Predict outcomes.
Not noise.
AI-driven sports outcome modeling built on data, discipline, and probability.
What Snark Does
Probability-calibrated sports outcome modeling. No hype, no promises.
Probability-First
Every prediction comes with calibrated confidence intervals, not false certainty.
Market-Aware
Line movement and market sentiment factored into every signal output.
Clear Uncertainty
We tell you when we don't know. Volatility and unknowns are explicitly flagged.
The Model
Built on historical data, real-time signals, and continuous calibration. Every output comes with context about what drove it and how certain we are.
Injury Weighting
Player availability cascades through lineup projections, adjusting expected performance dynamically.
Line Movement Sensitivity
Real-time tracking of market shifts to identify when consensus diverges from model expectations.
Recency & Volatility
Recent performance weighted against historical baselines, with volatility scores for unstable matchups.
Calibration Bands
Confidence percentages are calibrated against historical accuracy to ensure stated probability reflects reality.
Example data for illustration only
Live Signals
Real-time probability estimates with confidence bands and volatility flags.
NYK vs BOS
Updated 2 min ago
LAL vs GSW
Updated 5 min ago
MIA vs PHI
Updated 1 min ago
DEN vs PHX
Updated 8 min ago
MIL vs CLE
Updated 3 min ago
DAL vs MIN
Updated 6 min ago
Example preview — live feed shown in product
Our Approach
Sports outcomes are uncertain. Any system claiming otherwise is misleading you. We build models that embrace uncertainty, quantify confidence, and update continuously.
No hype. No guaranteed wins. No insider secrets. Just probability estimates derived from data, with full transparency about methodology and historical performance.
We believe better decisions come from honest information, not false confidence. That's why every output includes what we don't know alongside what we do.
Principles
- 1Model outputs are probabilities, not predictions of certain outcomes.
- 2Uncertainty is a feature, not a bug — we show what we don't know.
- 3No cherry-picked results. All historical performance is available.
- 4Independent analysis. We don't take positions or have conflicts.
- 5Continuous calibration against real-world outcomes.
Frequently Asked Questions
Clear answers about what Snark is and isn't.
No. Snark provides probabilistic outcome modeling for informational and educational purposes only. We do not recommend, encourage, or facilitate any betting activity. How you use this information is entirely your decision and responsibility.
Currently, we focus exclusively on NBA. We may expand to other sports in the future based on data quality and model reliability.
Signals update continuously as new data becomes available — typically every few minutes during active periods. Major factors like injury reports trigger immediate recalculation.
A volatile flag indicates that recent data is shifting the model's output significantly. This could be due to breaking news, unusual line movement, or conflicting signals. It suggests higher uncertainty than the confidence number alone indicates.
A 70% confidence means the model expects that outcome to occur roughly 70 times out of 100 similar situations. It's not a guarantee — a 70% chance still means 30% of the time, the other outcome occurs. We calibrate these percentages against historical accuracy.
Yes. We publish full historical records of model outputs and actual outcomes. Transparency about past performance — including misses — is core to our approach.
Because uncertainty is fundamental to sports outcomes. Any system claiming guaranteed results is misleading you. Our goal is accurate probability estimation, not impossible certainty.