Transparency
Model Performance
Every published prediction, tracked from publication to final result. Sample history — demo data
Tracking policy: every prediction Vextiq publishes is logged when it’s published and tracked to its eventual result: pending, win, loss or push. Losing predictions are never deleted, hidden or excluded from these numbers, and graded results can’t be edited. Predictions for cancelled games are marked void and shown separately. Hit rate = wins ÷ (wins + losses).
Showing: NFL · Season · Prop · 50–59% confidence
Published
7
7 sample
Wins
3
Losses
3
All included
Pushes
0
Pending
1
Awaiting final result
Hit rate
50%
Wins ÷ (wins + losses)
Daily results & cumulative hit rate
SampleBy prediction type
SamplePending: published, awaiting result (1)
Sample| Published | Game time | Sport | Matchup | Type | Confidence | Status |
|---|---|---|---|---|---|---|
| Sep 27, 2026 | Mon, Sep 28, 3:25 PM CDT | NFL | Kansas City Chiefs vs Buffalo Bills | PROP | 53% | PENDING |
Picks stay hidden here until game time so they don’t undercut members’ access. Each one is graded here once its game is final.
Graded predictions (most recent)
Sample| Graded | Sport | Matchup | Type | Pick | Confidence | Result |
|---|---|---|---|---|---|---|
| Sep 25, 2026 | NFL | Philadelphia Eagles vs Dallas Cowboys | PROP | Marcus Sutton Under 244.5 Passing Yards | 52% | WIN |
| Sep 14, 2026 | NFL | Philadelphia Eagles vs Houston Texans | PROP | Marcus Sutton Under 244.5 Passing Yards | 52% | LOSS |
| Sep 10, 2026 | NFL | Houston Texans vs Philadelphia Eagles | PROP | Marcus Hale Under 262.5 Passing Yards | 52% | LOSS |
| Sep 6, 2026 | NFL | San Francisco 49ers vs Detroit Lions | PROP | Luca Lang Over 221.5 Passing Yards | 57% | WIN |
| Sep 3, 2026 | NFL | Dallas Cowboys vs Detroit Lions | PROP | Tyler Kane Under 244.5 Passing Yards | 53% | WIN |
| Jun 25, 2026 | NFL | Kansas City Chiefs vs Houston Texans | PROP | Player prop (sample) — Passing Yards | 55% | LOSS |
Past model performance does not guarantee future performance. Sports outcomes are unpredictable. The seeded history is SAMPLE data for demonstration and doesn’t reflect real-world results. Grading from a live data provider is prepared (lib/grading.ts) but not yet connected.
ⓘ Confidence percentages are model confidence and do not guarantee an outcome.