diff --git a/transform/sqlmesh_padelnomics/models/serving/location_profiles.sql b/transform/sqlmesh_padelnomics/models/serving/location_profiles.sql
index 68f2197..0fd5b9a 100644
--- a/transform/sqlmesh_padelnomics/models/serving/location_profiles.sql
+++ b/transform/sqlmesh_padelnomics/models/serving/location_profiles.sql
@@ -5,15 +5,18 @@
 --
 -- Two scores per location:
 --
--- Padelnomics Market Score (Marktreife-Score v3, 0–100):
+-- Padelnomics Market Score (Marktreife-Score v4, 0–100):
 --   "How mature/established is this padel market?"
 --   Only meaningful for locations matched to a dim_cities row (city_slug IS NOT NULL)
 --   with padel venues. 0 for all other locations.
 --
---   40 pts  supply development — log-scaled density (LN ceiling 20/100k) × count gate
---   25 pts  demand evidence   — occupancy when available; 40% density proxy otherwise
+--   v4 changes: lower count gate (5→3), lower density ceiling (LN(21)→LN(11)),
+--   better demand fallback (0.4→0.65 with 0.3 floor), economic context discrimination (200→25K).
+--
+--   40 pts  supply development — log-scaled density (LN ceiling 10/100k) × count gate (3)
+--   25 pts  demand evidence   — occupancy when available; 65% density proxy + 0.3 floor otherwise
 --   15 pts  addressable market — log-scaled population, ceiling 1M
---   10 pts  economic context  — income PPS normalised to 200 ceiling
+--   10 pts  economic context  — income PPS normalised to 25,000 ceiling
 --   10 pts  data quality      — completeness discount
 --
 -- Padelnomics Opportunity Score (Marktpotenzial-Score v4, 0–100):
@@ -146,34 +149,38 @@ market_scored AS (
       WHEN population > 0 OR  COALESCE(city_padel_venue_count, 0) > 0 THEN 0.5
       ELSE 0.0
     END AS data_confidence,
-    -- ── Market Score (Marktreife-Score v3) ──────────────────────────────────
+    -- ── Market Score (Marktreife-Score v4) ──────────────────────────────────
     -- 0 when no city match or no venues (city_padel_venue_count NULL or 0)
     CASE WHEN COALESCE(city_padel_venue_count, 0) > 0 THEN
       ROUND(
         -- Supply development (40 pts)
+        -- density ceiling 10/100k (LN(11)), count gate 3 venues
         40.0 * LEAST(1.0, LN(
             COALESCE(
               CASE WHEN population > 0
                 THEN COALESCE(city_padel_venue_count, 0)::DOUBLE / population * 100000
                 ELSE 0 END
-            , 0) + 1) / LN(21))
-             * LEAST(1.0, COALESCE(city_padel_venue_count, 0) / 5.0)
+            , 0) + 1) / LN(11))
+             * LEAST(1.0, COALESCE(city_padel_venue_count, 0) / 3.0)
         -- Demand evidence (25 pts)
+        -- with occupancy: scale to 65% target. Without: 65% of supply proxy + 0.3 floor
+        -- (existence of venues IS evidence of demand)
         + 25.0 * CASE
             WHEN median_occupancy_rate IS NOT NULL
               THEN LEAST(1.0, median_occupancy_rate / 0.65)
-            ELSE 0.4 * LEAST(1.0, LN(
+            ELSE GREATEST(0.3, 0.65 * LEAST(1.0, LN(
                 COALESCE(
                   CASE WHEN population > 0
                     THEN COALESCE(city_padel_venue_count, 0)::DOUBLE / population * 100000
                     ELSE 0 END
-                , 0) + 1) / LN(21))
-                     * LEAST(1.0, COALESCE(city_padel_venue_count, 0) / 5.0)
+                , 0) + 1) / LN(11))
+                     * LEAST(1.0, COALESCE(city_padel_venue_count, 0) / 3.0))
           END
         -- Addressable market (15 pts)
         + 15.0 * LEAST(1.0, LN(GREATEST(population, 1)) / LN(1000000))
         -- Economic context (10 pts)
-        + 10.0 * LEAST(1.0, COALESCE(median_income_pps, 100) / 200.0)
+        -- ceiling 25,000 PPS discriminates between wealthy and poorer markets
+        + 10.0 * LEAST(1.0, COALESCE(median_income_pps, 15000) / 25000.0)
         -- Data quality (10 pts)
         + 10.0 * CASE
             WHEN population > 0 AND COALESCE(city_padel_venue_count, 0) > 0 THEN 1.0