Toronto Blue Jays — Model Predictions & Analytics

Toronto Blue Jays power rating, recent prediction performance and upcoming-game projections from the Signal Labs MLB engine.

Elo Rating

1453

Rank #26 of 30

Last 10 Picks

4-3

7 settled

Total Logged Picks

across all bet types

Upcoming Toronto Blue Jays games (next 5)

Date (ET)	Matchup	Spread	O/U	Venue
Sep 9, 3:05 PM ET	@ Athletics	—	—	Sutter Health Park

Trends & situational edges

scoring profile

Averages 4.05 runs scored, 4.28 allowed last season

72-71 record across 143 games in 2026

4.05 / 4.28

Updated Sep 8, 2026 ET. Rolling 3-5 season window.

Recent Toronto Blue Jays model results (last 10)

Date (ET)	Pick	Odds	Result	Units
Sep 7, 2026	Toronto Blue Jays ML at -176	-176	WIN	+0.85u
Aug 31, 2026	Toronto Blue Jays ML at +163	163	LOSS	-1.00u
Aug 15, 2026	Toronto Blue Jays ML at -118	-118	LOSS	-1.50u
Jul 10, 2026	Toronto Blue Jays ML at -102	-102	LOSS	-1.00u
Jun 30, 2026	Toronto Blue Jays ML at -108	-108	WIN	+1.39u
Jun 17, 2026	Toronto Blue Jays ML at +118	118	WIN	+1.77u
Apr 28, 2026	Toronto Blue Jays ML at -130	-130	WIN	+0.77u

Best Toronto Blue Jays wins

Date	Game	Pick	Odds	P/L
Jun 17, 2026	Toronto Blue Jays @ Boston Red Sox	Toronto Blue Jays ML at +118	118	+1.77u
Jun 30, 2026	New York Mets @ Toronto Blue Jays	Toronto Blue Jays ML at -108	-108	+1.39u
Sep 7, 2026	Toronto Blue Jays @ Athletics	Toronto Blue Jays ML at -176	-176	+0.85u

Worst Toronto Blue Jays losses

Date	Game	Pick	Odds	P/L
Aug 15, 2026	New York Yankees @ Toronto Blue Jays	Toronto Blue Jays ML at -118	-118	-1.50u
Jul 10, 2026	Toronto Blue Jays @ San Diego Padres	Toronto Blue Jays ML at -102	-102	-1.00u
Aug 31, 2026	Toronto Blue Jays @ Cleveland Guardians	Toronto Blue Jays ML at +163	163	-1.00u

How we model MLB

Our MLB engine blends an Elo-style power rating with starter-quality (xERA/xwOBA-against), bullpen rest state, park factors, ump effects and same-day weather to project win probability and total runs. Every projection is benchmarked against the live market — we only post a pick when our edge clears a strict threshold and the source data passes cross-checks.