| ★ ▲ | Address ▲ | Zone ▲ | Lot ▲ | Price ▲ | Lot Size ▲ | Lot W ▲ | Units ▲ | Exit $/SF ▲ | Revenue/Unit ▲ | Cost/Unit ▲ | Profit ▲ | Margin ▲ | Slope ▲ | Days Listed ▲ | New ▲ | Link |
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PIN COLORS (Net Margin)
DEAL STATUS DOTS
OTHER MARKERS
Click Deal Assumptions in the header to adjust inputs and reprice all pins in real time.
SB 1123 (signed 2024) allows by-right subdivision of single R1 and multifamily-zoned parcels into up to 10 fee-simple lots without discretionary review. “By-right” means no planning commission hearings, no neighbor appeals, no conditional use permits — the city must approve ministerially if the project meets objective standards.
We acquire directly from homeowners at pre-SB 1123 pricing — before the market has repriced for subdivision potential. We subdivide, build attached townhomes, and sell fee-simple lots to end buyers.
Unlike condos, fee-simple buyers own their land outright. No shared ownership structure, no master HOA over the land. This is the same ownership structure as a single-family home — the most liquid and fundable product in the for-sale market.
The app supports multiple markets. Append ?market=sd to the URL for San Diego. Default is Los Angeles. Each market has its own listings, comps, and zoning data.
?search=lat,lng URL. Pasting into a new window reopens the off-market card (loads from saved data if available, otherwise re-fetches parcel data).sb1123_overrides_<AIN>). An “✎ Edited” badge appears on cards with saved overrides.Colored dots in the header bar show when each dataset was last refreshed:
Datasets tracked: Listings, Comps, Parcels. Rental comp data age is tracked separately — rental comps are regenerated via fetch_rental_comps.py and stamped into LISTINGS_META.rentalCompsAge.
Invite-only access. Contact matt@lucidresi.com.
SB 1123 unit capacity is calculated from lot size:
On parcels with known lot dimensions, a layout check verifies that the lot width and depth can physically accommodate the calculated units. If not, the count is reduced and a layout warning is shown.
All-In $/SF = Total Project Cost ÷ Total Sellable SF
Equity and debt sized on FAR-constrained buildable SF (lot SF × FAR floor), not gross unit SF — prevents overstatement on sub-14K SF lots.
Slopes above 5% increase hard costs by $15/SF per 5% increment (e.g., 12% slope adds $30/SF). Ellis Act relocation costs apply to RSO-risk multifamily properties and add 4 months to the hold period.
Deals where the economics don’t pencil at current assumptions appear as faded “ghost” pins. These are filtered out when the margin slider minimum is above 0%.
Exit $/SF is derived from a weighted scoring model using recent comparable sales — townhomes, condos, and size-gated SFR — scored by product similarity, proximity, and recency. See the Exit Pricing tab for full methodology. Spread = Exit $/SF − All-In $/SF.
Exit $/SF is the estimated sale price per square foot for completed townhomes. It is derived from a weighted average of recent comparable sales — not a manual input or a simple median. Every comp earns a composite score; higher-scoring comps have more influence on the final number.
Composite Score = Product Wt × Proximity Wt × Recency Wt
Exit $/SF = Σ(comp $/SF × score) ÷ Σ(scores)
No floor. No ceiling. The model output is the number.
Each listing’s exit $/SF is computed offline by the data pipeline using a spatial expanding-radius search. The pipeline searches outward from the listing (0.25 mi → 0.5 → 1 → 2 → 4 mi) until at least 5 qualifying comps are found. Only sold comps within the past 24 months and in eligible property types (SFR, Condo, Townhome) are considered.
The resulting weighted average skews toward the upper quartile of the scored comp pool — reflecting the positioning of new-construction product against predominantly older resale stock. This is not a simple median or mean; higher-scoring comps (better product match, closer, more recent) carry more weight in the final number.
The comp search radius and count are shown on each deal card. Open the BTS Comps table to inspect the full comp pool, sort by any column, and use the Hide toggle to exclude individual comps from the exit $/SF calculation.
The Sale $/SF grid layer and comp popup colors use a 14-bucket cold-to-hot gradient:
We build new attached townhomes. Comps closest to that product receive the highest weight. Comps further from it are discounted.
SFR outside 1,500–2,200 SF is excluded entirely — $/SF is not comparable to a 1,750 SF townhome. All other SFR is excluded.
The model requires at least 5 comps. If fewer qualify, the search radius expands (up to 3.0 miles) and lower product tiers are added until 5 are found. Confidence is scored 0–100 based on comp count and method quality:
Before computing the weighted average, the model trims outlier comps using a 1.0× IQR filter on $/SF. Trimming only activates when the pool has at least 5 comps and will never remove more than 40% of the pool, ensuring the average is not skewed by extreme values while preserving thin markets.
The comp pool in our target markets is dominated by pre-2015 renovated stock — older homes that qualify as T1 via high $/SF relative to neighborhood median. We build new ground-up product.
Empirically, new construction in our target ZIPs trades approximately 20% above the blended T1 pool. We apply an 18% new construction premium to the weighted comp average to account for this gap.
This premium is applied after scoring — it does not affect individual comp weights or pool composition.
The three comps shown on each deal card are selected by product type relevance — townhomes first, then condos, then SFR — so the most comparable sales are always visible.
Comps labeled T1 in the comp table are split into three sub-types:
All three sub-types are valid T1 comps. The sub-tier label lets you assess comp quality and vintage mix at a glance.
Exit $/SF reflects active comps only. Use the Hide toggle in the BTS table to exclude individual comps based on local market expertise. Excluded comps remain visible at reduced opacity and are flagged (EXCLUDED: TRUE) in CSV exports but are removed from the exit $/SF regression and all downstream exports (XLS, OM, Teaser).
Exclusions are per-deal and per-session — they reset on page reload. When comps are excluded, the exit $/SF is recalculated using a distance-weighted average of remaining comps with the same 18% new construction premium.
Build-to-Rent (BTR) is modeled as a secondary exit strategy for markets with strong rent fundamentals. It is not our primary strategy — the for-sale exit typically produces superior returns. BTR viability is constrained by DSCR: at current market rates and 70% LTV, most deals do not achieve 1.25× DSCR, which sets the cap on permanent loan proceeds and therefore on equity return.
DSCR = NOI ÷ Annual Debt Service. We require ≥1.25× for a BTR deal to be considered viable. The Refi LTV and Refi Rate sliders (in the Assumptions tab) directly control the DSCR calculation — adjusting either slider instantly recalculates annual debt service and the viability threshold. The DSCR constraint back-calculates the maximum sustainable NOI — which in turn caps the rent required to make the deal work.
The deal card DSCR waterfall shows three scenarios at 90% / 100% / 110% of base rent, with vacancy at 5% and operating expenses at the slider-set OpEx ratio (default 30%). Deals achieving ≥1.25× DSCR at base rent are flagged BTR-viable.
Rent estimates are derived from a 6-tier spatial cascade. The model uses the first tier that produces enough data:
Each comp’s $/SF is size-normalized to 1,750 SF before aggregation. Rental outliers are trimmed using 1.5× IQR before any percentile calculation.
Why P75: The comp pool includes aged existing stock that rents well below what a new-construction 3BR townhome would command. The 75th percentile better reflects achievable rents for new product without cherry-picking a single top comp. When fewer than 8 comps are available the model falls back to median to avoid overfitting a thin sample.
Rent fallback: When no rental comp data is available and no HUD SAFMR exists for the ZIP, the model uses a market-based floor — LA: $3,400/mo, SD: $3,600/mo — derived from HUD MSA Fair Market Rent estimates for a 3BR unit. If a HUD SAFMR value is present, the fallback uses that value × 1.15 instead.
SB 1123 applies to parcels where residential use is permitted as-of-right. Eligible zones: R1, R2, R3, R4, MU, and LAND (vacant residential). All other zones are excluded.
The following are automatic disqualifiers — no override possible:
Minimum lot size: 2,400 SF for R1/LAND (2-unit floor at 1,200 SF/lot), 1,200 SF for R2–R4/MU (2-unit floor at 600 SF/lot). Maximum: 1.5 acres (LA) or 2 acres (SD) for R1/LAND; 5 acres for multifamily zones.
On lots under 14,000 SF, the FAR floor binds before the 1,750 SF average unit size cap — meaning full-size units may not be achievable. Breakeven for full-size units is approximately 14,000 SF. In edit mode, manually overriding Avg Unit SF or Units bypasses the FAR cap so revenue reflects the user’s explicit assumptions.
Each listing is scored 0–3 for tenant displacement risk, shown as a badge on the deal card:
Risk factors: existing improvements, bedroom count (3+ or 5+), multifamily structure, pre-2000 build year, and RSO rent stabilization (LA only — built pre-1979 in an RSO-eligible city). RSO properties incur Ellis Act relocation costs and a longer hold period.
For multifamily parcels with existing structures, the model estimates how many SB 1123 units can fit on the remainder of the lot after deducting the existing building footprint and a 2,000 SF driveway access corridor. Viable if ≥6,000 SF available and ≥4 units fit.
We acquire directly from homeowners before the property is listed, at prices that reflect current use (typically a single-family home) rather than SB 1123 subdivision potential. Most homeowners are unaware of SB 1123 or its value impact on their parcel.
Estimated market value is derived from LA County Assessor data (assessed land + improvement value), time-adjusted to current date using ZIP-level appreciation rates. Off-market discount = (Est. Market Value − Max Offer) ÷ Est. Market Value. Pins with insufficient data to compute a reliable estimate are ghosted.
Off-market pins only appear when all of the following are met:
Acquiring at pre-SB 1123 pricing is the core of our return model. The spread between acquisition cost and exit value is only achievable if we buy before the market reprices. Direct-to-homeowner outreach and speed of close (no listing process, no competing bids) are our structural advantages.
Adjust assumptions below. All pins reprice live.
1123 Acquisition Platform
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