Today's matchup
Garrett draws San Diego Padres on the road today. He shows up on 12 boards — triples (66.4/100, #5), walks (59.2/100, #7), hits (56.8/100, #15), singles (56.6/100, #12). We've got him at 0 on the triples board. Open any board row for the full breakdown of what's driving it.
He's in a cold stretch
Garrett is 7-for-35 (.200) across his last 10 games, down from .265 on the season. Slumps this size are mostly noise at this sample — 35 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
Garrett has 10 home runs and 44 extra-base hits in 442 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
Garrett 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
Garrett has recorded at least one hit in 74 of 130 games he's batted in — 57% — with 32 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
Garrett is hitting .300 at home (63-for-210) and .233 on the road (54-for-232) across the season. That's a real-looking split, and it's the kind of thing that's usually part park and part noise. The model doesn't apply a blanket home-road adjustment — it prices the actual ballpark he's standing in, which is the part that carries signal.
Against San Diego Padres
Garrett is 2-for-11 (.182) against San Diego Padres in our log, over 3 games. Worth knowing, worth not over-reading. 11 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.
How our calls on Garrett have graded
In the 13 games where we ranked Garrett a top-20 hitter matchup, he recorded a hit 9 times — 69%. 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
Garrett was scored on 12 boards in that matchup, and the spread is the interesting part: triples graded 66.4/100 while stolen bases came in at 21.1/100. 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
Garrett 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.