merge: opportunity-score-integration — expose Marktpotenzial score in city + country articles

CHANGELOG.md

@@ -7,6 +7,13 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 ## [Unreleased]
 
 ### 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`
+  - **71.4% match rate** — 3,350 of 4,693 cities matched to a GeoNames `geoname_id`; unmatched cities gracefully show no Opportunity Score
+  - **City articles** (`city-cost-de.md.jinja`) — `{% if opportunity_score %}` guard adds: 5th stats-strip item with green/amber/red color coding (≥65/≥40/<40), contextual intro sentence explaining the score interplay, table row in Market Overview, score explainer FAQ (DE + EN)
+  - **Country overview articles** (`country-overview.md.jinja`) — adds: `avg_opportunity_score` as 5th stats-strip item, opportunity interplay paragraph in market landscape section, "Top Locations by Investment Potential" table (distinct from top Market Score cities), score explainer FAQ (DE + EN)
+  - **CSS**: stats-strip changed from `repeat(4, 1fr)` to `repeat(auto-fit, minmax(140px, 1fr))` — supports 4-item country and 5-item city strips without layout breakage
+
 - **Pipeline Console admin section** — full operational visibility into the data engineering pipeline at `/admin/pipeline/`:
   - **Overview tab** — extraction status grid (one card per workflow with status dot, schedule, last-run timestamp, error preview), serving table row counts from `_serving_meta.json`, landing zone file stats (per-source file count + total size)
   - **Extractions tab** — filterable, paginated run history table from `.state.sqlite` (extractor + status dropdowns, HTMX live filter); stale "running" row detection (amber highlight) with "Mark Failed" button; "Run All Extractors" button enqueues `run_extraction` task

PROJECT.md

@@ -86,6 +86,7 @@
 - [x] URL prefix fix: articles stored without lang prefix (was causing `/en/en/markets/...`), all consumers updated
 - [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
 
 ### Data Pipeline (DaaS)
 - [x] Overpass API extractor (OSM padel courts)

transform/sqlmesh_padelnomics/models/foundation/dim_cities.sql

@@ -75,7 +75,7 @@ uk_pop AS (
 ),
 -- GeoNames global fallback (all cities ≥50K)
 geonames_pop AS (
-  SELECT city_name, country_code, population, ref_year
+  SELECT geoname_id, city_name, country_code, population, ref_year
   FROM staging.stg_population_geonames
   QUALIFY ROW_NUMBER() OVER (PARTITION BY geoname_id ORDER BY ref_year DESC) = 1
 )
@@ -153,7 +153,10 @@ SELECT
   )::INTEGER                                                 AS population_year,
   vc.padel_venue_count,
   ci.median_income_pps,
-  ci.income_year
+  ci.income_year,
+  -- GeoNames ID: FK to dim_locations / location_opportunity_profile.
+  -- NULL when city name doesn't match any GeoNames entry.
+  gn.geoname_id
 FROM venue_cities vc
 LEFT JOIN country_income ci ON vc.country_code = ci.country_code
 -- Eurostat EU population (via city code→name lookup)

transform/sqlmesh_padelnomics/models/serving/city_market_profile.sql

@@ -33,6 +33,7 @@ WITH base AS (
     c.padel_venue_count,
     c.median_income_pps,
     c.income_year,
+    c.geoname_id,
     -- Venue density: padel venues per 100K residents
     CASE WHEN c.population > 0
       THEN ROUND(c.padel_venue_count::DOUBLE / c.population * 100000, 2)
@@ -107,6 +108,7 @@ SELECT
   s.median_occupancy_rate,
   s.median_daily_revenue_per_venue,
   s.price_currency,
+  s.geoname_id,
   CURRENT_DATE                   AS refreshed_date
 FROM scored s
 ORDER BY s.market_score DESC

transform/sqlmesh_padelnomics/models/serving/pseo_city_costs_de.sql

@@ -27,6 +27,7 @@ SELECT
   c.padel_venue_count,
   c.venues_per_100k,
   c.market_score,
+  lop.opportunity_score,
   c.data_confidence,
   -- Pricing (from Playtomic, NULL when no coverage)
   c.median_hourly_rate,
@@ -48,6 +49,9 @@ FROM serving.city_market_profile c
 LEFT JOIN serving.planner_defaults p
   ON c.country_code = p.country_code
   AND c.city_slug = p.city_slug
+LEFT JOIN serving.location_opportunity_profile lop
+  ON c.country_code = lop.country_code
+  AND c.geoname_id = lop.geoname_id
 -- Only cities with actual padel presence and at least some rate data
 WHERE c.padel_venue_count > 0
   AND (p.rate_peak IS NOT NULL OR c.median_peak_rate IS NOT NULL)

transform/sqlmesh_padelnomics/models/serving/pseo_country_overview.sql

@@ -23,6 +23,12 @@ SELECT
   -- Top 5 cities by market score for internal linking (DuckDB list slice syntax)
   LIST(city_slug ORDER BY market_score DESC NULLS LAST)[1:5]     AS top_city_slugs,
   LIST(city_name ORDER BY market_score DESC NULLS LAST)[1:5]     AS top_city_names,
+  -- Opportunity score aggregates (NULL-safe: cities without geoname_id match excluded from AVG)
+  ROUND(AVG(opportunity_score), 1)                               AS avg_opportunity_score,
+  MAX(opportunity_score)                                         AS top_opportunity_score,
+  -- Top 5 cities by opportunity score (may differ from top market score cities)
+  LIST(city_slug ORDER BY opportunity_score DESC NULLS LAST)[1:5] AS top_opportunity_slugs,
+  LIST(city_name ORDER BY opportunity_score DESC NULLS LAST)[1:5] AS top_opportunity_names,
   -- Pricing medians across cities (NULL when no Playtomic coverage in country)
   ROUND(MEDIAN(median_hourly_rate), 0)                           AS median_hourly_rate,
   ROUND(MEDIAN(median_peak_rate), 0)                             AS median_peak_rate,

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

@@ -9,7 +9,7 @@ url_pattern: "/markets/{{ country_slug }}/{{ city_slug }}"
 title_pattern: "{% if language == 'de' %}Padel in {{ city_name }} — Investitionskosten & Marktanalyse {{ 'now' | datetimeformat('%Y') }}{% else %}Padel in {{ city_name }} — Investment Costs & Market Analysis {{ 'now' | datetimeformat('%Y') }}{% endif %}"
 meta_description_pattern: "{% if language == 'de' %}Lohnt sich eine Padelhalle in {{ city_name }}? {{ padel_venue_count }} Anlagen, <span style=\"font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em\">padelnomics</span> Market Score {{ market_score | round(1) }}/100 und ein vollständiges Finanzmodell. Stand {{ 'now' | datetimeformat('%B %Y') }}.{% else %}Is {{ city_name }} worth building a padel center in? {{ padel_venue_count }} venues, <span style=\"font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em\">padelnomics</span> Market Score {{ market_score | round(1) }}/100, and a full financial model. Updated {{ 'now' | datetimeformat('%B %Y') }}.{% endif %}"
 schema_type: [Article, FAQPage]
-priority_column: padel_venue_count
+priority_column: population
 ---
 {% if language == "de" %}
 # Lohnt sich eine Padelhalle in {{ city_name }}?
@@ -23,6 +23,12 @@ priority_column: padel_venue_count
     <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>
+  {% if opportunity_score %}
+  <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> Opportunity Score</div>
+    <div class="stats-strip__value" style="color:{% if opportunity_score >= 65 %}#16A34A{% elif opportunity_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ opportunity_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
+  </div>
+  {% endif %}
   <div class="stats-strip__item">
     <div class="stats-strip__label">Spitzenpreis</div>
     <div class="stats-strip__value">{% if median_peak_rate %}{{ median_peak_rate | round(0) | int }}{% else %}—{% endif %}<span class="stats-strip__unit">{% if median_peak_rate %}{{ price_currency }}/Std{% endif %}</span></div>
@@ -33,7 +39,7 @@ priority_column: padel_venue_count
   </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.
+{{ 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 %}
 
 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 }}.
 
@@ -88,7 +94,8 @@ Eine detaillierte Preisanalyse mit Preisspannen und Vergleichsdaten findest Du a
 | Anlagen | {{ padel_venue_count }} |
 | Anlagen pro 100K Einwohner | {{ venues_per_100k | round(1) }} |
 | <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score | {{ market_score | round(1) }}/100 |
-| Datenqualität | {{ (data_confidence * 100) | round(0) | int }}% |
+{% if opportunity_score %}| <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score | {{ opportunity_score | round(1) }}/100 |
+{% endif %}| Datenqualität | {{ (data_confidence * 100) | round(0) | int }}% |
 
 ## FAQ
 
@@ -128,6 +135,14 @@ Das Gesamtinvestment hängt vom Hallentyp (Indoor vs. Outdoor), Grundstückskost
 Der <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score von {{ market_score | round(1) }}/100 zeigt {{ city_name }}s Position unter den erfassten Städten in {{ country_name_en }}. In der [Marktübersicht für {{ country_name_en }}](/{{ language }}/markets/{{ country_slug }}) findest Du den Vergleich aller Städte.
 </details>
 
+{% if opportunity_score %}
+<details>
+<summary>Was ist der Unterschied zwischen Market Score und Opportunity Score?</summary>
+
+Der **Market Score ({{ market_score | round(1) }}/100)** misst die *Marktreife*: Bevölkerungsgröße, bestehende Anlagendichte und Datenqualität. Ein hoher Wert steht für einen etablierten Markt mit belastbaren Preisdaten — und oft auch für mehr Wettbewerb. Der **Opportunity Score ({{ opportunity_score | round(1) }}/100)** dreht die Logik um: Er bewertet *Investitionspotenzial* anhand von Versorgungslücken, Entfernung zur nächsten Anlage und der Tennisinfrastruktur als Proxy für Racket-Sport-Affinität. Hoher Opportunity Score bei niedrigem Market Score — das ist das klassische White-Space-Signal. Hoher Wert in beiden — bewiesene Nachfrage mit noch offenen Standorten.
+</details>
+{% endif %}
+
 <div style="background:#EFF6FF;border:1px solid #BFDBFE;border-radius:12px;padding:1rem 1.25rem;margin:1.5rem 0;">
   Bereit für Deine eigene Kalkulation? →
   <a href="/{{ language }}/planner" style="font-weight:600;color:#1D4ED8;margin-left:0.25rem;">Businessplan erstellen</a>
@@ -148,6 +163,12 @@ Der <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;co
     <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>
+  {% if opportunity_score %}
+  <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> Opportunity Score</div>
+    <div class="stats-strip__value" style="color:{% if opportunity_score >= 65 %}#16A34A{% elif opportunity_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ opportunity_score | round(1) }}<span class="stats-strip__unit">/100</span></div>
+  </div>
+  {% endif %}
   <div class="stats-strip__item">
     <div class="stats-strip__label">Peak Rate</div>
     <div class="stats-strip__value">{% if median_peak_rate %}{{ median_peak_rate | round(0) | int }}{% else %}—{% endif %}<span class="stats-strip__unit">{% if median_peak_rate %}{{ price_currency }}/hr{% endif %}</span></div>
@@ -158,7 +179,7 @@ Der <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;co
   </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.
+{{ 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 %}
 
 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.
 
@@ -213,7 +234,8 @@ For a detailed pricing breakdown with price ranges and venue comparisons, see th
 | Venues | {{ padel_venue_count }} |
 | Venues per 100K residents | {{ venues_per_100k | round(1) }} |
 | <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score | {{ market_score | round(1) }}/100 |
-| Data Confidence | {{ (data_confidence * 100) | round(0) | int }}% |
+{% if opportunity_score %}| <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Opportunity Score | {{ opportunity_score | round(1) }}/100 |
+{% endif %}| Data Confidence | {{ (data_confidence * 100) | round(0) | int }}% |
 
 ## FAQ
 
@@ -253,6 +275,14 @@ Total investment depends on venue type (indoor vs outdoor), land costs, and loca
 {{ city_name }}'s <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score of {{ market_score | round(1) }}/100 reflects its ranking among tracked {{ country_name_en }} cities. See the [{{ country_name_en }} market overview](/{{ language }}/markets/{{ country_slug }}) for a full comparison across cities.
 </details>
 
+{% if opportunity_score %}
+<details>
+<summary>What is the difference between Market Score and Opportunity Score?</summary>
+
+The **Market Score ({{ market_score | round(1) }}/100)** measures *market maturity*: population size, existing venue density, and data quality. A high score signals an established market with reliable pricing data — and typically more competition. The **Opportunity Score ({{ opportunity_score | round(1) }}/100)** inverts that logic: it scores *investment potential* based on supply gaps, distance to the nearest facility, and tennis infrastructure as a proxy for racket sport demand. High Opportunity Score with a low Market Score is the classic white-space signal. High on both means proven demand with open locations still available.
+</details>
+{% endif %}
+
 <div style="background:#EFF6FF;border:1px solid #BFDBFE;border-radius:12px;padding:1rem 1.25rem;margin:1.5rem 0;">
   Ready to run the numbers for {{ city_name }}? →
   <a href="/{{ language }}/planner" style="font-weight:600;color:#1D4ED8;margin-left:0.25rem;">Build your business plan</a>

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

@@ -28,6 +28,12 @@ priority_column: total_venues
     <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>
+  {% if avg_opportunity_score %}
+  <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> Opportunity Score</div>
+    <div class="stats-strip__value" style="color:{% if avg_opportunity_score >= 65 %}#16A34A{% elif avg_opportunity_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_opportunity_score }}<span class="stats-strip__unit">/100</span></div>
+  </div>
+  {% endif %}
   <div class="stats-strip__item">
     <div class="stats-strip__label">Median Spitzenpreis</div>
     <div class="stats-strip__value">{% if median_peak_rate %}{{ median_peak_rate | int }}{% else %}—{% endif %}<span class="stats-strip__unit">{% if median_peak_rate and price_currency %}{{ price_currency }}/Std{% endif %}</span></div>
@@ -42,6 +48,8 @@ Padel wächst in {{ country_name_en }} mit bemerkenswertem Tempo. Unsere Daten z
 
 {% 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_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 %}
+
 ## Top-Städte in {{ country_name_en }}
 
 Die Rangfolge basiert auf dem <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score — einem Komposit aus Bevölkerungsgröße, Anlagendichte und Datenqualität. Städte mit höherem Score bieten in der Regel größere adressierbare Märkte und belastbarere Benchmarks für die Finanzplanung.
@@ -53,6 +61,17 @@ Die Rangfolge basiert auf dem <span style="font-family:'Bricolage Grotesque',san
 
 Jede Stadtseite enthält detaillierte Preisdaten, eine Kosten-Nutzen-Analyse und einen vorkonfigurierten Finanzplaner mit lokalen Marktdaten als Ausgangswerte.
 
+{% if top_opportunity_names and top_opportunity_names | length > 0 %}
+## Top-Standorte nach Investitionspotenzial
+
+Diese Städte erzielen die höchsten Opportunity Scores in {{ country_name_en }} — dort treffen adressierbare Nachfrage auf Versorgungslücken und starke Standortfaktoren. Sie können sich von den Top-Städten nach Market Score unterscheiden: Der Market Score belohnt bestehende Märkte, der Opportunity Score unerschlossenes Potenzial.
+
+| Stadt | Investmentanalyse |
+|-------|-------------------|
+{% for i in range(top_opportunity_names | length) %}| [{{ top_opportunity_names[i] }}](/{{ language }}/markets/{{ country_slug }}/{{ top_opportunity_slugs[i] }}) | [Marktanalyse ansehen →](/{{ language }}/markets/{{ country_slug }}/{{ top_opportunity_slugs[i] }}) |
+{% endfor %}
+{% endif %}
+
 ## Preisüberblick
 
 {% if median_peak_rate %}
@@ -112,6 +131,14 @@ Padel gehört zu den am schnellsten wachsenden Racketsportarten in Europa. Mit {
 Städte mit höherem <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score (wie {{ top_city_names[0] }}) haben in der Regel die umfassendsten Preisdaten, weil dort mehr Anlagen auf Playtomic gelistet sind. In unserem <a href="/{{ language }}/markets/{{ country_slug }}">{{ country_name_en }}-Marktüberblick</a> findest Du alle Städte nach Market Score sortiert.
 </details>
 
+{% if avg_opportunity_score %}
+<details>
+<summary>Was ist der Unterschied zwischen Market Score und Opportunity Score?</summary>
+
+Der **Market Score (Ø {{ avg_market_score }}/100)** bewertet die Marktreife: Bevölkerungsgröße, bestehende Anlagendichte und Datenqualität. Der **Opportunity Score (Ø {{ avg_opportunity_score }}/100)** dreht die Logik um: Er misst Investitionspotenzial — Versorgungslücken, Einzugsgebiet und Tennisinfrastruktur als Proxy für Racket-Sport-Affinität. Für Standortentscheidungen ist die Kombination beider Scores am aussagekräftigsten: Hoher Opportunity Score bei niedrigem Market Score signalisiert White-Space-Chancen. Hoher Wert in beiden zeigt Märkte, in denen Nachfrage belegt ist und trotzdem noch offene Standorte existieren.
+</details>
+{% endif %}
+
 <div style="background:#EFF6FF;border:1px solid #BFDBFE;border-radius:12px;padding:1rem 1.25rem;margin:1.5rem 0;">
   Du überlegst, eine Padelhalle in {{ country_name_en }} zu eröffnen? Rechne Dein Vorhaben mit echten Marktdaten durch →
   <a href="/{{ language }}/planner" style="font-weight:600;color:#1D4ED8;margin-left:0.25rem;">Zum Finanzplaner</a>
@@ -133,6 +160,12 @@ Städte mit höherem <span style="font-family:'Bricolage Grotesque',sans-serif;f
     <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>
+  {% if avg_opportunity_score %}
+  <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> Opportunity Score</div>
+    <div class="stats-strip__value" style="color:{% if avg_opportunity_score >= 65 %}#16A34A{% elif avg_opportunity_score >= 40 %}#D97706{% else %}#DC2626{% endif %}">{{ avg_opportunity_score }}<span class="stats-strip__unit">/100</span></div>
+  </div>
+  {% endif %}
   <div class="stats-strip__item">
     <div class="stats-strip__label">Median Peak Rate</div>
     <div class="stats-strip__value">{% if median_peak_rate %}{{ median_peak_rate | int }}{% else %}—{% endif %}<span class="stats-strip__unit">{% if median_peak_rate and price_currency %}{{ price_currency }}/hr{% endif %}</span></div>
@@ -147,6 +180,8 @@ Padel is growing rapidly across {{ country_name_en }}. Our data tracks {{ total_
 
 {% 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_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 %}
+
 ## Top Cities in {{ country_name_en }}
 
 Cities are ranked by <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score — a composite of population size, venue density, and data quality. Higher-scoring cities generally offer larger addressable markets and more reliable benchmarks for financial planning.
@@ -158,6 +193,17 @@ Cities are ranked by <span style="font-family:'Bricolage Grotesque',sans-serif;f
 
 Each city page includes detailed pricing data, a cost-benefit analysis, and a pre-configured financial planner seeded with local market data.
 
+{% if top_opportunity_names and top_opportunity_names | length > 0 %}
+## Top Locations by Investment Potential
+
+These cities score highest on the Opportunity Score in {{ country_name_en }} — where addressable demand meets supply gaps and strong location fundamentals. They may differ from the top Market Score cities: the Market Score rewards established markets, the Opportunity Score rewards untapped potential.
+
+| City | Market Analysis |
+|------|----------------|
+{% for i in range(top_opportunity_names | length) %}| [{{ top_opportunity_names[i] }}](/{{ language }}/markets/{{ country_slug }}/{{ top_opportunity_slugs[i] }}) | [View investment analysis →](/{{ language }}/markets/{{ country_slug }}/{{ top_opportunity_slugs[i] }}) |
+{% endfor %}
+{% endif %}
+
 ## Pricing Overview
 
 {% if median_peak_rate %}
@@ -217,6 +263,14 @@ Padel is one of the fastest-growing racquet sports in Europe. With {{ total_venu
 Cities with higher <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Scores (like {{ top_city_names[0] }}) typically have the most comprehensive pricing data, because more venues are listed on Playtomic. Browse our <a href="/{{ language }}/markets/{{ country_slug }}">{{ country_name_en }} market overview</a> to see all cities ranked by <span style="font-family:'Bricolage Grotesque',sans-serif;font-weight:800;color:#0F172A;letter-spacing:-0.02em">padelnomics</span> Market Score.
 </details>
 
+{% if avg_opportunity_score %}
+<details>
+<summary>What is the difference between Market Score and Opportunity Score?</summary>
+
+The **Market Score (avg. {{ avg_market_score }}/100)** measures market maturity: population size, existing venue density, and data quality. The **Opportunity Score (avg. {{ avg_opportunity_score }}/100)** inverts that logic: it scores investment potential based on supply gaps, catchment reach, and tennis infrastructure as a proxy for racket sport demand. For site selection, the combination of both scores is the most informative signal. A high Opportunity Score with a low Market Score points to white-space locations. High on both means proven demand with open sites still available.
+</details>
+{% endif %}
+
 <div style="background:#EFF6FF;border:1px solid #BFDBFE;border-radius:12px;padding:1rem 1.25rem;margin:1.5rem 0;">
   Considering a padel center in {{ country_name_en }}? Model your investment with real market data →
   <a href="/{{ language }}/planner" style="font-weight:600;color:#1D4ED8;margin-left:0.25rem;">Open the Planner</a>

web/src/padelnomics/static/css/input.css

@@ -484,7 +484,7 @@
     @apply grid grid-cols-2 gap-3 mb-8;
   }
   @media (min-width: 640px) {
-    .stats-strip { grid-template-columns: repeat(4, 1fr); }
+    .stats-strip { grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); }
   }
   .stats-strip__item {
     @apply bg-soft-white border border-light-gray rounded-lg p-4;