College Basketball

Loyola Chicago vs Richmond Prediction

March 11, 2026

10,000 Monte Carlo simulations

FINAL: Richmond 67 — Loyola Chicago 75. Our Monte Carlo simulation projected Richmond 73.0 - Loyola Chicago 61.6 (Richmond at 78.1% win probability). The spread is -4.5 and the total is 138.5.

Richmond
73.0
Projected Score
VS O/U 138.5
Loyola Chicago
61.6
Projected Score
Win Probability
78.1%
21.9%
RichmondLoyola Chicago
-4.5
Spread (Richmond)
138.5
Total Line
10,000
Simulations
Loyola ChicagoRichmond L4
Calibrated accuracy at this confidence: 92.2% (4,284 games)

Projected Points Range 10th – 90th percentile

Loyola Chicago
486275
Richmond
597387
FINALRichmond 67 — Loyola Chicago 75
Projected
Richmond 73.0 — Loyola Chicago 61.6
Actual
Richmond 67 — Loyola Chicago 75

Pick Results

Richmond -5.0spreadLOSS-0.50u

Spread Analysis

Richmond Cover
67.9%
Loyola Chicago Cover
32.1%
ATS Edge: +10.9 pts

AI Intelligence Analysis

LEANGREEN ZONE78.0% WR (n=223)
Richmond projects at 78.0% home win probability vs Loyola Chicago with a 10.7-pt spread edge over the market (-5.0) — technically a HIGH EDGE WARNING territory, but the directional call is sound and the GREEN zone is strong; risk-reward on ML is the only viable angle.

Key Factors

  • Model win prob 78.0% for Richmond — GREEN zone (CBB|ml|home|favorite|5-10%|any = 78.0% WR, n=223)
  • Model spread -15.7 vs market -5.0 = 10.7 pt gap — HIGH EDGE WARNING (model likely overestimates margin)
  • Richmond 78% win prob is directionally strong even if the margin is noise — ML is the play, not spread
  • No ML odds available — lean is directional only

Risk Factors

  • HIGH EDGE WARNING: 10.7 pt model-market spread gap — 30-day high-edge (25%+) WR is only 30.0% (3-7)
  • No ML odds available — cannot compute Kelly or market-implied probability
  • A-10 conference tournament — both teams know each other; market likely has solid information at -5
GREEN ZONEML VALUECONFERENCE GAMEHIGH EDGE WARNING

Edge Analysis

Moneyline
Richmond 78.1%
--
Spread
-4.5
--
Total
138.5
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How this prediction was generated: This page shows output from the Olympus Bets College Basketball 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 →

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