Which side does The One Analytics' model favor in BOS at TOR?

The model favors TOR, based on a weighted edge across matchup factors. The pick is logged before the game and graded in public.

When is the pick logged, and can it change?

Every model pick is timestamped before the game starts and is never edited after the fact.

How is the pick graded?

In public, the moment the game goes final — wins and losses alike, with the full record on the model accuracy page.

Boston Red Sox vs Toronto Blue Jays: Final Score & Box Score — Apr 29, 2026

FINAL+7TOR

BOS

12-19

TOR

14-16

Rogers Centre · Toronto, Ontario

41,314 attended

Line movement

51 snapshots

TOR spread

+1.5

open +1.5

Total

O/U 8.5

open O/U 8.5

TOR no-vig %

50.4%

open 50.4%

Stepped lines reflect captured market snapshots from odds_snapshots. Spread sign convention: negative = TOR favored. Live mode caps the in-game branch to the last 60 minutes.

Logged before first pitch · graded in public

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.

57.5%

ensemble · TOR favored

Elo Static
56.4%
P(TOR win)
33%
weight
Elo Pitching
58.2%
P(TOR win)
32%
weight
Bullpen Park
57.0%
P(TOR win)
34%
weight

Disagreement

0.74 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.

The receipts

Closing-line value.

0.00

CLV pp

Open price

-112

Close price

-112

Open no-vig

50.4%

Close no-vig

50.4%

Line barely moved · Graded: hit

Logged before tip · graded in public

How we read this game

Which side does The One Analytics' model favor in BOS at TOR?: The model favors TOR, based on a weighted edge across matchup factors. The pick is logged before the game and graded in public.
When is the pick logged, and can it change?: Every model pick is timestamped before the game starts and is never edited after the fact.
How is the pick graded?: In public, the moment the game goes final — wins and losses alike, with the full record on the model accuracy page.

Player projections

TOR vs BOS.

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 · 93 high confidence

Strikeouts

Dylan CeaseTOR
8.5± 2.8low
Ranger SuarezBOS
5.7± 3.6low
Connelly EarlyBOS
5.4± 2.0medium

Hits

Caleb DurbinBOS
1.1± 1.3high
Ceddanne RafaelaBOS
1.1± 0.9high
Willson ContrerasBOS
1.0± 1.1high

Total bases

Caleb DurbinBOS
2.2± 3.2high
Willson ContrerasBOS
2.1± 3.0high
Ceddanne RafaelaBOS
2.0± 2.4high

RBIs

Ceddanne RafaelaBOS
0.7± 1.3high
Brandon ValenzuelaTOR
0.7± 0.7high
Kazuma OkamotoTOR
0.7± 1.0high

Earned runs

Kevin GausmanTOR
2.8± 2.7medium
Simeon Woods RichardsonTOR
2.8± 3.3low
Jake BennettBOS
2.7± 2.0low

Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands

Matchup · 2026

Team rate stats vs league

MLB Stats API

BOS

league avg

TOR

.690

OPS

.718

▶

.706

.311

OBP

.319

.313

3.89

Runs / G

4.50

▶

4.10

3.85

Team ERA

◀

4.18

4.10

1.26

WHIP

◀

1.31

1.30

8.5

K / 9

8.5

▶

8.9

Postgame · final

The morning-after recap.

Line score, top performers, model verdict against Vegas, and how the closing line shaped up vs the actual outcome.

Final

TOR wins

BOS 1 · TOR 8 (by 7)

Model verdict

✓ Hit

Picked TOR +6pp

Against the spread

No spread

Line score

Inning by inning

Team	1	2	3	4	5	6	7	8	9	R
BOS	1	0	0	0	0	0	0	0	0	1
TOR	0	0	3	2	2	0	0	1	8

What's next

Tomorrow's slate is open.

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.

MLB edges →Full slate →

Tomorrow's board↗Tomorrow's board↗

21+ · we may earn a referral fee · your odds unchanged.

Data via ESPN · MLB Stats API · Baseball Savant

batting box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
R. AnthonyLF	.208	5	0	1	0	0	0	2
W. Contreras1B	.262	4	1	2	1	1	0	0
W. AbreuRF	.307	3	0	2	0	0	1	0
C. RafaelaCF	.263	4	0	0	0	0	0	2
T. StorySS	.197	3	0	1	0	0	1	0
A. MonasterioSS	.227	3	0	0	0	0	0	0
C. WongC	.243	4	0	0	0	0	0	0
I. Kiner-Falefa2B	.229	2	0	1	0	0	0	0
C. Durbin3B	.172	4	0	1	0	0	0	1
J. DuranLF	.170	1	0	0	0	0	0	1
M. Mayer2B	.253	2	0	1	0	0	0	0
Team		35	1	9	1	1	2	6

Player

.208

.262

.307

.263

.197

.227

.243

.229

.172

.170

.253

Team

pitching box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
B. BelloSP	3.2	6	4	4	2	2	63
G. WeissertRP	0.2	2	2	2	0	1	13
J. MoranRP	2.2	1	1	1	1	0	39
G. WhitlockRP	1.0	1	1	1	0	0	15
Team	8.0	10	8	8	3	3	130

Player

3.2

0.2

2.2

1.0

Team

8.0

130

batting box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
E. Clement2B	.301	5	1	1	2	1	0	0
J. SanchezRF	.264	4	1	1	0	0	0	0
V. Guerrero Jr.1B	.358	3	2	3	0	0	1	0
K. Okamoto3B	.224	4	0	1	2	0	0	2
D. VarshoCF	.234	2	1	0	0	0	1	0
Y. PinangoLF	.400	2	0	1	1	0	0	0
M. StrawRF	.277	3	0	0	1	0	0	0
A. GimenezSS	.277	4	0	0	0	0	0	1
B. ValenzuelaC	.189	3	3	2	1	1	1	0
G. SpringerDH	.196	2	0	1	1	0	0	0
Team		32	8	10	8	2	3	3

pitching box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
E. LauerSP	4.1	5	1	1	1	1	68
B. FisherRP	1.2	1	0	0	0	1	17
T. NanceRP	0.2	1	0	0	0	0	7
J. MantiplyRP	0.1	2	0	0	0	1	10
S. MilesRP	2.0	0	0	0	1	3	26
Team	9.0	9	1	1	2	6	128

Team

BOS

TOR

—

3 sub-models, blended.

Closing-line value.

TOR vs BOS.

Team rate stats vs league

The morning-after recap.

Inning by inning

Tomorrow's slate is open.

Batters

Pitchers

Batters

Pitchers

Closing-line value.

TOR vs BOS.

3 sub-models, blended.