap only the stake rule to isolate progression risk — flat, edge, hot-streak, Martingale, and more.
4 steps →
Compare de-vig methods in Model Comparison
See how proportional, power, Shin, odds-ratio, and additive margin removal produce different fair lines from the same prices.
4 steps →
Model a player prop distribution
Build a fictional scoring distribution, sweep the line, and find where expected value crosses zero at a fixed juice.
4 steps →
Simulate a matchup, soccer 1X2, or a field
Rate two teams, price a three-way soccer market, or generate a multi-runner board — and read fair vs priced markets.
4 steps →
Read a horse field's four probabilities
Understand raw implied, margin-adjusted, underlying model, and observed frequency for every runner in a synthetic field.
4 steps →
Calibrate a sport adapter
Run any sport adapter and confirm its observed win rates land inside the Wilson interval around the model probabilities.
4 steps →
Understand the Repeated Price experiment
Why a price with a high chance of at least one win can still have a most-likely outcome that loses units.
4 steps →
Explore house edge in the Casino Lab
Quantify why casino games are structurally negative for the player, and how staking interacts with a fixed edge.
4 steps →
Generate a synthetic dataset
Build fictional seasons of teams and games, then export aggregates and sample rows for offline study.
4 steps →
Read the discrepancy detector
Tell observable market structure apart from look-ahead signals that only exist because this is a simulation.
4 steps →
How deterministic replay works
Why the replay timeline is reproducible, and why the animation never determines the result.
3 steps →