The biggest divergence on today’s board is Bank of America earnings: Polymarket implies 82% for a beat, while our model sits at 44%. That is a 38-point gap concentrated around a very tight EPS strike, where even small estimate drift can flip resolution outcomes.
- The largest gaps are in contracts with tight thresholds where consensus sits at or just below the strike.
- In late-cycle bank earnings setups, estimate revisions and threshold design matter more than headline momentum.
- In sports, lineup uncertainty and fixture congestion can create pricing lags, especially near playoff or cup inflection points.
- In Hungary, opposing poll ecosystems imply wider uncertainty bands than a single-point market quote suggests.
5 Mispricings at a Glance
| Event | Polymarket | Naly AI | Gap | Confidence | Why We Disagree |
|---|---|---|---|---|---|
| Bank of America earnings beat | 82% | 44% | -38pp | 78% | Consensus near/below strike and recent estimate softening make the “beat” bar less forgiving than market pricing implies. |
| Wells Fargo earnings beat | 84% | 47% | -37pp | 76% | Expected EPS clustered around the strike leaves little cushion; late estimate mix does not justify very high beat odds. |
| Hurricanes vs. Utah | 46% | 64% | +18pp | 77% | Team quality edge is real, but late rest decisions create uncertainty the market may be over-penalizing. |
| Fidesz-KDNP seat outcome | 40% | 24% | -16pp | 80% | Independent projections imply lower Fidesz seat ceilings; market may underweight anti-incumbent momentum. |
| Sevilla vs. Atlético Madrid | 39% | 57% | +18pp | 69% | Relative team strength and Sevilla stress context favor Atlético more than current market pricing. |
Will Bank of America (BAC) beat quarterly earnings?
Consensus near/below strike and recent estimate softening make the “beat” bar less forgiving than market pricing implies.
Causal Chain
Key Factors
| Factor | |
|---|---|
| Report timing is fixed for April 15, reducing event-date uncertainty. | |
| Consensus snapshots near 0.99 create a razor-thin cushion versus the strike. | |
| Recent revision direction has been negative rather than positive. | |
| Prior-quarter strength included market-sensitive businesses that are not always stable quarter to quarter. | |
| High implied odds leave little margin for normal estimate error. |
Bayesian Calculation
Alternative explanation: The market may be correctly anticipating a late pre-release expectation reset followed by an upside surprise from markets and fee lines, which would make the current high beat probability rational.
Fresh Checks
Will Wells Fargo (WFC) beat quarterly earnings?
Expected EPS clustered around the strike leaves little cushion; late estimate mix does not justify very high beat odds.
Causal Chain
Key Factors
| Factor | |
|---|---|
| Earnings release timing is confirmed for April 14. | |
| Public estimate trackers place expected EPS roughly at the strike level. | |
| Tight threshold contracts typically require clear positive revision momentum to justify very high yes pricing. | |
| Prior beats do not always transfer when hurdle design tightens. | |
| Market odds may overweight beat-history narratives versus threshold math. |
Bayesian Calculation
Alternative explanation: If management has unusually strong fee growth and credit normalization this quarter, the narrow strike concern may prove less relevant than expected.
Fresh Checks
Hurricanes vs. Utah
Team quality edge is real, but late rest decisions create uncertainty the market may be over-penalizing.
Causal Chain
Key Factors
| Factor | |
|---|---|
| Carolina recently clinched the Metropolitan Division title. | |
| Hurricanes season record and underlying form remain strong. | |
| Official preview flagged multiple stars as recently rested with game-time status decisions. | |
| Utah enters competitive and motivated, adding volatility. | |
| Market may be over-discounting Carolina’s depth quality when pricing uncertainty. |
Bayesian Calculation
Alternative explanation: Because playoff seeding is largely secured, Carolina may prioritize health over result, effectively lowering true win probability more than season-long metrics suggest.
Fresh Checks
# of seats won by Fidesz-KDNP in Hungary parliamentary election?
Independent projections imply lower Fidesz seat ceilings; market may underweight anti-incumbent momentum.
Causal Chain
Key Factors
| Factor | |
|---|---|
| Multiple recent reports describe Tisza leading in independent polling sets. | |
| Seat projections in some recent analyses imply materially lower Fidesz seat totals. | |
| Large anti-government mobilization events suggest turnout intensity risk for incumbents. | |
| Pollster dispersion is wide, so uncertainty remains non-trivial. | |
| Electoral-system structure can still cushion incumbents in close races. |
Bayesian Calculation
Alternative explanation: Government-aligned polling could be closer to true turnout composition than independent polls, especially if older/rural participation dominates election-day behavior.
Fresh Checks
Sevilla FC vs. Club Atlético de Madrid
Relative team strength and Sevilla stress context favor Atlético more than current market pricing.
Causal Chain
Key Factors
| Factor | |
|---|---|
| Match context reports Sevilla in urgent points-needed mode after poor run. | |
| Atlético has external priorities (cup/European schedule), introducing rotation risk. | |
| Sevilla injury/availability updates include defensive uncertainty. | |
| Historical quality differential still favors Atlético over a single-game sample. | |
| Market likely overweights spot-fatigue narratives relative to structural strength gap. |
Bayesian Calculation
Alternative explanation: Sevilla’s urgency plus home crowd and Atlético’s upcoming high-priority fixtures could produce a lower-intensity away setup than season averages imply.
Fresh Checks
Methodology
We start from market-implied priors, update with fresh public information, then apply threshold-aware Bayesian adjustments that emphasize resolution mechanics over headlines. Full calibration and historical scoring are published at Naly Track Record.
Disclaimer
This analysis is for informational purposes only and is not investment, betting, or financial advice. Forecasts are probabilistic, may change with new information, and can be wrong.