Park factor
98 total idx
PNC Park run environment
Park factor boosts run scoring, so contact quality matters more tonight here.
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Cincinnati Reds at Pittsburgh Pirates
CIN
CIN
35-37
PregameFri, 6:40 PM EDT
PIT
PIT
37-37
Verdict
Pass · no edge tonight.
The model doesn't see daylight against the posted line on this game. We don't surface negative-EV picks; check the drill-down for sub-model context.
Why this matchup
1 signal · model + marketPNC Park · Pittsburgh, Pennsylvania
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Pregame · scouting report
The matchup, end-to-end.
Probable starters, projected lineups, head-to-head this season, our model edge against the market — every angle on one surface.
Away starter
Andrew Abbott
SP · #41
4-4
W-L
3.95
ERA
1.41
WHIP
58
K
79.2
IP
Last 3 starts
vsARI-5.0 IP1 ER5 K
@SDL(4-4)6.0 IP3 ER6 K
vsKC-6.0 IP3 ER5 K
Home starter
Paul Skenes
SP · #30
6-6
W-L
2.85
ERA
0.93
WHIP
99
K
82.0
IP
Last 3 starts
vsMIAL(6-6)6.0 IP2 ER10 K
vsLAD-6.0 IP2 ER7 K
@HOU-4.2 IP1 ER7 K
Vegas line
Lines post once a sportsbook releases them.
Model edge
Our model rates this game once both starters are confirmed.
Head to head
SeriesPIT leads series 5-1
TypeRegular Season Series
Model ensemble · how the prediction is built
3 sub-models, blended.
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.
48.1%
ensemble · CIN favored
Elo Static
fallback · inputs missing
50.0%
P(PIT win)
33%
weight
Elo Pitching
fallback · inputs missing
50.0%
P(PIT win)
32%
weight
Bullpen Park
fallback · inputs missing
50.0%
P(PIT win)
34%
weight
Disagreement
0.00 pp
weighted σ across sub-models
Confidence
100% · high
maps from disagreement
Substrate count
0 / 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.
Player projections
PIT vs CIN.
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 · 81 high confidence
Strikeouts
- Paul SkenesPIT7.2± 2.8medium
- Chase BurnsCIN7.1± 2.8low
- Braxton AshcraftPIT6.4± 2.9low
Hits
- Bryan ReynoldsPIT1.2± 1.1high
- Blake DunnCIN1.1± 0.9high
- Jake MangumPIT1.1± 0.9high
Total bases
- Bryan ReynoldsPIT2.5± 3.2high
- JJ BledayCIN2.0± 1.9high
- Eugenio SuarezCIN1.8± 2.6high
RBIs
- Eugenio SuarezCIN0.8± 1.8high
- JJ BledayCIN0.7± 1.3high
- Sal StewartCIN0.7± 1.3high
Earned runs
- Mitch KellerPIT3.6± 2.5medium
- Chris PaddackCIN3.2± 2.4low
- Nick LodoloCIN3.1± 1.8low
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
MLB Stats API
CIN
league avg
PIT
.710
OPS
.717
▶.739
.313
OBP
.319
▶.335
4.31
Runs / G
4.50
▶4.96
4.57
Team ERA
4.17
▶4.25
1.46
WHIP
1.31
▶1.31
7.9
K / 9
8.5
▶9.2
Data via ESPN · MLB Stats API · Baseball Savant
