RSI vs SEGG

Rush Street Interactive, Inc. vs Sports Entertainment Gaming Glo — Valuation Comparison 2026

RSI

Gambling
Rush Street Interactive, Inc.
Quality
7.6
out of 10
Value Trap
12
SAFE
Price
$26.37
Last close
Models
13/13
Active
VS

SEGG

Gambling
Sports Entertainment Gaming Glo
Quality
4.6
out of 10
Value Trap
60
DANGER
Price
$1.64
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType RSI Fair ValueRSI Upside SEGG Fair ValueSEGG Upside
Bayesian DCF Intrinsic $7.94 -69.9% $0.18 -88.8%
Earnings Power Value Intrinsic $6.22 -76.4% $4.34 +255.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for RSI vs SEGG — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

RSI vs SEGG — Which Stock Is More Undervalued?

RSI scores higher with a 7.6/10 quality rating vs SEGG's 4.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Rush Street Interactive, Inc. (RSI) and Sports Entertainment Gaming Glo (SEGG) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

RSI currently trades at $26.37 with a QOC of 7.6/10, while SEGG trades at $1.64 with a QOC of 4.6/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).