Today's matchup
Today it's Atlanta Braves for Andrew, at home. He shows up on 12 boards — singles (91.6/100, #3), hits (79.1/100, #19), h+r+rbi (62.4/100, #34), rbis (52.8/100, #39). We've got him at 0.7 on the singles 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
0 starts, 0-0, 27.00 ERA, 5.00 WHIP, 1.0 innings. He's struck out 1 over that span, against 2 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
Andrew 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.
Where he lands across our boards
Andrew was scored on 12 boards in that matchup, and the spread is the interesting part: singles graded 91.6/100 while stolen bases 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 Andrew 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.