merge: market_score v3 + opportunity_score v2 recalibration

CHANGELOG.md

@@ -6,6 +6,15 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
 ## [Unreleased]
 
+### Changed
+- **Market Score v3 (Marktreife-Score recalibration)** — fixes ranking inversion where early-stage markets (Germany 1/100k) outscored mature markets (Spain 36/100k):
+  - **Formula rewrite** (`city_market_profile.sql`): supply development now 40 pts (log-scaled density LN(d+1)/LN(21) × count gate min(1,count/5)); demand evidence 25 pts (occupancy or 40% density proxy); population reduced to 15 pts (context); income to 10 pts (context); data quality to 10 pts; saturation discount removed
+  - **Count gate** eliminates small-town inflation: a single venue in a 5k-resident town can no longer outscore Berlin (was 92.7 → now 43.9 for Bernau bei Berlin)
+  - **LN ceiling at 20/100k** (was linear 4/100k) gives meaningful differentiation from 0 to 20: Málaga 70.1, Barcelona 67.4, Madrid 66.9, Amsterdam 58.4, Berlin 42.2, London 44.1
+  - **Template thresholds updated** across all 3 pSEO templates (city-cost-de, country-overview, city-pricing): color coding green ≥55 (was ≥65) / amber ≥35 (was ≥40); intro/FAQ tiers strong ≥55 (was ≥70) / mid ≥35 (was ≥45); white-space signal interplay market_score < 40 (was < 50)
+
+- **Opportunity Score supply gap ceiling raised 4→8/100k** (`location_opportunity_profile.sql`) — gentler gradient for partially-served markets; accounts for ~87% data undercount vs FIP real-world totals. Documents discovered formula behaviour: DuckDB `LEAST(1.0, NULL)=1.0` means NULL catchment already yields full 15 pts; income PPS saturates for all EU countries; tennis courts data currently empty (formula correct, data pending)
+
 ### Added
 - **Opportunity Score integration** — second scoring dimension (`Marktpotenzial`) now visible in city and country articles:
   - **SQL chain**: `dim_cities` now carries `geoname_id` (from the existing GeoNames LEFT JOIN); threaded through `city_market_profile` → `pseo_city_costs_de` which LEFT JOINs `location_opportunity_profile` on `(country_code, geoname_id)`; `pseo_country_overview` gains `avg_opportunity_score`, `top_opportunity_score`, `top_opportunity_slugs`, `top_opportunity_names`

PROJECT.md

@@ -1,7 +1,7 @@
 # Padelnomics — Project Tracker
 
 > Move tasks across columns as you work. Add new tasks at the top of the relevant column.
-> Last updated: 2026-02-25.
+> Last updated: 2026-02-27.
 
 ---
 
@@ -87,6 +87,8 @@
 - [x] Markets hub (`/<lang>/markets`) — article listing with FTS + country/region filters
 - [x] DuckDB refresh script (`refresh_from_daas.py`)
 - [x] **Opportunity Score integration** — `opportunity_score` (Marktpotenzial) wired into city + country templates; `geoname_id` threaded through SQL chain (dim_cities → city_market_profile → pseo_city_costs_de); 71.4% city match rate; stats strip, intro paragraphs, market tables, and FAQ updated in both DE + EN
+- [x] **Market Score v3 recalibration** — fixes ranking inversion (Germany 1/100k was outscoring Spain 36/100k); log-scaled density + count gate replaces linear formula; saturation discount removed; template thresholds updated across all 3 pSEO templates; verified: Málaga 70.1, Barcelona 67.4, Madrid 66.9, Amsterdam 58.4, Bernau 43.9 (was 92.7), Berlin 42.2, London 44.1
+- [x] **Opportunity Score v2** — supply gap ceiling raised 4→8/100k (gentler gradient, accounts for 87% data undercount); formula documentation added (DuckDB LEAST NULL behaviour, income saturation, tennis data gap)
 
 ### Data Pipeline (DaaS)
 - [x] Overpass API extractor (OSM padel courts)

transform/sqlmesh_padelnomics/models/serving/city_market_profile.sql

@@ -1,16 +1,18 @@
 -- One Big Table: per-city padel market intelligence.
 -- Consumed by: SEO article generation, planner city-select pre-fill, API endpoints.
 --
--- Padelnomics Marktreife-Score v2 (0–100):
+-- Padelnomics Marktreife-Score v3 (0–100):
 -- Answers "How mature/established is this padel market?"
 -- Only computed for cities with ≥1 padel venue (padel_venue_count > 0).
 -- For white-space opportunity scoring, see serving.location_opportunity_profile.
 --
---   30 pts  population  — log-scaled to 1M+ city ceiling
+--   40 pts  supply development — log-scaled density (LN ceiling 20/100k) × count gate
---   25 pts  income PPS  — normalised to 200 ceiling (covers CH/NO/LU outliers)
+--                                (min(1, count/5) kills small-town inflation)
---   30 pts  demand      — observed occupancy if available, else venue density
+--   25 pts  demand evidence   — occupancy when available; 40% density proxy otherwise
---   15 pts  data quality — completeness discount, not a market signal
+--   15 pts  addressable market — log-scaled population, ceiling 1M (context only)
---   ×0.85   saturation  — discount when venues_per_100k > 8 (oversupplied market)
+--   10 pts  economic context  — income PPS normalised to 200 ceiling
+--   10 pts  data quality      — completeness discount
+--   No saturation discount: high density = maturity, not a penalty
 
 MODEL (
   name serving.city_market_profile,
@@ -61,28 +63,29 @@ WITH base AS (
 scored AS (
   SELECT *,
     ROUND(
-      -- Population (30 pts): log-scale, 1M+ city = full marks.
+      -- Supply development (40 pts): THE maturity signal.
-      -- LN(1) = 0 so unpopulated cities score 0 here — they still score on demand.
+      -- Log-scaled density: LN(density+1)/LN(21) → 20/100k ≈ full marks.
-      30.0 * LEAST(1.0, LN(GREATEST(population, 1)) / LN(1000000))
+      -- Count gate: min(1, count/5) — 1 venue=20%, 5+ venues=100%.
-      -- Economic power (25 pts): income PPS normalised to 200 ceiling.
+      -- Kills small-town inflation (1 court / 5k pop = 20/100k) without hard cutoffs.
-      -- 200 covers high-income outliers (CH ~190, NO ~180, LU ~200+).
+      40.0 * LEAST(1.0, LN(COALESCE(venues_per_100k, 0) + 1) / LN(21))
-      -- Drives pricing power and willingness-to-pay directly.
+           * LEAST(1.0, padel_venue_count / 5.0)
-      + 25.0 * LEAST(1.0, COALESCE(median_income_pps, 100) / 200.0)
+      -- Demand evidence (25 pts): occupancy when Playtomic data available.
-      -- Demand evidence (30 pts): observed occupancy is the best signal
+      -- Fallback: 40% of density score (avoids double-counting with supply component).
-      -- (proves real demand). If unavailable, venue density is the proxy
+      + 25.0 * CASE
-      -- (proves market exists; caps at 4/100K to avoid penalising dense cities).
-      + 30.0 * CASE
           WHEN median_occupancy_rate IS NOT NULL
             THEN LEAST(1.0, median_occupancy_rate / 0.65)
-          ELSE LEAST(1.0, COALESCE(venues_per_100k, 0) / 4.0)
+          ELSE 0.4 * LEAST(1.0, LN(COALESCE(venues_per_100k, 0) + 1) / LN(21))
+                   * LEAST(1.0, padel_venue_count / 5.0)
         END
-      -- Data quality (15 pts): measures completeness, not market quality.
+      -- Addressable market (15 pts): population as context, not maturity signal.
-      -- Reduced from 20pts — kept as confidence discount, not market signal.
+      -- LN(1) = 0 so zero-pop cities score 0 here.
-      + 15.0 * data_confidence
+      + 15.0 * LEAST(1.0, LN(GREATEST(population, 1)) / LN(1000000))
+      -- Economic context (10 pts): country-level income PPS.
+      -- Flat per country — kept as context modifier, not primary signal.
+      + 10.0 * LEAST(1.0, COALESCE(median_income_pps, 100) / 200.0)
+      -- Data quality (10 pts): completeness discount.
+      + 10.0 * data_confidence
     , 1)
-    -- Saturation discount: venues_per_100k > 8 signals oversupply.
-    -- ~8/100K ≈ Spain-tier density; above this marginal return decreases.
-    * CASE WHEN venues_per_100k > 8 THEN 0.85 ELSE 1.0 END
                                  AS market_score
   FROM base
 )

transform/sqlmesh_padelnomics/models/serving/location_opportunity_profile.sql

@@ -1,7 +1,7 @@
 -- Per-location padel investment opportunity intelligence.
 -- Consumed by: Gemeinde-level pSEO pages, opportunity map, "top markets" lists.
 --
--- Padelnomics Marktpotenzial-Score (0–100):
+-- Padelnomics Marktpotenzial-Score v2 (0–100):
 -- Answers "Where should I build a padel court?"
 -- Covers ALL GeoNames locations (pop ≥ 1K) — NOT filtered to existing padel markets.
 -- Zero-court locations score highest on supply gap component (white space = opportunity).
@@ -9,9 +9,21 @@
 --   25 pts  addressable market — log-scaled population, ceiling 500K
 --           (opportunity peaks in mid-size cities; megacities already served)
 --   20 pts  economic power     — country income PPS, normalised to 200
---   30 pts  supply gap         — INVERTED venue density; 0 courts/100K = full marks
+--                               NOTE: PPS values are country-level constants in the range
---   15 pts  catchment gap      — distance to nearest padel court (>30km = full marks)
+--                               18k-37k — ALL EU countries saturate this component (20/20).
---   10 pts  sports culture     — tennis courts within 25km (≥10 = full marks)
+--                               Component is a flat uplift per country until city-level
+--                               income data becomes available.
+--   30 pts  supply gap         — INVERTED venue density; 0 courts/100K = full marks.
+--                               Ceiling raised to 8/100K (was 4) for a gentler gradient
+--                               and to account for ~87% data undercount vs FIP totals.
+--                               Linear: GREATEST(0, 1 - density/8)
+--   15 pts  catchment gap      — distance to nearest padel court.
+--                               DuckDB LEAST ignores NULLs: LEAST(1.0, NULL/30) = 1.0,
+--                               so NULL nearest_km = full marks (no court in bounding box
+--                               = high opportunity). COALESCE fallback is dead code.
+--   10 pts  sports culture     — tennis courts within 25km (≥10 = full marks).
+--                               NOTE: dim_locations tennis data is empty (all 0 rows).
+--                               Component contributes 0 pts everywhere until data lands.
 
 MODEL (
   name serving.location_opportunity_profile,
@@ -50,9 +62,11 @@ SELECT
     + 20.0 * LEAST(1.0, COALESCE(l.median_income_pps, 100) / 200.0)
 
     -- Supply gap (30 pts): INVERTED venue density.
-    -- 0 courts/100K = full 30 pts (white space); ≥4/100K = 0 pts (served market).
+    -- 0 courts/100K = full 30 pts (white space); ≥8/100K = 0 pts (served market).
+    -- Ceiling raised from 4→8/100K for a gentler gradient and to account for data
+    -- undercount (~87% of real courts not in our data).
     -- This is the key signal that separates Marktpotenzial from Marktreife.
-    + 30.0 * GREATEST(0.0, 1.0 - COALESCE(l.padel_venues_per_100k, 0) / 4.0)
+    + 30.0 * GREATEST(0.0, 1.0 - COALESCE(l.padel_venues_per_100k, 0) / 8.0)
 
     -- Catchment gap (15 pts): distance to nearest existing padel court.
     -- >30km = full 15 pts (underserved catchment area).

web/src/padelnomics/content/templates/city-cost-de.md.jinja

@@ -21,7 +21,7 @@ priority_column: population
   </div>
   <div class="stats-strip__item">
     <div class="stats-strip__label"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</div>
-    <div class="stats-strip__value" style="color:{% if market_score >= 65 %}#16A34A{% elif market_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ market_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
+    <div class="stats-strip__value" style="color:{% if market_score >= 55 %}#16A34A{% elif market_score >= 35 %}#D97706{% else %}#DC2626{% endif %}">{{ market_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
   </div>
   {% if opportunity_score %}
   <div class="stats-strip__item">
@@ -39,7 +39,7 @@ priority_column: population
   </div>
 </div>
 
-{{ city_name }} erreicht einen **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> von {{ market_score | round(1) }}/100** — damit liegt die Stadt{% if market_score >= 70 %} unter den stärksten Padel-Märkten in {{ country_name_en }}{% elif market_score >= 45 %} im soliden Mittelfeld der Padel-Märkte in {{ country_name_en }}{% else %} in einem frühen Padel-Markt mit Wachstumspotenzial{% endif %}. Aktuell gibt es **{{ padel_venue_count }} Padelanlagen** für {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} Einwohner — das entspricht {{ venues_per_100k | round(1) }} Anlagen pro 100.000 Einwohner.{% if opportunity_score %} Der **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> von {{ opportunity_score | round(1) }}/100** bewertet das Investitionspotenzial — Versorgungslücken, Einzugsgebiet und Sportaffinität der Region:{% if opportunity_score >= 65 and market_score < 50 %} überschaubare Konkurrenz trifft auf starkes Standortpotenzial{% elif opportunity_score >= 65 %} hohes Potenzial trotz bereits aktivem Marktumfeld{% elif opportunity_score >= 40 %} solides Potenzial, der Markt beginnt sich zu verdichten{% else %} der Standort ist vergleichsweise gut versorgt, Differenzierung wird zum Schlüssel{% endif %}.{% endif %}
+{{ city_name }} erreicht einen **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> von {{ market_score | round(1) }}/100** — damit liegt die Stadt{% if market_score >= 55 %} unter den stärksten Padel-Märkten in {{ country_name_en }}{% elif market_score >= 35 %} im soliden Mittelfeld der Padel-Märkte in {{ country_name_en }}{% else %} in einem frühen Padel-Markt mit Wachstumspotenzial{% endif %}. Aktuell gibt es **{{ padel_venue_count }} Padelanlagen** für {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} Einwohner — das entspricht {{ venues_per_100k | round(1) }} Anlagen pro 100.000 Einwohner.{% if opportunity_score %} Der **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> von {{ opportunity_score | round(1) }}/100** bewertet das Investitionspotenzial — Versorgungslücken, Einzugsgebiet und Sportaffinität der Region:{% if opportunity_score >= 65 and market_score < 40 %} überschaubare Konkurrenz trifft auf starkes Standortpotenzial{% elif opportunity_score >= 65 %} hohes Potenzial trotz bereits aktivem Marktumfeld{% elif opportunity_score >= 40 %} solides Potenzial, der Markt beginnt sich zu verdichten{% else %} der Standort ist vergleichsweise gut versorgt, Differenzierung wird zum Schlüssel{% endif %}.{% endif %}
 
 Die entscheidende Frage für Investoren: Was bringt ein Padel-Investment bei den aktuellen Preisen, Auslastungsraten und Baukosten tatsächlich? Das Finanzmodell unten rechnet mit echten Marktdaten aus {{ city_name }}.
 
@@ -102,7 +102,7 @@ Eine detaillierte Preisanalyse mit Preisspannen und Vergleichsdaten findest Du a
 <details>
 <summary>Ist {{ city_name }} ein guter Standort für eine Padelhalle?</summary>
 
-{{ city_name }} erreicht **{{ market_score | round(1) }}/100** auf dem <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score, der Bevölkerungsgröße, Anlagendichte und Datenqualität berücksichtigt. {% if market_score >= 70 %}Ein Score über 70 signalisiert einen starken Markt: große Bevölkerung, wachsende Anlagenzahl und belastbare Preisdaten. {% elif market_score >= 45 %}Ein mittlerer Score bedeutet solide Grundlagen, aber einen teils stärker umkämpften oder datenlimitierten Markt. {% else %}Ein niedrigerer Score spricht für eine kleinere Stadt, begrenzte Datenlage oder einen Markt im Aufbau — was gleichzeitig weniger Wettbewerb und First-Mover-Vorteile bedeuten kann. {% endif %}Mit dem [Finanzplaner](/{{ language }}/planner) kannst Du Deine eigenen Annahmen durchrechnen.
+{{ city_name }} erreicht **{{ market_score | round(1) }}/100** auf dem <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score, der Anlagendichte, Bevölkerungsgröße und Datenqualität berücksichtigt. {% if market_score >= 55 %}Ein Score über 55 signalisiert einen starken Markt: etablierte Anlagendichte, wachsende Spielerbasis und belastbare Preisdaten. {% elif market_score >= 35 %}Ein mittlerer Score bedeutet solide Grundlagen, aber einen teils stärker umkämpften oder datenlimitierten Markt. {% else %}Ein niedrigerer Score spricht für einen Markt im frühen Aufbau — was gleichzeitig weniger Wettbewerb und First-Mover-Vorteile bedeuten kann. {% endif %}Mit dem [Finanzplaner](/{{ language }}/planner) kannst Du Deine eigenen Annahmen durchrechnen.
 </details>
 
 <details>
@@ -161,7 +161,7 @@ Der **Market Score ({{ market_score | round(1) }}/100)** misst die *Marktreife*:
   </div>
   <div class="stats-strip__item">
     <div class="stats-strip__label"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</div>
-    <div class="stats-strip__value" style="color:{% if market_score >= 65 %}#16A34A{% elif market_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ market_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
+    <div class="stats-strip__value" style="color:{% if market_score >= 55 %}#16A34A{% elif market_score >= 35 %}#D97706{% else %}#DC2626{% endif %}">{{ market_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
   </div>
   {% if opportunity_score %}
   <div class="stats-strip__item">
@@ -179,7 +179,7 @@ Der **Market Score ({{ market_score | round(1) }}/100)** misst die *Marktreife*:
   </div>
 </div>
 
-{{ city_name }} has a **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> of {{ market_score | round(1) }}/100** — placing it{% if market_score >= 70 %} among the strongest padel markets in {{ country_name_en }}{% elif market_score >= 45 %} in the mid-tier of {{ country_name_en }}'s padel markets{% else %} in an early-stage padel market with room for growth{% endif %}. The city currently has **{{ padel_venue_count }} padel venues** serving a population of {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} residents — a density of {{ venues_per_100k | round(1) }} venues per 100,000 people.{% if opportunity_score %} The **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> of {{ opportunity_score | round(1) }}/100** scores investment potential — supply gaps, catchment reach, and sports culture as a demand proxy:{% if opportunity_score >= 65 and market_score < 50 %} limited competition meets strong location fundamentals{% elif opportunity_score >= 65 %} strong potential despite an already active market{% elif opportunity_score >= 40 %} solid potential as the market starts to fill in{% else %} the area is comparatively well-served; differentiation is the key lever{% endif %}.{% endif %}
+{{ city_name }} has a **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> of {{ market_score | round(1) }}/100** — placing it{% if market_score >= 55 %} among the strongest padel markets in {{ country_name_en }}{% elif market_score >= 35 %} in the mid-tier of {{ country_name_en }}'s padel markets{% else %} in an early-stage padel market with room for growth{% endif %}. The city currently has **{{ padel_venue_count }} padel venues** serving a population of {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} residents — a density of {{ venues_per_100k | round(1) }} venues per 100,000 people.{% if opportunity_score %} The **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> of {{ opportunity_score | round(1) }}/100** scores investment potential — supply gaps, catchment reach, and sports culture as a demand proxy:{% if opportunity_score >= 65 and market_score < 40 %} limited competition meets strong location fundamentals{% elif opportunity_score >= 65 %} strong potential despite an already active market{% elif opportunity_score >= 40 %} solid potential as the market starts to fill in{% else %} the area is comparatively well-served; differentiation is the key lever{% endif %}.{% endif %}
 
 The question investors actually need answered is: given current pricing, occupancy, and build costs, what does the return look like? The financial model below uses real {{ city_name }} market data to give you that answer.
 
@@ -242,7 +242,7 @@ For a detailed pricing breakdown with price ranges and venue comparisons, see th
 <details>
 <summary>Is {{ city_name }} a good location for a padel center?</summary>
 
-{{ city_name }} scores **{{ market_score | round(1) }}/100** on the <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score, which accounts for population size, existing venue density, and data completeness. {% if market_score >= 70 %}A score above 70 indicates a strong market: high population, growing venue count, and solid pricing data. {% elif market_score >= 45 %}A mid-range score means decent fundamentals but a more competitive or data-limited market. {% else %}A lower score reflects either a smaller city, sparse venue data, or an early-stage market — which can also mean lower competition and first-mover advantage. {% endif %}Use the [Padelnomics planner](/{{ language }}/planner) to model your specific assumptions.
+{{ city_name }} scores **{{ market_score | round(1) }}/100** on the <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score, which primarily reflects venue density alongside population size and data completeness. {% if market_score >= 55 %}A score above 55 indicates a strong market: established venue density, a growing player base, and solid pricing data. {% elif market_score >= 35 %}A mid-range score means decent fundamentals but a more competitive or data-limited market. {% else %}A lower score reflects an early-stage market — which can also mean lower competition and first-mover advantage. {% endif %}Use the [Padelnomics planner](/{{ language }}/planner) to model your specific assumptions.
 </details>
 
 <details>

web/src/padelnomics/content/templates/city-pricing.md.jinja

@@ -55,7 +55,7 @@ Die Preisspanne von {{ hourly_rate_p25 | round(0) | int }} bis {{ hourly_rate_p7
 
 ## Wie steht {{ city_name }} im Vergleich da?
 
-{{ city_name }} hat {{ padel_venue_count }} Padelanlagen für {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} Einwohner ({{ venues_per_100k | round(1) }} Anlagen pro 100K Einwohner). {% if market_score >= 65 %}Mit einem <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> von {{ market_score | round(1) }}/100 gehört {{ city_name }} zu den stärksten Padel-Märkten in {{ country_name_en }} — höhere Auslastung und Preise sind typisch für dichte, etablierte Märkte. {% elif market_score >= 40 %}Ein Market Score von {{ market_score | round(1) }}/100 steht für einen Markt im Aufbau: genug Angebot für marktgerechte Preise, aber Raum für neue Anlagen. {% else %}Ein Market Score von {{ market_score | round(1) }}/100 deutet auf einen Markt in der Frühphase hin, in dem sich Preise und Auslastung mit dem Wachstum des Sports noch deutlich entwickeln können. {% endif %}
+{{ city_name }} hat {{ padel_venue_count }} Padelanlagen für {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} Einwohner ({{ venues_per_100k | round(1) }} Anlagen pro 100K Einwohner). {% if market_score >= 55 %}Mit einem <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> von {{ market_score | round(1) }}/100 gehört {{ city_name }} zu den stärksten Padel-Märkten in {{ country_name_en }} — höhere Auslastung und Preise sind typisch für dichte, etablierte Märkte. {% elif market_score >= 35 %}Ein Market Score von {{ market_score | round(1) }}/100 steht für einen Markt im Aufbau: genug Angebot für marktgerechte Preise, aber Raum für neue Anlagen. {% else %}Ein Market Score von {{ market_score | round(1) }}/100 deutet auf einen Markt in der Frühphase hin, in dem sich Preise und Auslastung mit dem Wachstum des Sports noch deutlich entwickeln können. {% endif %}
 
 Die Anlagendichte von {{ venues_per_100k | round(1) }} pro 100K Einwohner beeinflusst die Preisgestaltung direkt: {% if venues_per_100k >= 3.0 %}Höhere Dichte bedeutet mehr Wettbewerb, was die Preise eher stabilisiert oder senkt.{% elif venues_per_100k >= 1.0 %}Moderate Dichte ermöglicht marktgerechte Preise bei gleichzeitigem Wachstumsspielraum.{% else %}Niedrige Dichte gibt Betreibern mehr Preissetzungsmacht — vorausgesetzt, die Nachfrage ist da.{% endif %}
 
@@ -168,7 +168,7 @@ The P25–P75 price range of {{ hourly_rate_p25 | round(0) | int }} to {{ hourly
 
 ## How Does {{ city_name }} Compare?
 
-{{ city_name }} has {{ padel_venue_count }} padel venues for a population of {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} ({{ venues_per_100k | round(1) }} venues per 100K residents). {% if market_score >= 65 %}With a <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> of {{ market_score | round(1) }}/100, {{ city_name }} is one of the stronger padel markets in {{ country_name_en }} — higher occupancy and pricing typically follow dense, competitive markets. {% elif market_score >= 40 %}A market score of {{ market_score | round(1) }}/100 reflects a mid-tier market: enough supply to have competitive pricing, but room for new venues to grow. {% else %}A market score of {{ market_score | round(1) }}/100 indicates an early-stage market where pricing and occupancy benchmarks may shift as the sport grows. {% endif %}
+{{ city_name }} has {{ padel_venue_count }} padel venues for a population of {% if population >= 1000000 %}{{ (population / 1000000) | round(1) }}M{% else %}{{ (population / 1000) | round(0) | int }}K{% endif %} ({{ venues_per_100k | round(1) }} venues per 100K residents). {% if market_score >= 55 %}With a <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> of {{ market_score | round(1) }}/100, {{ city_name }} is one of the stronger padel markets in {{ country_name_en }} — higher occupancy and pricing typically follow dense, competitive markets. {% elif market_score >= 35 %}A market score of {{ market_score | round(1) }}/100 reflects a mid-tier market: enough supply to have competitive pricing, but room for new venues to grow. {% else %}A market score of {{ market_score | round(1) }}/100 indicates an early-stage market where pricing and occupancy benchmarks may shift as the sport grows. {% endif %}
 
 Venue density of {{ venues_per_100k | round(1) }} per 100K residents directly influences pricing: {% if venues_per_100k >= 3.0 %}higher density means more competition, which tends to stabilize or compress prices.{% elif venues_per_100k >= 1.0 %}moderate density supports market-rate pricing with room for growth.{% else %}low density gives operators more pricing power — provided demand exists.{% endif %}
 

web/src/padelnomics/content/templates/country-overview.md.jinja

@@ -26,7 +26,7 @@ priority_column: total_venues
   </div>
   <div class="stats-strip__item">
     <div class="stats-strip__label"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</div>
-    <div class="stats-strip__value" style="color:{% if avg_market_score >= 65 %}#16A34A{% elif avg_market_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_market_score }}<span class="stats-strip__unit">/100</span></div>
+    <div class="stats-strip__value" style="color:{% if avg_market_score >= 55 %}#16A34A{% elif avg_market_score >= 35 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_market_score }}<span class="stats-strip__unit">/100</span></div>
   </div>
   {% if avg_opportunity_score %}
   <div class="stats-strip__item">
@@ -40,15 +40,15 @@ priority_column: total_venues
   </div>
 </div>
 
-In {{ country_name_en }} erfassen wir aktuell **{{ total_venues }} Padelanlagen** in **{{ city_count }} Städten**. Der durchschnittliche <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> liegt bei **{{ avg_market_score }}/100**{% if avg_market_score >= 65 %} — ein starker Markt mit breiter Infrastruktur und belastbaren Preisdaten{% elif avg_market_score >= 40 %} — ein wachsender Markt mit guter Abdeckung{% else %} — ein aufstrebender Markt, in dem Früheinsteiger noch Premiumstandorte sichern können{% endif %}.
+In {{ country_name_en }} erfassen wir aktuell **{{ total_venues }} Padelanlagen** in **{{ city_count }} Städten**. Der durchschnittliche <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> liegt bei **{{ avg_market_score }}/100**{% if avg_market_score >= 55 %} — ein starker Markt mit breiter Infrastruktur und belastbaren Preisdaten{% elif avg_market_score >= 35 %} — ein wachsender Markt mit guter Abdeckung{% else %} — ein aufstrebender Markt, in dem Früheinsteiger noch Premiumstandorte sichern können{% endif %}.
 
 ## Marktlandschaft
 
 Padel wächst in {{ country_name_en }} mit bemerkenswertem Tempo. Unsere Daten zeigen {{ total_venues }} erfasste Anlagen — eine Zahl, die angesichts nicht auf Buchungsplattformen gelisteter Clubs vermutlich noch höher liegt. Der durchschnittliche <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score von {{ avg_market_score }}/100 über {{ city_count }} Städte spiegelt sowohl die Marktreife als auch die Datenverfügbarkeit wider.
 
-{% if avg_market_score >= 65 %}Märkte mit Scores über 65 weisen in der Regel eine etablierte Spielerbasis, belastbare Preisdaten und berechenbare Nachfragemuster auf — entscheidend für eine solide Finanzplanung. Dennoch bleiben viele Städte unterversorgt: Selbst in reifen Märkten variiert die Anlagendichte pro 100.000 Einwohner erheblich.{% elif avg_market_score >= 40 %}Ein Score im mittleren Bereich deutet auf eine Wachstumsphase hin: Die Nachfrage ist nachweisbar, die Anlageninfrastruktur baut sich auf, und Preise haben sich noch nicht vollständig auf Wettbewerbsniveau eingependelt. Das eröffnet Chancen für gut positionierte Neueintritte.{% else %}Aufstrebende Märkte bieten First-Mover-Vorteile — weniger direkte Konkurrenz, potenziell attraktivere Mietkonditionen und die Möglichkeit, eine loyale Spielerbasis aufzubauen, bevor sich der Markt verdichtet.{% endif %}
+{% if avg_market_score >= 55 %}Märkte mit Scores über 55 weisen in der Regel eine etablierte Spielerbasis, belastbare Preisdaten und berechenbare Nachfragemuster auf — entscheidend für eine solide Finanzplanung. Dennoch bleiben viele Städte unterversorgt: Selbst in reifen Märkten variiert die Anlagendichte pro 100.000 Einwohner erheblich.{% elif avg_market_score >= 35 %}Ein Score im mittleren Bereich deutet auf eine Wachstumsphase hin: Die Nachfrage ist nachweisbar, die Anlageninfrastruktur baut sich auf, und Preise haben sich noch nicht vollständig auf Wettbewerbsniveau eingependelt. Das eröffnet Chancen für gut positionierte Neueintritte.{% else %}Aufstrebende Märkte bieten First-Mover-Vorteile — weniger direkte Konkurrenz, potenziell attraktivere Mietkonditionen und die Möglichkeit, eine loyale Spielerbasis aufzubauen, bevor sich der Markt verdichtet.{% endif %}
 
-{% if avg_opportunity_score %}Der durchschnittliche **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> von {{ avg_opportunity_score }}/100** zeigt, wie viel Investitionspotenzial in {{ country_name_en }} noch unerschlossen ist. {% if avg_opportunity_score >= 60 and avg_market_score < 50 %}Die Kombination aus hohem Opportunity Score und moderatem Market Score macht {{ country_name_en }} besonders interessant: Nachfragepotenzial und Sportaffinität sind vorhanden, die Infrastruktur noch im Aufbau — First-Mover-Konditionen für gut gewählte Standorte.{% elif avg_opportunity_score >= 60 %}Trotz eines bereits aktiven Markts gibt es noch Standorte mit erheblichem Potenzial — vor allem in mittelgroßen Städten und an der Peripherie großer Ballungsräume.{% else %}Viele Standorte in {{ country_name_en }} sind bereits gut versorgt. Neue Projekte brauchen eine sorgfältige Standortanalyse und ein klares Differenzierungsprofil.{% endif %}{% endif %}
+{% if avg_opportunity_score %}Der durchschnittliche **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> von {{ avg_opportunity_score }}/100** zeigt, wie viel Investitionspotenzial in {{ country_name_en }} noch unerschlossen ist. {% if avg_opportunity_score >= 60 and avg_market_score < 40 %}Die Kombination aus hohem Opportunity Score und moderatem Market Score macht {{ country_name_en }} besonders interessant: Nachfragepotenzial und Sportaffinität sind vorhanden, die Infrastruktur noch im Aufbau — First-Mover-Konditionen für gut gewählte Standorte.{% elif avg_opportunity_score >= 60 %}Trotz eines bereits aktiven Markts gibt es noch Standorte mit erheblichem Potenzial — vor allem in mittelgroßen Städten und an der Peripherie großer Ballungsräume.{% else %}Viele Standorte in {{ country_name_en }} sind bereits gut versorgt. Neue Projekte brauchen eine sorgfältige Standortanalyse und ein klares Differenzierungsprofil.{% endif %}{% endif %}
 
 ## Top-Städte in {{ country_name_en }}
 
@@ -122,7 +122,7 @@ Unsere Spitzenstadt nach <span style="font-family:'Bricolage Grotesque',sans-ser
 <details>
 <summary>Wie schnell wächst Padel in {{ country_name_en }}?</summary>
 
-Padel gehört zu den am schnellsten wachsenden Racketsportarten in Europa. Mit {{ total_venues }} erfassten Anlagen in {{ city_count }} Städten zeigt {{ country_name_en }} {% if avg_market_score >= 65 %}bereits eine reife Infrastruktur — Wachstum kommt hier vor allem aus steigender Spielfrequenz und Premiumangeboten{% elif avg_market_score >= 40 %}eine klare Wachstumsdynamik mit steigender Nachfrage und neuen Anlagen{% else %}ein frühes Wachstumsstadium mit großem Potenzial für Neueintritte{% endif %}. Die Sportart profitiert von niedriger Einstiegshürde, hohem Spaßfaktor und starker Mund-zu-Mund-Verbreitung.
+Padel gehört zu den am schnellsten wachsenden Racketsportarten in Europa. Mit {{ total_venues }} erfassten Anlagen in {{ city_count }} Städten zeigt {{ country_name_en }} {% if avg_market_score >= 55 %}bereits eine reife Infrastruktur — Wachstum kommt hier vor allem aus steigender Spielfrequenz und Premiumangeboten{% elif avg_market_score >= 35 %}eine klare Wachstumsdynamik mit steigender Nachfrage und neuen Anlagen{% else %}ein frühes Wachstumsstadium mit großem Potenzial für Neueintritte{% endif %}. Die Sportart profitiert von niedriger Einstiegshürde, hohem Spaßfaktor und starker Mund-zu-Mund-Verbreitung.
 </details>
 
 <details>
@@ -158,7 +158,7 @@ Der **Market Score (Ø {{ avg_market_score }}/100)** bewertet die Marktreife: Be
   </div>
   <div class="stats-strip__item">
     <div class="stats-strip__label"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</div>
-    <div class="stats-strip__value" style="color:{% if avg_market_score >= 65 %}#16A34A{% elif avg_market_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_market_score }}<span class="stats-strip__unit">/100</span></div>
+    <div class="stats-strip__value" style="color:{% if avg_market_score >= 55 %}#16A34A{% elif avg_market_score >= 35 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_market_score }}<span class="stats-strip__unit">/100</span></div>
   </div>
   {% if avg_opportunity_score %}
   <div class="stats-strip__item">
@@ -172,15 +172,15 @@ Der **Market Score (Ø {{ avg_market_score }}/100)** bewertet die Marktreife: Be
   </div>
 </div>
 
-{{ country_name_en }} has **{{ total_venues }} padel venues** tracked across **{{ city_count }} cities**. The average <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> across tracked cities is **{{ avg_market_score }}/100**{% if avg_market_score >= 65 %} — a strong market with widespread venue penetration and solid pricing data{% elif avg_market_score >= 40 %} — a growing market with healthy city coverage{% else %} — an emerging market where early entrants can still capture prime locations{% endif %}.
+{{ country_name_en }} has **{{ total_venues }} padel venues** tracked across **{{ city_count }} cities**. The average <a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score</a> across tracked cities is **{{ avg_market_score }}/100**{% if avg_market_score >= 55 %} — a strong market with widespread venue penetration and solid pricing data{% elif avg_market_score >= 35 %} — a growing market with healthy city coverage{% else %} — an emerging market where early entrants can still capture prime locations{% endif %}.
 
 ## Market Landscape
 
 Padel is growing rapidly across {{ country_name_en }}. Our data tracks {{ total_venues }} venues — a figure that likely understates the true count given independent clubs not listed on booking platforms. The average <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score of {{ avg_market_score }}/100 across {{ city_count }} cities reflects both market maturity and data availability.
 
-{% if avg_market_score >= 65 %}Markets scoring above 65 typically show an established player base, reliable pricing data, and predictable demand patterns — all critical for sound financial planning. Yet even in mature markets, venue density per 100,000 residents varies significantly between cities, pointing to pockets of underserved demand.{% elif avg_market_score >= 40 %}A mid-range score signals a growth phase: demand is proven, venue infrastructure is building, and pricing hasn't fully settled to competitive levels. This creates opportunities for well-positioned new entrants who can secure good locations before the market matures.{% else %}Emerging markets offer first-mover advantages — less direct competition, potentially better lease terms, and the opportunity to build a loyal player base before the market fills out. The trade-off is less pricing data and more uncertainty in demand projections.{% endif %}
+{% if avg_market_score >= 55 %}Markets scoring above 55 typically show an established player base, reliable pricing data, and predictable demand patterns — all critical for sound financial planning. Yet even in mature markets, venue density per 100,000 residents varies significantly between cities, pointing to pockets of underserved demand.{% elif avg_market_score >= 35 %}A mid-range score signals a growth phase: demand is proven, venue infrastructure is building, and pricing hasn't fully settled to competitive levels. This creates opportunities for well-positioned new entrants who can secure good locations before the market matures.{% else %}Emerging markets offer first-mover advantages — less direct competition, potentially better lease terms, and the opportunity to build a loyal player base before the market fills out. The trade-off is less pricing data and more uncertainty in demand projections.{% endif %}
 
-{% if avg_opportunity_score %}The average **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> of {{ avg_opportunity_score }}/100** shows how much investment potential remains untapped in {{ country_name_en }}. {% if avg_opportunity_score >= 60 and avg_market_score < 50 %}The combination of a high Opportunity Score and a moderate Market Score makes {{ country_name_en }} particularly attractive for new entrants: demand potential and sports culture are there, infrastructure is still building — first-mover conditions for well-chosen locations.{% elif avg_opportunity_score >= 60 %}Despite an already active market, locations with significant potential remain — particularly in mid-size cities and at the periphery of major metro areas.{% else %}Many locations in {{ country_name_en }} are already well-served. New projects need careful site selection and a clear differentiation strategy to compete.{% endif %}{% endif %}
+{% if avg_opportunity_score %}The average **<a href="/{{ language }}/market-score" style="text-decoration:none"><span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score</a> of {{ avg_opportunity_score }}/100** shows how much investment potential remains untapped in {{ country_name_en }}. {% if avg_opportunity_score >= 60 and avg_market_score < 40 %}The combination of a high Opportunity Score and a moderate Market Score makes {{ country_name_en }} particularly attractive for new entrants: demand potential and sports culture are there, infrastructure is still building — first-mover conditions for well-chosen locations.{% elif avg_opportunity_score >= 60 %}Despite an already active market, locations with significant potential remain — particularly in mid-size cities and at the periphery of major metro areas.{% else %}Many locations in {{ country_name_en }} are already well-served. New projects need careful site selection and a clear differentiation strategy to compete.{% endif %}{% endif %}
 
 ## Top Cities in {{ country_name_en }}
 
@@ -254,7 +254,7 @@ Our top-ranked city by <span style="font-family:'Bricolage Grotesque',sans-serif
 <details>
 <summary>How fast is padel growing in {{ country_name_en }}?</summary>
 
-Padel is one of the fastest-growing racquet sports in Europe. With {{ total_venues }} venues tracked across {{ city_count }} cities, {{ country_name_en }} shows {% if avg_market_score >= 65 %}a mature infrastructure — growth here comes mainly from increasing play frequency and premium offerings{% elif avg_market_score >= 40 %}clear growth momentum with rising demand and new venues opening{% else %}early-stage growth with significant potential for new entrants{% endif %}. The sport benefits from a low barrier to entry, high enjoyment factor, and strong word-of-mouth growth among players.
+Padel is one of the fastest-growing racquet sports in Europe. With {{ total_venues }} venues tracked across {{ city_count }} cities, {{ country_name_en }} shows {% if avg_market_score >= 55 %}a mature infrastructure — growth here comes mainly from increasing play frequency and premium offerings{% elif avg_market_score >= 35 %}clear growth momentum with rising demand and new venues opening{% else %}early-stage growth with significant potential for new entrants{% endif %}. The sport benefits from a low barrier to entry, high enjoyment factor, and strong word-of-mouth growth among players.
 </details>
 
 <details>