
MIL
69-42

PIT
56-57
Line movement
21 snapshots
PIT spread
-1.5
open -1.5
Total
O/U 8.5
open O/U 8.5
PIT no-vig %
53.8%
open 53.8%
Stepped lines reflect captured market snapshots from odds_snapshots. Spread sign convention: negative = PIT favored. Live mode caps the in-game branch to the last 60 minutes.
Matchup · 2026
MLB Stats API
MIL
league avg
PIT
.736
OPS
.719
▶.751
.337
OBP
.318
.335
5.00
Runs / G
4.50
▶5.12
3.48
Team ERA
4.18
4.31
1.16
WHIP
1.30
1.33
9.8
K / 9
8.5
9.3
Postgame · final
Line score, top performers, model verdict against Vegas, and how the closing line shaped up vs the actual outcome.
Final
MIL wins
MIL 0 · PIT 0 (tied)
Model verdict
✗ Missed
Picked PIT +1pp
Against the spread
No spread
Line score
What's next
See every model edge for tonight's remaining games and tomorrow's slate side-by-side, or jump straight to DraftKings & FanDuel for the full board.
21+ · we may earn a referral fee · your odds unchanged.
Data via ESPN · MLB Stats API · Baseball Savant
Team pages
Elsewhere in the MLB
MLB · Box scoreADVANCED
No player stats available yet.
No player stats available yet.
Season series
PIT leads series 2-1
Model & market
Vegas line center
DraftKings via ESPN · 21+
Spread
PIT -1.5
Total
8.5
Standard · 0.0 vs avg
Moneyline
Implied probabilities back-computed from American odds — break-even win % a moneyline bet needs to be +EV.
Line movement · 21 snapshots
ESPN-tracked · 21+
Spread
1.5
0.0 since open
Total
8.5
0.0 since open
Betting line
PIT -1.5·O/U 8.5·MIL +107/PIT -129
The receipts
0.00
CLV pp
Open price
+107
Close price
+107
Open no-vig
46.2%
Close no-vig
46.2%
Line barely moved
How we read this game
Player projections
Per-player stat projections built from a recency-weighted blend of the last ten games, season average, and matchup context. Confidence reflects sample size and stability — the top of each list is who to watch.
128
projections · 107 high confidence
Strikeouts
Hits
Total bases
RBIs
Earned runs
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Model ensemble · how the prediction is built
Each sub-model uses a different rating substrate. Bayesian model averaging weights them by rolling Brier score so the ensemble inherits each model's strengths. Disagreement flags games where the sub-models don't see eye-to-eye — lower confidence, wider band.
51.7%
ensemble · PIT favored
Elo Static
51.1%
P(PIT win)
33%
weight
Elo Pitching
52.4%
P(PIT win)
33%
weight
Bullpen Park
50.5%
P(PIT win)
34%
weight
Disagreement
0.79 pp
weighted σ across sub-models
Confidence
95% · high
maps from disagreement
Substrate count
3 / 3 active
ones with full inputs tonight
Weights recalibrated nightly on a 90-day rolling window with strict point-in-time correctness — no model gets credit for a game it hasn't seen. Headline % is Platt-scaled per league; sub-model rows show raw BMA inputs.