Prediction Results & Track Record
Every pick we publish is recorded here, win or loss, with no hidden removals or selective reporting. Full transparency is essential in sports predictions because anyone can claim a winning record without proof. This page is that proof. Use the filters below to break down performance by sport, pick type, confidence tier, or date range. Our picks are generated by a machine learning model trained on historical game data, team statistics, and situational factors. For a deeper look at how the model works, visit How It Works.
Record
3-3-0
50.0%
O/U 2-1-0 66.7%
ML 1-2-0 33.3%
Risked
$2,420
22u
Net P&L
+$226
ROI
+9.3%
Pick History 6
| Date | Sport | Matchup | Type | Pick | Line | Conf | Units | W/L | P&L |
|---|---|---|---|---|---|---|---|---|---|
| Apr 6 | ncaab | UConn @ Michigan 63-69 | TOTAL | Over | 144.5 (to 163.6) | | 5u | L | -$550 |
| ‹ same game › | ML | UConn | +240 | | 1u | L | -$110 | ||
| Apr 5 | ncaab | Tulsa @ Auburn 86-92 | TOTAL | Over | 160.5 (to 167.5) | | 4u | W | +$400 |
| ‹ same game › | ML | Tulsa | +195 | | 4u | L | -$440 | ||
| Apr 5 | ncaab | Oklahoma @ West Virginia 82-89 | TOTAL | Over | 137.5 (to 151.2) | | 5u | W | +$500 |
| ‹ same game › | ML | West Virginia | +142 | | 3u | W | +$426 |