MIN vs BOS prediction for May 22, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects BOS 3.9 - MIN 5.4. MIN is favored with a 54.6% win probability. The run line is -1.5 and the total is 7.5. Model projects 9.4 total runs.
BOS
3.9
Projected Score
VS
O/U 7.5
MIN
5.4
Projected Score
Win Probability
BOSMIN
-1.5
Run Line (BOS)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 52.0% (2,236 games)
Projected Runs Range 10th – 90th percentile
MIN
357
BOS
246
Projected
BOS 3.9 — MIN 5.4
Actual
BOS 6 — MIN 8
Starting Pitcher Matchup
Connor Prielipp L
MIN
SL38%87 mph30% whiff
FF31%95 mph11% whiff
CU13%82 mph15% whiff
Payton Tolle L
BOS
FF45%96 mph22% whiff
SI23%95 mph8% whiff
FC17%89 mph20% whiff
Weather Impact
Fenway Park
59°F7 mph wind
HR: 1.024 Total: 1.015
6mph out
Bullpen Comparison
MIN
5.14ERA
4.41FIP
7.27K/9
4.20BB/9
1.48WHIP
BOS
3.47ERA
4.21FIP
9.08K/9
3.64BB/9
1.22WHIP
Betting Edges
RUN_LINE HOME -1.5
-31.2% EV
+146
F5_ML HOME
-22.9% EV
-143
TOTAL UNDER 7.5
-21.5% EV
-115
ML HOME
-21.0% EV
-154
ML AWAY
+19.9% EV
+130
RUN_LINE AWAY +1.5
-19.8% EV
-179
First 5 Innings & NRFI
MIN F5
2.9 runs
49.6% win
BOS F5
2.2 runs
35.6% win
F5 Total
5.0
NRFI
56.0%
YRFI
44.0%
Avg 1st Inn Runs
0.91
HR Spotlight
Avg HRs
1.6
Over 0.5 HR
79%
Over 1.5 HR
47%
No HR
21%
Willson Contreras BOS27.4%
ISO: 0.326 | Barrel: 13.1% | vs Connor Prielipp | Park: 1.08x Platoon: 1.12x
Ryan Kreidler MIN26.3%
ISO: 0.200 | Barrel: 20.0% | vs Payton Tolle | Park: 1.08x Platoon: 1.12x
Byron Buxton MIN25.2%
ISO: 0.096 | Barrel: 18.2% | vs Payton Tolle | Park: 1.08x Platoon: 1.12x
Pitcher Strikeout Projections
Connor Prielipp
0.0 K projected
MIN | K/9: 0.0
Payton Tolle
0.0 K projected
BOS | K/9: 0.0
Injury Report
MIN8 injured
Tristan Gray 3BPATERNITY
Taj Bradley SP15-DAY-IL
Ryan Jeffers C10-DAY-IL
Garrett Acton RP60-DAY-IL
Walker Jenkins CFDAY-TO-DAY
David Festa SP60-DAY-IL
+2 more
BOS8 injured
Trevor Story SS10-DAY-IL
Roman Anthony LF10-DAY-IL
Kutter Crawford SP60-DAY-IL
Danny Coulombe RP15-DAY-IL
Garrett Crochet SP15-DAY-IL
Tanner Houck SP60-DAY-IL
+2 more
AI Intelligence Analysis
STRONG BET +2RED ZONE45.1% WR (n=164)
MIN away favorite at +129 is RARE actionable edge: 19.9% model edge (52.1% prob) combined with (a) BOS Trevor Story out long-term (sports hernia surgery), (b) Connor Prielipp elite LHP K-profile (28.4% K-rate, good command), (c) strong lineup quality gap. Market mispricing BOS at -153, suggesting market overweighting home field and underestimating MIN pitching advantage.
Key Factors
- SP advantage favors away: Connor Prielipp (B- grade, 0.461 score, 28.4% K-rate, 8.8% BB-rate, elite slider) vs Payton Tolle (B grade, 0.602 score, 26.1% K-rate, 6.1% BB-rate) — both B-tier but Prielipp's K-rate is elite; modern game values K
- BOS lineup WEAKENED by Trevor Story (SS) long-term IL (sports hernia) — removes premium everyday OF depth, -0.75pt offensive swing
- MIN away underdog paradox BROKEN here: 19.9% edge on 52.1% prob is STRONG edge (10-15% bucket); historically this bucket is 51.8% WR (n=85) — POSITIVE
- Fenway park factor 1.024 (slight HR multiplier) favors power, but Prielipp dominance might suppress scoring regardless
- Connor Prielipp's slider is elite (37.8% pitch mix) — attacks LHH; BOS lineup skews left-handed without Story; advantage away pitcher
Risk Factors
- 19.9% edge is HIGH — calibration warns that high-edge plays underperform (model overconfidence). But this 10-15% bucket has positive historical record.
- BOS at home typically doesn't lose to away teams despite injuries — Fenway effect is real
- MIN lineup quality: are they better than BOS enough to justify +129 price? Model says yes (52.1% prob), market says no (43.5% implied). One of these is wrong.
PITCHER ADVANTAGESHARP SUPPORTWEATHER IMPACT
Edge Analysis
Moneyline
MIN 54.6%
-31.2 pts
Run Line
-1.5
-31.2 pts
Total
7.5
+13.2 pts
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →