Soccer

Lecce vs Pisa Prediction

May 1, 2026

5,000 Monte Carlo simulations

Lecce vs Pisa prediction for May 1, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects Pisa 1.34 - Lecce 1.32. Lecce is favored with a 55.1% win probability. Expected total goals: 2.7..

Pisa
1.34
Projected Goals
VS 2.7 total
Lecce
1.32
Projected Goals
Match Outcome Probabilities
22.4%
22%
55.1%
PisaDrawLecce
Calibrated accuracy at this confidence: 80.4% (1,114 games)

Projected Goals Range 10th – 90th percentile

Lecce
0.51.32.1
Pisa
0.61.32.1
FINALPisa 1 — Lecce 2
Projected
Pisa 1.34 — Lecce 1.32
Actual
Pisa 1 — Lecce 2

Expected Goals (xG)

Pisa1.31
Lecce1.30
14.2Shots13.9
5.2On Target5.1
5.2Corners5.1

Goal Probabilities

Over 0.5
94.6%
Over 1.5
75.0%
Over 2.5
27.6%
Over 3.5
15.3%
Under 2.5
72.4%
BTTS
31.9%

Most Likely Scores

1-1
14.2%
0-0
11.8%
1-0
11.5%
0-1
11.1%
2-1
7.5%

Match Context

SERCritical
Pisa
3.64
Draw
3.04
Lecce
2.35

AI Intelligence Analysis

NEUTRAL -1RED ZONE38.1% WR (n=64)
Model claims 12.5% edge on Lecce away ML, but xG is virtually tied (1.31 vs 1.30), high draw probability (22.5% model vs 32.9% market) kills 3-way ML, and away ML is in RED zone (38.1% WR). This is a classic high-edge-without-edge-support trap.

Key Factors

  • xG gap is ZERO (1.31 Pisa vs 1.30 Lecce) — teams are evenly matched in team quality despite model's 12.5% edge
  • Away ML in RED zone: 38.1% WR historically (n=64) with z=-2.0. Betting against fundamental profitability pattern
  • Pisa mathematically relegated (18 pts, 6 games left). Motivation collapse risk on home team
  • Draw probability 22.5% model vs 32.9% market — model is drastically underpricing draws in high-defensive matchup
  • Lecce away form terrible: 0.582 GF/90, 1.488 GA/90 — weak attacking threat on the road

Risk Factors

  • Draw outcome kills 3-way ML: 22.5% of outcomes are draws (loss for any ML pick), reducing effective win probability from 55.1% to ~43% accounting for draw loss
  • RED zone all-in: SOCCER|ml|away is RED (38.1% WR). No matter the edge size, away ML historically loses
  • Model-xG mismatch: Model is generating 12.5% edge in a matchup with zero xG differential — classic overconfidence
RED ZONEXG MISMATCHHIGH EDGE WARNINGDRAW RISKMODEL MARKET CONFLICT

Edge Analysis

Moneyline
Lecce 55.1%
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Total
2.7
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How this prediction was generated: This page shows output from the Olympus Bets Soccer Monte Carlo engine. Each game is simulated 5,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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