Scenario Builder
Configure assumptions, adjust parameters, run evaluations · Changes propagate in real-time
📋 SCN-2034-042
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APPROVED1. Tournament Clustering Strategy
How should teams be distributed across host cities?
🏛 Anchor City
🗺 Regional Cluster
✈ National Rotation
▶Concentrates 80% of fixtures in Riyadh & Jeddah.
▶Creates high accommodation pressure in primary cities.
▶Minimises inter-city travel burden for teams.
2. Visitor Admission Policy
Ticketed Only
1:1 Non-Ticketed
Open Entry
Ticketed fans only. Most conservative estimate.
Host City Selection
Click a city to toggle it on/off. Deselecting cities concentrates demand on remaining ones.
✓
Riyadh
8 stadiums
✓
Jeddah
4 stadiums
✓
Al Khobar
1 stadium
✓
NEOM
1 stadium
✓
Abha
1 stadium
All 5 cities selected. Load distributed across full network.
3. Demand Parameters
Domestic Fans1.4M
800K1.6M2.5M
GCC Arrivals520K
200K700K1.2M
International Visitors850K
300K1.15M2M
Umrah Overlap Visitors0
0400K800K
Media, VIP & Officials55K
20K70K120K
4. Capacity & Infrastructure
Hotel Room Keys300K
Current: 300K
2030 Target: 640K
100K450K800K
Public Transit Capacity (trips/day)800K
500K1.75M3M
Road Network Capacity (vehicle moves/day)3.2M
2M5M8M
Security Personnel30K
20K50K80K
5. Operational Parameters
6. Planning Timeline (2027-2034)
Select a year to view monthly planning milestones
Map Preview: Anchor City
Preliminary Outcomes
Based on current parameter configuration
3.84M
Visitors
412K
Peak Daily
0.91
Accom. Index
91%
Transport
78%
FIFA Score
2
Cities at Risk
Audit Trail0 entries
Scenario Dashboard
Deep results for Anchor City, Peak Load · Last evaluated: just now
Peak Daily Volume
412K
▲ 8% above threshold
Accommodation Index
0.91
Riyadh at 1.12, Critical
Transport Utilisation
91%
Air corridors near capacity
FIFA Compliance
78%
3 criteria below threshold
Host Cities5 Cities
KSA Tournament Footprint · Live GIS
Anchor City15 Stadiums
Visitors (Peak)25K▲ 6%
Transit Load76%▲ 12%
Avg Delays12 min▲ 4
Carbon Footprint18%▼ 2%
Match Day
2:00 PM
11 PM
Visitor Arc (64 Days)
Accommodation Pressure by City
Transport Corridor Load
City Demand DistributionAI Engine
Security & Workforce Intensity
🏆
King Salman International Stadium · Riyadh
Stadium Operations Twin · Powered by stc Mobility Intelligence
LIVE SIMULATION
Match: KSA vs Brazil · Group A
Date: 14 Dec 2034
Visitor Volume
0K+18% vs last
Peak hour: T-30 min · 18:30
Transport Split
Car48%
Metro28%
Bus14%
Uber10%
Live Operational Insight
Light arrivals. Hospitality & VIP checking in. Pre-stage Gates A & D.
Visitor Type Flow
Domestic (Saudi)
GCC Arrivals
International
Media / VIP
Metro Line 6
King Salman International Stadium
NE Riyadh · King Abdulaziz Park · 92,000 seats
Stadium Status PRE-MATCH
Occupancy0%
Gates Open6 / 6
Security
Standard
EMS
On Site
Parking
12%
Crowd Mood
Calm
Selected Corridor Click a road
Click any road on the map to see live bidirectional flow, V/C ratio, LOS, and visitor breakdown.
Phase Brief
Slide the timeline to see how visitor flow, stadium occupancy, and security posture evolve from 3 hours pre-match to 3 hours post-match.
stcinsights
Mobility Intelligence · King Salman Stadium
Total Visitors
0
of 92,000 capacity · 0%
Growth
+18%
vs comparable group-stage match
Peak Hour
18:30
T-30 min · expected peak ingress
Arrival Timing
Hourly arrivals · distribution shape evolves with phase
Visitor Mix
By origin segment · live composition
Domestic 64%
GCC 18%
International 14%
VIP / Hospitality 4%
Transport Split
Mode share · shifts toward metro near kick-off
🚗
Private Car
48%
🚝
Metro · Line 6
28%
🚌
Bus / Shuttle
14%
🚕
Uber / Careem
10%
Top Origins
International · tied to ticket-purchase telemetry
Countries
🇧🇷Brazil14%
🇦🇷Argentina9%
🇩🇪Germany7%
🇬🇧UK5%
🇫🇷France4%
Top Cities (Domestic)
Riyadh38%
Jeddah14%
Dammam7%
Makkah3%
Madinah2%
Demographics
Age bands · gender split (population trait)
♂72%Male
♀28%Female
Visit Frequency
Repeat visits per visitor (rolling 12 months)
1 visit65%
2-3 visits22%
4-7 visits9%
8+ visits4%
35% of visitors are repeat — loyalty signal for season-pass programmes.
Bank
Card-issuer share · from ticket & F&B transactions
ARAl Rajhi Bank32%
SNBSaudi National Bank24%
RBRiyad Bank12%
SABSaudi British Bank (SAB)9%
BSFBanque Saudi Fransi8%
ANBArab National Bank7%
+Other (Alinma / Albilad / Visa intl)8%
Booking App
Travel platform usage · correlates with international arrivals
B.
am
A
A
M
+
International visitor surge raises Booking.com share. Domestic-heavy phases shift toward Almosafer / Mosafer.
Interests
Lifestyle preferences · from app-usage signals
⚽Sport82%
🎪Entertainment64%
🍽Dining58%
🛍Shopping42%
Scenario Comparison
Side-by-side analysis of clustering archetypes with qualitative assessment
Select Scenarios to Compare
Multi-Axis Comparison (Spider)
KPI Bar Comparison
Metric Comparison Table
| Metric | 🏛 Anchor | 🗺 Regional | ✈ Rotation |
|---|---|---|---|
| Projected Visitors | 3.84M | 3.22M | 4.51M |
| Peak Daily Volume | 412K | 328K | 502K |
| Accommodation Index | 0.91 | 0.72 | 1.18 |
| Transport Utilisation | 91% | 78% | 108% |
| FIFA Compliance | 78% | 91% | 64% |
| Cities at Risk | 2 | 0 | 4 |
| Travel Burden | Low | Medium | High |
| Security Complexity | Medium | Low | High |
| Legacy Distribution | Concentrated | Balanced | National |
Risk Traffic-Light Matrix
Low Risk Moderate Risk High Risk
AI Qualitative AnalysisAI-Assisted
Demand Heatmap
Real-time temporal demand simulation with hour-by-hour playback across all 104 match days.
🔒 Coming Soon
64-day timeline scrubber
GIS heatmap overlays
Hourly demand curves
Peak hour analytics
Supply vs Demand
Comprehensive gap analysis between infrastructure capacity and projected demand across host cities.
🔒 Coming Soon
City-by-city gap analysis
Overload detection
Capacity vs demand
Drill-down by asset
Impact Assessment
Infrastructure readiness scoring, operational risk matrix, and automated mitigation recommendations.
🔒 Coming Soon
Readiness matrix
Risk identification
AI recommendations
City readiness
Analytics & Export
Deep analytics with 64-day trend analysis, scenario history, and executive decision pack generation.
🔒 Coming Soon
Executive PDF packs
Full Excel exports
GIS data packages
Trend analytics
Glossary & Guide
Key terms, metrics definitions, and how to read the platform outputs
Core Metrics
Accommodation Index
Ratio of projected visitor demand to available hotel/lodging capacity. Below 0.80 = comfortable surplus. 0.80-0.99 = elevated pressure. 1.00+ = demand exceeds supply. A value of 1.12 means demand is 12% above capacity.
Peak Daily Volume
Highest single-day visitor count across the tournament. Typically occurs during Round of 16. Comfort threshold: 380K. Above this, infrastructure stress increases non-linearly.
Transport Utilisation
% of inter-city transport capacity consumed (air, rail, road). Below 75% = nominal. 75-90% = elevated. 90%+ = near saturation. 100%+ = overload.
FIFA Compliance Score
Aggregate alignment with FIFA hosting requirements across: stadium capacity, training sites, accommodation, transport, fan zones, medical, broadcast. 80%+ = compliant. Below = remediation required.
Cities at Risk
Count of host cities where critical thresholds are breached (accommodation >1.0, transport >95%, or stadium utilisation >100%). Require intervention plans.
Fan Zone Capacity
% of city visitor allocation directed to official fan zones. Higher values require more open-space infrastructure and crowd management.
Security Posture
Level of security deployment. Standard = normal. Enhanced = elevated threat response. Maximum = full military-grade deployment.
Clustering Archetypes
Anchor City
Concentrates 80% of fixtures in Riyadh & Jeddah. Teams assigned a home base for group-stage. Advantage: minimal travel. Risk: extreme accommodation pressure.
Regional Cluster
Groups cities into geographic corridors (Western, Central, Eastern). Advantage: balanced load, best FIFA compliance. Risk: moderate cross-corridor travel.
National Rotation
Distributes fixtures evenly across all 15 stadiums. Advantage: maximum national exposure. Risk: highest transport burden.
Admission Policies
Ticketed Only
Only ticket-holding fans access precincts. Most conservative demand estimate. Baseline assumption.
1:1 Non-Ticketed
One additional non-ticketed visitor per ticket-holder. Increases demand by ~28%.
Open Entry
Fan zones open to all. Maximum stress-test: +55% above baseline.
How to Read the Platform
Colour Coding
Green = safe. Amber = approaching threshold. Red = breach.
Scenario Propagation
Changing any assumption recalculates all downstream metrics in real-time across all dashboards and reports.
Quick vs Detailed Eval
Quick Eval = fast 3-second headline KPIs. Detailed Eval = comprehensive 15-second simulation with city breakdowns, corridor analysis, and AI recommendations.
Planning Timeline
2027-2034 timeline with key planning milestones. Tournament window: Nov-Dec 2034.