EXECUTIVE ANSWER
What does a multi-sport publishing feed need to represent?
A multi-sport publishing feed needs one stable outer contract and sport-specific inner structures. Across the PowerHouse specification, six products are organized per fixture and three per card. Seven combine two selection groups. The target ranges from three tennis match picks to ten golf tournament selections.
The benchmark covers soccer, NBA, NHL, NFL, MLB, US college football, UFC, tennis, and golf. It compares the documented publishing unit and intended selection mix for each package. The result is a product-structure benchmark: it shows what an enterprise integration must be able to express, not which sport is easier to predict.
Summing one target unit from every package produces 59 specified selections. That number is a useful way to describe schema breadth, but it is not a daily inventory forecast. Sports calendars operate at different frequencies, and every delivered record remains subject to schedule, market availability, quality gates, and the active customer licence.
SPECIFICATION DATASET
Nine sports require nine honest product shapes.
| Sport package | Publishing unit | Target output | Selection groups | Target total |
|---|---|---|---|---|
| Soccer | Per fixture | 5 team picks + 3 player props | 5 team picks + 3 player props | 8 |
| NBA | Per fixture | 4 team picks + 3 player props | 4 team picks + 3 player props | 7 |
| NHL | Per fixture | 4 team picks + 3 player props | 4 team picks + 3 player props | 7 |
| NFL | Per fixture | 4 team picks + 3 player props | 4 team picks + 3 player props | 7 |
| MLB | Per fixture | 3 team picks + 3 player props | 3 team picks + 3 player props | 6 |
| College | Per fixture | 3 team picks + 2 player props | 3 team picks + 2 player props | 5 |
| UFC | Per card | 3 fight picks + 3 fighter props | 3 fight picks + 3 fighter props | 6 |
| Tennis | Per card | 3 match picks | 3 match picks | 3 |
| Golf | Per card | 10 tournament picks · minimum 5 | 10 tournament picks | 10 |
OPERATING FINDINGS
Four findings for media, product, and data teams.
The publishing unit must be sport-specific
Six packages are organized per fixture, while UFC, tennis, and golf use card-level products. Treating every sport as one generic game object would hide the event structure that editorial, product, and data teams need.
Selection mix matters as much as the total
Seven packages combine two distinct selection groups. Team picks and player props, or fight picks and fighter props, have different labels, markets, and editorial uses even when they belong to the same event.
Target output is not guaranteed inventory
The specification describes the intended product shape. Schedule, market availability, model quality, and customer licence can reduce the delivered set. Golf makes this explicit with a target of ten and a minimum of five qualified tournament selections.
One normalized contract still creates leverage
Sport-specific products can share event identity, selection, confidence, rationale, timestamps, lifecycle, and attribution fields. A common outer contract reduces integration work without pretending the underlying sports are identical.
The dataset contains 6 fixture-based products, 3 card-based products, and 7 products with multiple selection groups. Those differences should survive every stage of the customer workflow—from API ingestion to editorial presentation.
ARCHITECTURE IMPLICATIONS
Normalize the contract, not the sport itself.
An enterprise schema can standardize stable concepts such as record ID, sport, event reference, market, selection, confidence, rationale, evaluation timestamp, publishing state, and attribution. Those fields let a customer build shared ingestion, storage, entitlement, and lifecycle logic.
The schema should not erase sport-specific meaning. Soccer, NBA, NHL, NFL, MLB, and college packages distinguish team selections from player props. UFC distinguishes fight picks from fighter props. Tennis uses match selections, while golf uses tournament selections. A typed selection group preserves that distinction without creating a separate delivery platform for every sport.
Buyers can inspect the current field-level contract in the API field dictionary and compare the delivery layer with a raw fixtures or statistics service in the sports picks API versus sports data API guide.
METHODOLOGY AND LIMITS
This is a reproducible specification audit.
PowerHouse reviewed the public product specification for all nine sport packages on 29 July 2026. For each package, the audit recorded the publishing unit, selection-group labels, target count for each group, and summed target total. Aggregate figures on this page are calculated directly from those documented values.
The benchmark does not use customer data, private API responses, betting results, retrospective win rates, revenue figures, or unsupported market-share estimates. It does not compare prediction accuracy across sports. It should be used to evaluate product structure, schema requirements, editorial workflow, and licensing questions.
Product targets can change as coverage and delivery requirements evolve. The publication and review dates provide a clear version boundary. The live sports coverage index remains the authoritative source for current package definitions, while the qualification methodology explains why a delivered set can contain fewer records than its target.
BUYER CHECKLIST
Six questions to ask before licensing a multi-sport feed.
- 01Does the provider define the publishing unit for every sport?
- 02Can team, player, fight, fighter, match, and tournament selections be distinguished without parsing labels?
- 03Is target output separated from guaranteed availability?
- 04Can a customer identify when each record was evaluated and whether it remains active?
- 05Are licence scope, attribution, territories, fields, and redistribution represented outside the pick label?
- 06Can the same record move through API, JSON, CSV, and portal workflows without changing meaning?
A useful evaluation should test these questions against one real customer workflow. Review the sports picks data licensing guide before procurement and use a focused enterprise pilot to validate record completeness, lifecycle behavior, and delivery fit.