
MIL
50-29

KC
34-49
Line movement
10 snapshots
KC spread
+1.5
open +1.5
Total
O/U 9.0
open O/U 9.0
KC no-vig %
48.3%
open 48.3%
Stepped lines reflect captured market snapshots from odds_snapshots. Spread sign convention: negative = KC favored. Live mode caps the in-game branch to the last 60 minutes.
Logged before first pitch · graded in public
Matchup · 2026
MLB Stats API
MIL
league avg
KC
.732
OPS
.718
.710
.338
OBP
.319
.317
5.23
Runs / G
4.50
4.23
3.36
Team ERA
4.18
4.87
1.18
WHIP
1.31
1.43
9.9
K / 9
8.5
7.9
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 · KC 0 (tied)
Model verdict
✓ Hit
Picked MIL +3pp
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
MLB · Box scoreADVANCED
No player stats available yet.
No player stats available yet.
Season series
Season series
KC wins series 2-0
Model & market
Vegas line center
DraftKings via ESPN · 21+
Spread
MIL -1.5
Total
9.0
High-scoring · +0.5 vs avg
Moneyline
Implied probabilities back-computed from American odds — break-even win % a moneyline bet needs to be +EV.
Line movement · 10 snapshots
ESPN-tracked · 21+
Spread
1.5
0.0 since open
Total
9.0
0.0 since open
Betting line
MIL -1.5·O/U 9·MIL -118/KC -102
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.
130
projections · 92 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.
43.3%
ensemble · MIL favored
Elo Static
47.0%
P(KC win)
33%
weight
Elo Pitching
44.9%
P(KC win)
32%
weight
Bullpen Park
47.6%
P(KC win)
34%
weight
Disagreement
1.15 pp
weighted σ across sub-models
Confidence
92% · 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.