Last 10 games
| Defender | Games | Min | eFG% | vs Season | Sample |
|---|---|---|---|---|---|
| Keyonte George | 3 | 8 | 33% | -6.6% | medium |
| Jamal Murray | 2 | 7 | 71% | +17.2% | low |
| Brandon Williams | 2 | 7 | 43% | +3.0% | low |
| Collin Gillespie | 3 | 6 | 0% |
De'Anthony Melton is running hotter than his season baseline, with 17.8 PPG over the last 5 and 17.2 over the last 10 versus a 12.9 season average. Even so, the trend label is down and his game log shows volatility, including 5 points in his most recent outing after a 27-point game two nights earlier. Detroit’s defense data is not an elite scoring environment, but his head-to-head line is still much lower at 7.75 PPG across 12 games, which supports a more cautious projection than the recent stretch suggests.
Detroit’s opponent defense data shows a 109.87 defensive rating with pace at 100, and no specific defender matchup data is provided. The head-to-head sample is notable because he has averaged only 7.75 points in 12 games against this opponent, which is a strong caution flag for overs.
| Player | Prop | Line | Pick | Confidence | ML | Trend | Actual | Result |
|---|---|---|---|---|---|---|---|---|
De'Anthony Melton▼ | Points | 14.5 | UNDER | 67%MEDIUM | 2/2 | 40% | 14 | ✓ |
De'Anthony Melton▼ | Rebounds | 3.5 | UNDER | 63%MEDIUM | 2/2 | 40% | 4 | ✗ |
De'Anthony Melton▼ | Assists | 2.5 | UNDER | 61%MEDIUM | 2/2 | 60% | 0 | ✓ |
De'Anthony Melton▼ | 3PM | 1.5 | UNDER | 58%MEDIUM | 2/2 | 30% | 2 | ✗ |
De'Anthony Melton▼ | Steals | 1.5 | UNDER | 66%MEDIUM | 2/2 | 60% | 0 | ✓ |
De'Anthony Melton▼ | Blocks | 0.5 | UNDER | 72%HIGH | — | 60% | 1 | ✗ |
De'Anthony Melton▼ | STL+BLK | 3 | UNDER | 55%MEDIUM | — | 80% | 1 | ✓ |
De'Anthony Melton▼ | P+A | 16.5 | UNDER | 59%MEDIUM | 2/2 | 40% | 14 | ✓ |
De'Anthony Melton▼ | P+R | 17.5 | UNDER | 60%MEDIUM | 1/2 | 40% | 18 | ✗ |
This is the cleanest angle because the season mean is 12.9, the head-to-head average is 7.75 across 12 games, and the value data shows positive EV on the under at multiple books. His recent 17.8 PPG is hotter than baseline, but the most recent game was a 5-point outing, so regression is a real concern.
| medium |
| Tyrese Maxey | 2 | 5 | 44% | +4.5% | low |
| Defender | Games | Min | PTS | FG% | eFG% |
|---|---|---|---|---|---|
| Daniss Jenkins | 2 | 4 | 4 | 33% | 33% |
| Cade Cunningham | 1 | 3 | 8 | 75% | 88% |
| Duncan Robinson | 2 | 2 | 0 | 0% | 0% |
| Ausar Thompson | 2 | 2 | 0 | 0% | 0% |
| Jaden Ivey | 1 | 2 | 2 | 0% | 0% |
Season mean is 12.9 and the value data shows UNDER edge at 14.5 with multiple books. His recent 17.8 PPG is well above season average, but the last game was only 5 points and his vs-opponent mark is 7.75 PPG across 12 games.
He averages 3.0 rebounds for the season and 3.7 over the last 5, but the recent bump is modest relative to the line. The value table also favors UNDER at 3.5.
His season assist mean is 2.4, right below the line, and his away mean is only 2.0. Recent production is 2.5, but the edge data and his usual distribution both point slightly lower.
He averages 1.51 made threes on the season, so this is essentially a coin flip, but the value data leans UNDER at 1.5. The under is also supported by a lower away mean of 1.25.
Season steals are 1.6, but the line is inflated at 1.5 and his value props point to UNDER. With a season standard deviation of 1.28 in stocks-related production, this still carries some volatility.
He averages just 0.4 blocks per game, below the line, and there is no need to force an over on a low-frequency stat. The season profile supports the under.
Using his season averages, steals plus blocks come out to 2.0, but this combo is volatile and his recent 2.6 last 5 is inflated by a small sample. Given the variance, this is a lean rather than a strong play.
Points plus assists projects below this number based on 12.9 points and 2.4 assists season averages. Recent form is stronger, but combo props are higher-variance and should be treated conservatively.
His season points plus rebounds average is 15.92, and the last 5 surge does not fully justify the jump. The value data and head-to-head scoring history both support a lower projection.