FIFA World Cup 26 Seattle

Seattle & King County Economic Impact In partnership with The Data Guys™
Command Center
Seattle & King County · June 15 – July 6, 2026 · data current to September 29, 2026

The tournament had a radius. Inside about a mile of Lumen Field it delivered everything promised; beyond it, the effect thinned quickly, and some neighbourhoods went backwards. Every page of this dashboard is one angle on that fact. Follow the five chapters below, or jump to any page from the navigation.

Official Economic Impact
$889M
Visit Seattle · published Sep 22, 2026
Class A · Visit Seattle
Official State & Local Tax
$109M
~20,000 jobs supported
Class A · Visit Seattle
Stadium Attendance
401,400
5 of 6 sellouts · 1 game 150 short
Class A · FIFA
Downtown Match-Day Visits
>3M
+17% vs same 2025 days
Class B · DSA/Placer.ai
June Link Boardings
5.4M
All-time monthly record
Class A · Sound Transit
Documented Floor vs Official
$489M → $889M
Bridged by 3 disclosed assumptions
Class B · Independent Triangulation
Hotel Occupancy Gap
-6.3pp
Largest among 11 host cities
Class B · HVS
Hotel ADR Peak
$271.80
+30.5% YoY (week ending Jun 20)
Class B · CoStar/STR
Combined Transit (6 Match Days)
~3.4M
Metro + Sound Transit
Class A/B · Metro/ST
WA Public Investment
~$120M
KUOW estimate · appropriations
Class C · KUOW
Visitors, Matches + Watch Parties
~1.3M
45% from outside Seattle · ~1 in 3 stayed overnight
Class A · Visit Seattle
Sea-Tac Passengers, Jun–Jul
−0.01%
Flat YoY · intl slightly up, domestic slightly down
Class A · Port of Seattle
THE OFFICIAL FIGURE IS NOW PUBLISHED — $889M

Visit Seattle released its post-event economic impact report on September 22, 2026, reporting $889 million in total economic impact for Seattle and King County, $109 million in state and local tax revenue, and approximately 20,000 jobs supported. That result lands below the original $929M December 2024 projection and above the $846M forecast revised in March 2026.

The gap between that headline and the $489M modeled independently here is not a data dispute. It resolves into three modelling choices: the 12% displacement adjustment, the 1.42× RIMS II multiplier versus the 1.84× implied by Tourism Economics’ New York/New Jersey study, and assumed spending per visitor. Applying all three alternatives to the same underlying evidence produces roughly $850M — within 5% of the published $889M. The bridge was built before the report was issued and it held. See Benchmarks & Reconciliation for the step-by-step derivation.

$80B Global Projection vs $40B Reality
FIFA's global gross output projection vs Bank of America's confirmed actual · Source: FIFA, Bank of America
Seattle Forecast vs Modeled Evidence
Forecast vs independent triangulated calculation · 5-method triangulation with displacement adjustment
Forecast vs Calculated Actual: The Gap
Every headline metric: pre-event forecast vs independent post-event calculated estimate · showing the delta
MetricPre-Event ForecastPost-Event CalculatedVarianceSource
Total Economic Impact$845.6M$489M-42.1%Independent 5-method triangulation
Direct Visitor Spending~$600M (implied)$391M-34.8%Independent weighted triangulation
Tax Revenue (Direct)$96M$15.5M-83.9%Independent 4-method from actual receipts
Tax Revenue (w/ Multiplier)$96M$22M-77.1%Independent 4-method × 1.42x IMPLAN
Hotel Occupancy~85% (expected)76.8%-8.2ppHVS actual
Hotel ADR~$208 (baseline)$271.80+30.5%CoStar/STR actual
International Visitors~225K (forecast)180K-20.0%KUOW/Visit Seattle
CID Sales+10% (expected)-22%-32ppNW Asian Weekly actual
Pioneer Square SalesBaseline3-10x typical+200-900%DSA/Placer.ai actual
Key finding: The gap between forecast and calculated actual is driven by: (1) hotel occupancy flat vs expected surge (-6.3pp gap, largest of 11 host cities), (2) CID displacement (-22% sales despite +10% foot traffic), (3) lower international visitors than forecast (-20%), (4) >60% of dollars captured by FIFA/airlines/hotels before reaching local merchants (Facteus). The ADR surge (+30.5%) was real but didn't translate to proportional economic impact because occupancy was flat.
Scenario Analysis: Conservative / Base / High
Wider range reflects genuine uncertainty in visitor spend, displacement, and multiplier assumptions
ScenarioDirect SpendingMultiplierDisplacementTotal Impactvs Forecast
Conservative$280M1.35x15%$321M-62%
Base (Central)$391M1.42x12%$489M-42%
High$520M1.50x8%$718M-15%
Conservative: Bottom-up Method B only ($118M × 1.35 after displacement) + partial Method D uplift. Assumes high displacement (15%), low multiplier (1.35x), low visitor spend.
Base: 5-method weighted triangulation ($391M direct) × 1.42x IMPLAN multiplier × 12% displacement. Central scenario.
High: Top-down Method A adjusted ($540M gross × 1.50 after displacement). Assumes low displacement (8%), high multiplier (1.50x), higher visitor spend, minimal leakage. Still below forecast due to flat occupancy and CID displacement.
Post-Event Calculation Workbench
Transparent methodology: inputs, formulas, and sensitivity drivers

Formulas Used

FormulaCalculationResult
Direct Spending (Weighted)0.30×A + 0.30×B + 0.15×C + 0.15×D + 0.10×E$391M
Total ImpactDirect × Multiplier × (1 - Displacement)$489M
Tax (Direct)Lodging×15.70% + Restaurants×10.25% + Retail×10.25% + Transport×8% + B&O×1.5%$15.5M
Tax (w/ Multiplier)Direct Tax × 1.42x IMPLAN$22M

5-Method Inputs

MethodApproachInput ValueWeight
A: Top-Down180K intl × 12d × $350 + 225K dom × 6d × $250$1,094M30%
B: Bottom-UpHVS $44M + Toast $25M + Square $11M + Transit $18M + Events $10M$118M30%
C: BofA Macro+5% of Seattle GDP × 35 days$81M15%
D: DSA/Datafy$821.6M × 6.89% × 40% WC portion$21M15%
E: Tax ImpliedTax receipts / 10% blended rate$126M10%
TriangulatedWeighted average$391M100%

What Would Change the Answer Most

#Sensitivity DriverCurrent AssumptionIf ChangedImpact
1Visitor home ZIP / nonlocal share405K visitors, 180K intlIf 250K intl: +$100M direct±$100M
2Merchant NAICS + ZIP card spendNot public (gap)Would replace Method D with actuals±$50M
3Final KC/Seattle tax collections (after Jul lag)Through Jun onlyQ3 data would validate Method E±$30M
4Hotel + STR displacement rate12% (mid)If 5%: +$40M; if 20%: -$40M±$40M
5FIFA/venue/vendor local procurementNot measuredWould add B2B spending+$50-100M
Seattle's Six Matches at Lumen Field
5 of 6 sellouts · 401,400 total · Source: FIFA/SBJ
Evidence Classification System

Class A — Official measured data from government/agency sources (FIFA, Sound Transit, ESD, SPU)

Class B — Provider sample data from commercial platforms (CoStar/STR, Placer.ai, Square, Toast, Datafy, AirDNA, HVS)

Class C — Appropriation/authorization data from legislative sources (WA Session Law, Seattle ordinances, King County budget)

Class D — Published forecast/model, not realized outcome (Tourism Economics $929M / $845.6M projections)

Class E — Not publicly available; requires direct data-owner access (DOR tax receipts, FIFA ticket origin, granular ZIP spending)

PUBLICATION RULE
Forecasts are "verified" only in the sense that a named source really published the forecast. They are not verified realized outcomes. They must not appear in a headline that says "FIFA generated $X" until the post-event model is reconciled to actual visitor, spend, tax, labor and public-cost data.