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: 98.1% (1,051 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. Full methodology →

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