PLAY vs RSVR

Dave & Buster's Entertainment, vs Reservoir Media, Inc.. — Valuation Comparison 2026

PLAY

Entertainment
Dave & Buster's Entertainment,
Quality
6.2
out of 10
Value Trap
19
SAFE
Price
$13.50
Last close
Models
10/13
Active
VS

RSVR

Entertainment
Reservoir Media, Inc..
Quality
9.0
out of 10
Value Trap
30
LOW
Price
$10.15
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType PLAY Fair ValuePLAY Upside RSVR Fair ValueRSVR Upside
Bayesian DCF Intrinsic $9.37 -7.7%
EROIC Spread Intrinsic $1.46 -87.4% $2.59 -74.5%
First Chicago Scenario $15.29 +32.3% $8.05 -20.7%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $14.03 +20.7%
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 PLAY vs RSVR — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PLAY vs RSVR — Which Stock Is More Undervalued?

RSVR scores higher with a 9.0/10 quality rating vs PLAY's 6.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Dave & Buster's Entertainment, (PLAY) and Reservoir Media, Inc.. (RSVR) 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.

PLAY currently trades at $13.50 with a QOC of 6.2/10, while RSVR trades at $10.15 with a QOC of 9.0/10.

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).