Methodology · white paper

How the Lotvox Turnover Index works

A transparent, weighted 0–100 score for every residential parcel in a farm territory, recomputed nightly from recorded county facts, calibrated separately for each ZIP against that ZIP's own recorded sales, and published only where a held-out backtest beats random. It is not a black-box model, and it does not describe people. Engine fs-2.0.0.

108 of 288
ZIPs with a published, backtested score
20.2–46.4%
held-out capture across live ZIPs (random = 20%)
1,223,520
parcels scored in the latest nightly run
2026-09-09
latest run

Snapshot 2026-09-10 from the engine's own ledger; see every ZIP's number.

1.What the score is — and is not

The score sums calibrated points for recorded facts about a parcel and caps at 100. Each point traces to a specific county record, and every surface that shows the score can open that decomposition. Weights are data, versioned per territory, never code; the engine refuses to run a ZIP without a complete, backtested weight set.

It is not a probability and it is not a judgment about an owner. Points are 20 × log₂(lift) per factor, so the total is an indicative multiple of the ZIP's own base sale rate: a score of 20 reads as roughly twice the base rate, 40 as roughly four times. The ladder below is that arithmetic, named. The measured claim is never the band — it is the per-ZIP held-out capture in section 4.

7Baseline14ElevatedTop 20%27High35Very high48Peak
Baseline0–9· about the ZIP's base rateElevated10–19· roughly 1.4–2× baseHigh20–29· roughly 2–3× baseVery high30–39· roughly 3–4× basePeak40–100· 4× base and up

The quintile chip ("Top 20%") is the territory-relative rank the engine computes each night; in the pilot ZIP the top-quintile cutoff is a score of 14, so band and rank are shown together — a modest absolute score can still be the most active fifth of its ZIP.

2.Data rails

  • County and public records only. Assessor rolls, recorder instruments and public-trustee filings. No listing-service data of any kind feeds the score, on any surface.
  • Nothing about people. No census attributes, no household characteristics, no purchased "intent" data. Factors describe the property and its recorded instruments — tenure, deed class, entity form, block turnover — never a person's class or state. That is the Fair-Housing posture, by construction.
  • Read-only on the public tables. The engine writes only to its own schema; scoring and display only. No outreach is initiated anywhere in it.
  • Parcel detail stays behind the territory subscription. Public pages — this one, the accuracy map, the market pages — show coverage and market-level facts only.

3.The factor dictionary

factordefinitionsource
No recorded prior deedno deed of record on the parcel (new construction on snapshot counties; rapid churn on Jefferson's 4-deep arrays; cannot fire in full-chain counties)assessor / recorder
Purchase recencyyears since the last recorded deed, bucketed under 2 and 2–6recorder
Low appreciation since purchaseestimated appreciation since purchase under 35%assessor value vs recorded price
Attached producttownhome or condo per the assessor's property typeassessor
Block turnovershare of parcels within roughly 500 m that sold in the trailing 24 months exceeds 14%recorder + assessor coordinates
Absentee mailingtax-bill mailing address differs from the situsassessor
Owner entitytrust / estate, or LLC, on the recorded owner namerecorder
Life-event deedthe latest recorded instrument is a quitclaim, personal-representative or death-class deed within 3 years, per a county-specific document-code maprecorder
Pending trustee salea public-trustee (NED) filing address-matched to the parcel, evidence string keptpublic trustee

Points per factor differ by territory (section 5). Where a county record cannot determine a factor, the factor is absent — rendered "—", never guessed — and a source-map test keeps every factor registered.

4.How a score earns the right to be shown: the render gate

Every offered ZIP is backtested point-in-time: parcels are scored as of a past date using only facts knowable then, and the outcome is an arm's-length deed recorded afterwards (quitclaims, death certificates and personal-representative deeds are excluded from the label — a quitclaim is not a listing). The claim graded is top-quintile capture: of the parcels that later sold, what share were already in the top 20% on the scoring date. Random chance is 20%.

A ZIP goes live only when its own held-out capture exceeds 20% on at least 30 held-out sales — the floor below which a capture number is noise. Everything else renders "Score pending" with the reason recorded: 131 ZIPs with too few recorded outcomes yet, 30 that did not beat random, 19 where county records hold no leakage-free history. Never a number worse than a coin flip.

countyofferedliveheld-out capture avg (min–max)held-out salessubstrate
Maricopa, AZ1333028.3% (20.4–43.2)1,305a dated pre-image snapshot with no post-outcome contamination
Jefferson, CO262130.3% (23.2–46.4)4,075the county's raw 4-deep sale/deed arrays
Denver, CO271322.9% (20.2–27.9)2,398current snapshot, restricted to factors a sale does not overwrite
Larimer, CO181226.9% (20.5–40)3,724full sale chains — point-in-time features from the recorded history
Weld, CO321126.5% (20.5–35.4)1,442full sale chains — point-in-time features from the recorded history
Douglas, CO141126.4% (20.8–35)4,148current snapshot, restricted to factors a sale does not overwrite
Adams, CO16824.4% (21.6–31.6)598full sale chains — point-in-time features from the recorded history
Broomfield, CO2226.1% (25.8–26.3)791a dated pre-image snapshot with no post-outcome contamination
Arapahoe, CO190no leakage-free substrate — nothing here is backtestable yet
Larimer, WY10full sale chains — point-in-time features from the recorded history

5.Why one national model fails: the calibration story

The pilot territory (Broomfield 80020, backtest dated 2026-08-29: features from a January-2025 pre-image snapshot, outcomes Feb 2025 – Jun 2026, 1,743 sellers, base rate 7.15%) inverted the folk heuristic that "long tenure plus high equity equals seller". Measured point-in-time, the sale rate falls with tenure and with accumulated appreciation — the sellers were recent buyers and new construction, not long-tenured high-equity owners:

sale rate by tenure (80020, full window)
0–2 yrs since deed9.46%
25+ yrs4.42%
sale rate by appreciation since purchase
below 0% appreciation9.56%
over 80%3.25%

The two end-points of each ladder are the figures the backtest report quotes; it records the path between them as monotone. A model tuned to the heuristic would have ranked this ZIP upside down.

Scaling to every offered territory (2026-08-30) made the point structural. The same factor name means different things on different county substrates: "no recorded prior deed" is new construction on a snapshot county, rapid churn on Jefferson's 4-deep sale arrays (where it earns ~40 points), and cannot fire at all in counties with 40-year sale chains (0 points, Adams and Weld). Phoenix's dominant signal is purchase recency at twice the pilot's weight; life-event deeds, fixed at 10 in the pilot, measure up to 19–21 points in older Weld and Larimer communities; Douglas clears the gate on block turnover alone. Two Sun City ZIPs failed the gate outright — a retirement-market selling pattern the gate refused to paper over.

So there is no shared classifier. Each ZIP gets a time-split calibration where it has at least 150 calibration outcomes, a county-pooled fit below that (flagged as such), and Maricopa runs leave-one-ZIP-out because its sale dates are month-granular and its affidavit feed lags about two months. Validation is always the ZIP's own held-out outcomes. Weights are then refit on the full window and stored per territory with their honesty label — zip-calibrated, county-pooled or fixed-uncalibrated — and the engine refuses any ZIP without them.

6.Where it fails (stated, not smoothed)

  • Modest separation at the top. In the pilot, the first and second quintiles were nearly tied out of sample (4.80% vs 4.84% sale rate); the top-40% vs bottom-60% split is the cleaner line.
  • Signal decay. The heaviest calibrated factors burn down as builder close-outs and product waves pass; purchase recency and low appreciation are the durable ones. Weights are recalibrated, not frozen.
  • Part of the factor set is not backtestable everywhere. Snapshot counties carry no historical owner or mailing data, so absentee, entity, life-event and trustee factors there ship with fixed, labeled weights. The proof loop exists to replace them with measured numbers.
  • One temporal fold per county. One snapshot vintage is one fold, not a walk-forward. Every future pre-image and every night's ledger row extends the evidence.
  • Fresh score, stale substrate. Scores recompute nightly, but county rolls advance roughly monthly and owner signals weekly; every run records its feature vintages and the surfaces print them.
  • Phoenix lags. Month-granular sale dates and a ~2-month affidavit lag mean Maricopa grades accrue about two months behind Colorado's.

7.The live accuracy panel: grading in public

Every night the engine records each territory's top quintile permanently. As county deed feeds advance, a view grades every past run: of the parcels that later recorded an arm's-length deed, the share that were top-quintile that night. The panel is served raw — never smoothed — on the score board and, per ZIP, on the accuracy map.

1,300
nightly runs graded since first scoring
2026-08-29
scoring since
0
deeds recorded after scoring, so far
accruing
pooled live capture so far

No post-scoring deed has reached the county rolls yet — the panel says so rather than showing a number it has not earned. The published backtest capture per ZIP stands as the claim until the live grade accrues.

8.The honest claim

"Scored months before the deed recorded, about one in four of the homes that actually sold in the pilot ZIP were already in the board's top 20% — measured on recorded county deeds, graded nightly in public view."

That is the shape of every claim this score supports: the ZIP's own measured capture, dated, beside the random baseline. Not "predicts 87% of sellers", not a national accuracy figure — the per-ZIP number is the product, and the accuracy map publishes all of them.

Sources: county assessor and recorder public records and public-trustee filings; engine ledger (schema farm_score: score_runs, backtests, territory_gate, quintile_history). Backtest reports dated 2026-08-29 (pilot) and 2026-08-30 (all offered territories). Turnover Index is calibrated and graded per ZIP; a territory with no live score shows "Score pending" everywhere it appears.