Not on the current slate
Samuel hasn't been scored in 15 days — his last matchup was against Toronto Blue Jays on Wednesday, September 23, 2026. A gap that long usually means an injury, a minor-league option, or a roster move rather than a rest day. Everything below is his most recent real production, not a projection.
He's in a cold stretch
Samuel is 4-for-29 (.138) across his last 10 games, down from .219 on the season. Slumps this size are mostly noise at this sample — 29 at-bats is a fortnight, not a trend — and the model treats it that way, discounting the cold run rather than writing him off. If the matchup underneath is good, he'll still grade well here. That's a feature, and sometimes it's wrong.
What kind of hitter he is
Samuel has 18 home runs and 27 extra-base hits in 347 at-bats this season. That profile is why he grades better on the total-bases and home-run boards than his batting average alone would suggest — those boards reward damage, not just contact. Park and weather matter more for a hitter like him too, and both feed the score.
He's a left-handed bat
Samuel hits from the left side, and that's the first thing the model looks at. Left-handed hitters see right-handed pitching most nights, which is the favourable side — so a lefty bat's baseline is set against righties, and drawing a left-handed starter is a genuine downgrade rather than a rounding error. When you see his score fall on a day he's still in the lineup, an opposing lefty is usually why. Handedness also shapes the park read: pull-side geometry matters more for a left-handed swing than the raw park factor suggests.
Floor and ceiling
Samuel has recorded at least one hit in 56 of 104 games he's batted in — 54% — with 18 multi-hit games among them. That's a boom-or-bust profile. He'll carry a game outright and then go quiet for three, so his hits-board score tends to sit below hitters with worse power and better contact.
Home and away
Samuel is hitting .236 at home (43-for-182) and .200 on the road (33-for-165) across the season. There's not much in it, which is the normal case. Home-road splits get talked about far more than they hold up.
Against Toronto Blue Jays
Samuel is 1-for-9 (.111) against Toronto Blue Jays in our log, over 4 games. Worth knowing, worth not over-reading. 9 at-bats against one club is a tiny sample, and the model treats it as a minor input next to what that pitching staff actually allows to his handedness. Batter-versus-pitcher history is the most quoted number in baseball and one of the least predictive.
His best game in the log
Samuel's biggest night was Wednesday, September 16, 2026 at NYM — 2-for-4 with 1 homer, 2 driven in. That's the ceiling, not the expectation. The projection you'll see on a board is closer to his typical game than his best one, which is the whole point of projecting rather than remembering.
How our calls on Samuel have graded
In the 7 games where we ranked Samuel a top-20 hitter matchup, he recorded a hit 4 times — 57%. That's a thin sample and we'd treat it as such. Every one of those calls was graded against the real box score, misses included.
Where he lands across our boards
Samuel was scored on 12 boards in that matchup, and the spread is the interesting part: rbis graded 47.7/100 while stolen bases came in at 1.2/100. Same player, same game, same opposing arm — different questions. A spread that wide usually means the matchup favours one kind of outcome over another, and it's the clearest argument for reading the board that matches what you actually care about.
How the model reads him
Samuel gets scored the same way a backup infielder does — same inputs, same scale, no thumb on it. What he's done against arms of this handedness, what this particular pitcher and bullpen give up, his likely plate appearances, the ballpark, the conditions, his recent form. The weighting behind those is ours and gets re-tuned weekly against what actually happened. The output is public and graded, which is the only claim worth making.
What we'd flag
Read this page knowing what it can't do. It can't show you a line no book posted — coverage peaks around 87% for confirmed starters. It can't see a lineup change that happens after the projection publishes. And it can't tell you anything useful from one game, because the model is only measurable across a season-sized sample.