Today's matchup
Today it's Cleveland Guardians for Sean, at home. He shows up on 6 boards — earned runs (100/100, #1), walks allowed (100/100, #1), hits allowed (93.1/100, #2), outs recorded (2.4/100, #6). We've got him at 0.9 on the earned runs board. That's one of the stronger spots on the board today. Open any board row for the full breakdown of what's driving it.
Season line
6 starts, 2-5, 3.09 ERA, 1.19 WHIP, 90.1 innings. He's struck out 84 over that span, against 34 walks. This is the baseline the matchup adjusts from — the model starts here and then asks what the specific lineup he's facing does to strikeout arms, how the park plays, and how deep he's likely to go.
He throws left-handed
Sean is a left-hander, and that matters more for a starter than it does for most hitters. Lineups get built specifically to attack lefties — managers stack right-handed bats against them — so the lineup he draws on a given night swings his projection further than a righty's would. The model prices the actual lineup rather than a season-long rate for exactly that reason. A stacked righty lineup is the spot where his strikeout projection comes down hardest.
Against Cleveland Guardians
Sean has faced Cleveland Guardians 3 times in our log — 3 strikeouts over 3.0 innings. Head-to-head history is the input people weight most and the model weights least: a handful of starts against one club tells you less than the same club's current strikeout rate against his handedness, which is what actually feeds the projection.
His last 5 starts
Sean has 9 strikeouts in 7.3 innings across his last 5 starts, a 11.0 K/9, with a 2.45 ERA over that stretch and 2 walks. Strikeouts are the one pitcher market where our model has found real, graded room — projected workload and the specific lineup he draws move that number more than a season-long rate does. Start-by-start detail is in the log below.
Strikeouts and control
Sean has 87 strikeouts and 35 walks in 93.3 innings this season — 8.4 K/9 against 3.4 BB/9, a 2.5-to-1 ratio. That's around league-typical control — enough to work deep when the lineup cooperates, not enough to bail him out of a bad matchup.
What his floor looks like
Sean has made 62 starts this season, averaging 1.5 innings with a 3.18 ERA across them. In the 12 starts we hold detailed lines for, he got through five or more innings 0 times. That ratio is the honest read on his floor, and it's what separates an arm worth projecting on the outs board from one whose good starts are unpredictable enough that the market prices them better than we do.
How long he goes
Sean is averaging 1.1 innings a start across his last 8 outings, with a high of 2.0 and about 23 pitches a night. He's not going deep, and that caps the strikeout and outs projections no matter how good the matchup looks — you can't strike out hitters you don't face. Expected batters faced is one of the bigger inputs to his score for exactly this reason.
His best start in the log
Sean's high-water mark was Saturday, September 12, 2026 at STL: 4 strikeouts over 1.3 innings, 1 earned run. One start doesn't set a projection — the model works off the blend of his recent work against the specific lineup in front of him — but it does show the ceiling when the matchup lines up.
Where he lands across our boards
Sean was scored on 6 boards in that matchup, and the spread is the interesting part: earned runs graded 100/100 while strikeouts came in at 0/100. 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
The number on Sean is about tonight, not about him. Strip out the name and the model is asking one question: what does this specific lineup do to this kind of arm, in this park, for as many batters as he's likely to face? That gets scored against every other starter on the slate. The combination math is proprietary and re-tuned every week. The grading isn't — it's all public, including the misses.
What we'd flag
Books don't price every player — coverage tops out around 87% even for confirmed starters, so "no line" here usually means no book posted one rather than a gap in our data. Lineups change late, and an afternoon projection can be stale by first pitch. And the model is tuned across hundreds of graded outcomes, so one game tells you nothing about whether it's working.