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BRIGHTSTAR LOTTERY PLC: selling, general and administrative expense

Selling, general and administrative expense for BRIGHTSTAR LOTTERY PLC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All BRIGHTSTAR LOTTERY PLC financial histories

What this measure means

Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.

Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. 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 2013-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.

Selected filing history

Selling, general and administrative expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31215,000,000USD2026-02-2420-F · 0001628280-26-011083
2024-01-012024-12-31235,000,000USD2026-02-2420-F · 0001628280-26-011083
2023-01-012023-12-31246,000,000USD2026-02-2420-F · 0001628280-26-011083
2022-01-012022-12-31400,000,000USD2025-02-2520-F · 0001619762-25-000007
2021-01-012021-12-31810,000,000USD2024-03-1220-F · 0001619762-24-000017
2020-01-012020-12-31707,000,000USD2023-02-2820-F · 0001619762-23-000014
2019-01-012019-12-31850,000,000USD2022-03-0320-F · 0001619762-22-000022
2018-01-012018-12-31845,503,000USD2021-03-0220-F · 0001619762-21-000010
2017-01-012017-12-31816,093,000USD2020-03-0320-F · 0001619762-20-000018
2016-01-012016-12-31945,824,000USD2019-03-0820-F · 0001619762-19-000007
2015-01-012015-12-31795,252,000USD2018-03-1520-F · 0001628280-18-003245
2014-01-012014-12-31413,001,000USD2017-04-2020-F · 0001628280-17-003934
2013-01-012013-12-31402,264,000USD2016-04-2920-F · 0001104659-16-116304

Related financial histories

Inspect the source

Entity
BRIGHTSTAR LOTTERY PLC / CIK 0001619762
Captured
2026-09-21T17:21:44.000Z
SEC response SHA-256
417d0790a80026b0c4e2b8dedd886f784129b2499fe666a1f242f97a933f5b01

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001619762.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"])))