Premium Showcase
Premium Analysis Showcase
Explore realistic examples of the analysis available with MilHousing Playbook Premium. These examples demonstrate how military families can evaluate their current home, compare housing options at their next duty station, and build a complete PCS housing strategy.
Sample Analyses — Example Data Only
This page demonstrates Premium features using fictional example scenarios.
Duty station
Nellis AFB, NV
Current home
Las Vegas, NV
Home value
$540,000.00
Mortgage balance
$284,156.00
Executive Summary
With $255,844 in equity, a favorable Las Vegas rental market, and a 10-year wealth-building horizon, converting the current home into a long-term rental builds substantially more wealth than selling. Projected rental income of $2,800/mo covers PITI plus property management with a positive ~$340/mo cash flow, and equity continues to grow through both appreciation and principal paydown.
Bottom Line Recommendation
Recommendation · High Confidence
Keep the home as a long-term rental.
Estimated 10-year net wealth advantage vs. selling: +$176,000.00.
Current Equity
Net Proceeds (if sold)
Rental Analysis
Sell Analysis
Recommendation Drivers
- ✅ Strong rental demand near Nellis AFB
- ✅ Locked-in 4.25% mortgage rate
- ✅ Positive monthly cash flow from day 1
- ✅ 10-year horizon supports long-term hold
- ⚠️ Self-management not feasible from CONUS PCS
- ⚠️ HOA fee escalation risk
Risk Assessment
Military Considerations
- VA loan entitlement remains partially used — affects next-duty-station financing.
- Section 121 capital-gains exclusion preserved through 2029.
- Distance management requires a vetted property manager.
Wealth Projection (10-Year)
Net worth (rental scenario, $K)
Sensitivity Analysis
Explain The Math
Net wealth = (Home value × growth) − Mortgage balance + Cumulative net cash flow − Sale of comparison portfolio. Defaults: 4% appreciation, 6.5% reinvestment, 8% sale cost, 12% management + vacancy + maintenance.
Ready to run your own analysis?
Use your real numbers, military compensation, duty station, and housing assumptions to generate personalized recommendations.