MIA vs TB prediction for May 15, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects TB 3.2 - MIA 3.5. MIA is favored with a 52.4% win probability. The run line is -1.5 and the total is 7.5. Model projects 6.7 total runs.
TB
3.2
Projected Score
VS
O/U 7.5
MIA
3.5
Projected Score
Win Probability
TBMIA
-1.5
Run Line (TB)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 52.0% (2,085 games)
Projected Runs Range 10th – 90th percentile
MIA
245
TB
135
Projected
TB 3.2 — MIA 3.5
Actual
TB 7 — MIA 2
Starting Pitcher Matchup
Janson Junk R
MIA
FF32%94 mph11% whiff
SL23%86 mph16% whiff
CH20%87 mph35% whiff
Ian Seymour L
TB
CH31%83 mph28% whiff
FF21%92 mph18% whiff
SI20%90 mph14% whiff
Weather Impact
Tropicana Field
84°F11 mph windRoof: closed
HR: 1.000 Total: 1.000
Indoor (neutral)
Bullpen Comparison
MIA
3.54ERA
3.54FIP
9.47K/9
4.56BB/9
1.18WHIP
TB
3.85ERA
3.61FIP
8.23K/9
3.42BB/9
1.27WHIP
Betting Edges
RUN_LINE AWAY +1.5
-36.4% EV
-213
TOTAL OVER 7.5
-26.8% EV
-122
TOTAL UNDER 7.5
+19.6% EV
+100
F5 UNDER 4.5
+16.4% EV
-132
RUN_LINE HOME -1.5
-16.4% EV
+176
NRFI NRFI
+13.1% EV
-118
First 5 Innings & NRFI
MIA F5
1.8 runs
42.2% win
TB F5
1.6 runs
36.7% win
F5 Total
3.5
NRFI
64.5%
YRFI
35.5%
Avg 1st Inn Runs
0.67
HR Spotlight
Avg HRs
1.7
Over 0.5 HR
82%
Over 1.5 HR
50%
No HR
18%
Jonathan Aranda TB30.0%
ISO: 0.243 | Barrel: 11.3% | vs Janson Junk | Park: 0.92x Platoon: 1.12x
Junior Caminero TB30.0%
ISO: 0.224 | Barrel: 12.8% | vs Janson Junk | Park: 0.92x
Esteury Ruiz MIA29.6%
ISO: 0.200 | Barrel: 20.0% | vs Ian Seymour | Park: 0.92x Platoon: 1.12x
Pitcher Strikeout Projections
Janson Junk
0.0 K projected
MIA | K/9: 0.0
Ian Seymour
0.0 K projected
TB | K/9: 0.0
Injury Report
MIA5 injured
Robby Snelling SP15-DAY-IL
Ronny Henriquez RP60-DAY-IL
Jesus Tinoco RPOUT
Griffin Conine LF10-DAY-IL
Adam Mazur SP60-DAY-IL
TB8 injured
Gavin Lux LF10-DAY-IL
Austin Vernon RPDAY-TO-DAY
Joe Boyle SP15-DAY-IL
Steven Wilson RP60-DAY-IL
Steven Matz SP15-DAY-IL
Logan Driscoll CDAY-TO-DAY
+2 more
AI Intelligence Analysis
LEANRED ZONE43.4% WR (n=34)
UNDER 7.5 has strong 19.6% edge (59.8% model) but sits in RED ZONE for under totals (46.0% WR historically). This is the high-edge trap: model sees massive disagreement with market but historical performance on big under edges is terrible. Both pitchers are decent (Seymour 6.04 ERA, Junk 3.51 ERA), park is neutral (dome), and weather is warm (84.2°F) which should inflate, not suppress. Market at 7.5 is actually reasonable. Recommend SKIP or very light LEAN only.
Key Factors
- UNDER edge strong on surface (19.6%, 59.8% model) but RED ZONE trap: Under totals historically 46.0% WR (n=247), worst bucket. Bigger edge = worse outcomes for unders.
- Temperature factor: 84.2°F is warm, should inflate run total by ~0.5 runs, not suppress it. Model at 6.74 doesn't account for warm air helping balls carry.
- Pitcher quality: Seymour (6.04 ERA, B-grade, 27.5% K) is decent for TB; Junk (3.51 ERA, A- command, 17.2% K) is legitimate arm. Neither screams 'low-scoring game.'
- Dome advantage TB: Tropicana Field with closed roof removes weather variables. Standard baseline = neutral scoring environment.
- F5 and NRFI edges moderate (16.4% and 13.1%) but still follow same RED ZONE under-total pattern. Early game also supports under but not at same extreme edge.
Risk Factors
- RED ZONE UNDER TOTALS: 43.4% WR (n=34) specifically on small-edge unders. This is a historical money pit. Recommend SKIP unless additional external data supports.
- Temperature not modeled: 84.2°F should add ~0.5 runs to 6.74 projection = 7.24, much closer to market 7.5. Model might be underestimating weather impact.
- Market is correct here: Junk is good, Seymour is decent, dome is neutral, warm weather inflates runs. Market at 7.5 seems reasonable.
RED ZONEHIGH EDGE WARNINGCALIBRATION DISABLEDTEMPERATURE MISMATCHSKIP CAUTION
Edge Analysis
Moneyline
MIA 52.4%
-16.4 pts
Run Line
-1.5
-16.4 pts
Total
7.5
+19.6 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 →