Churchill Downs Inc: operating expenses
Churchill Downs operating expenses: $2.24 billion for the year ending 2025-12-31, up 10.7% on the year. 12 values since 2014, each linked to its SEC filing.
All Churchill Downs Inc financial histories
At a glance
Churchill Downs reported operating expenses of $2.24 billion for the year ending 2025-12-31, up 10.7% from $2.03 billion a year earlier. From 2014 to 2025 it grew at a compound 10.9% a year, from $721.8 million to $2.24 billion. Across the last five reported years it ranged from $1.31 billion (2021-12-31) to $2.24 billion (2025-12-31). That was 76.6% of revenue ($2.93 billion) for the same year.
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.
Exact concept: us-gaap:OperatingExpenses. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2014-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2025-01-01 | 2025-12-31 | 2,242,100,000 | USD | 2026-02-25 | 10-K · 0000020212-26-000025 SEC |
| 2024-01-01 | 2024-12-31 | 2,025,300,000 | USD | 2026-02-25 | 10-K · 0000020212-26-000025 SEC |
| 2023-01-01 | 2023-12-31 | 1,897,700,000 | USD | 2026-02-25 | 10-K · 0000020212-26-000025 SEC |
| 2022-01-01 | 2022-12-31 | 1,488,000,000 | USD | 2025-02-20 | 10-K · 0000020212-25-000051 SEC |
| 2021-01-01 | 2021-12-31 | 1,312,800,000 | USD | 2024-02-21 | 10-K · 0000020212-24-000055 SEC |
| 2020-01-01 | 2020-12-31 | 993,800,000 | USD | 2023-02-22 | 10-K · 0000020212-23-000059 SEC |
| 2019-01-01 | 2019-12-31 | 1,114,000,000 | USD | 2022-02-23 | 10-K · 0000020212-22-000056 SEC |
| 2018-01-01 | 2018-12-31 | 820,200,000 | USD | 2021-02-24 | 10-K · 0000020212-21-000019 SEC |
| 2017-01-01 | 2017-12-31 | 736,900,000 | USD | 2020-02-26 | 10-K · 0000020212-20-000019 SEC |
| 2016-01-01 | 2016-12-31 | 649,900,000 | USD | 2019-02-27 | 10-K · 0000020212-19-000012 SEC |
| 2015-01-01 | 2015-12-31 | 672,300,000 | USD | 2018-02-28 | 10-K · 0000020212-18-000010 SEC |
| 2014-01-01 | 2014-12-31 | 721,800,000 | USD | 2017-02-28 | 10-K · 0000020212-17-000008 SEC |
Related Churchill Downs Inc histories
Inspect the source
- Entity
- Churchill Downs Inc / CIK 0000020212
- Captured
- SEC response SHA-256
78409a51095fa0d2edb8cd11cf696e2bc9c0e2ec05aff5cf3e555f8edc3d1ad9
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
- Get an API key and run your first validation
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- Read the MCP server source and integration examples
The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000020212.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))