Today's matchup
Cam draws Toronto Blue Jays on the road today. He shows up on 6 boards — outs recorded (91.7/100, #10), walks allowed (81.4/100, #3), fantasy points (65.3/100, #6), strikeouts (50.8/100, #7). We've got him at 17.1 on the outs recorded 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
25 starts, 10-6, 2.21 ERA, 0.93 WHIP, 146.2 innings. He's struck out 182 over that span, against 31 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 right-handed
Cam throws right-handed, which is the ordinary case and means fewer wild swings in the lineup he faces. Opposing managers aren't restacking against him the way they would a left-hander, so his projection moves more on the quality of the lineup than on its handedness. What does move it: how deep he's been going lately, and whether the lineup in front of him strikes out.
His last 5 starts
Cam has 45 strikeouts in 28.0 innings across his last 5 starts, a 14.5 K/9, with a 2.89 ERA over that stretch and 6 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
Cam has 182 strikeouts and 31 walks in 146.7 innings this season — 11.2 K/9 against 1.9 BB/9, a 5.9-to-1 ratio. That's strong control, and it does more for his projection than the raw strikeout number does. Walks are the fastest way to shorten a start — an arm that doesn't issue them gets deeper into games, which is what the outs and strikeout lines are really pricing.
What his floor looks like
Cam has made 25 starts this season, averaging 5.9 innings with a 2.21 ERA across them. In the 12 starts we hold detailed lines for, he got through five or more innings 9 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
Cam is averaging 5.8 innings a start across his last 8 outings, with a high of 8.0 and about 94 pitches a night. He's going deep enough that the outs and strikeout lines stay live into the seventh, which is where most of the value on those boards sits. Expected batters faced is one of the bigger inputs to his score for exactly this reason.
His best start in the log
Cam's high-water mark was Friday, June 19, 2026 against CIN: 13 strikeouts over 6.0 innings, 0 earned runs. 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
Cam was scored on 6 boards in that matchup, and the spread is the interesting part: outs recorded graded 91.7/100 while hits allowed came in at 30.2/100. 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
Cam's score comes from the matchup, not his reputation. The model weighs how the opposing lineup handles his handedness, how many batters he's likely to face given recent workload, the park, and the weather — then normalizes 0–100 against every other arm on the slate. How those factors are weighted is our own, and it re-tunes weekly against real outcomes. We publish the score and grade it in public; that's the half you can check.
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.