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Blog · Alternatives and comparisons · Sports

How to choose analytics software for sports: questions, data and traps

How sports organisations should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

By CoviragePublished 24 September 20264 min read
The short answerStart from the questions sports organisations ask every month, not from features. List the exports you already hold, ask every vendor what it needs before the first answer and whether its AI calculates figures, and check that every total reconciles. Then compare the first-year cost, all in.

Most buying decisions for analytics start from a feature list. For sports organisations the better start is the questions that come back every month, the files already on hand, and the traps that make a tool look right in a demonstration and wrong in the first board meeting.

Start from the questions

The question The measure behind it
What have we delivered against each partner's contract? Delivery ratio per partner
Is the renewal ask in line with what was delivered? Renewal value against delivered value
How much inventory goes unsold, fixture by fixture? Inventory utilisation per fixture
Which partners use their hospitality? Hospitality yield per partner
Which renewals are close, and when did they sign last time? Renewal timing
When did we last speak to each partner? Partner contact recency

Any tool you consider should answer these from your data, not from a sample. Ask to see it.

The data you already hold

  • Contracts
  • Delivery log
  • Rate card
  • Inventory register
  • Hospitality and ticketing systems
  • Activation records
  • Ledger
  • Ticketing

If a vendor needs a warehouse built before it can read these, count that in the cost and the time.

Ten questions to ask any vendor

  1. What does it need in place before the first answer? A warehouse, a data model, a modelling language, a partner? Ask for the list and the typical weeks.
  2. Who does the setup, and who maintains it? Your team, the vendor, or a partner, and what that costs after year one.
  3. Does the AI calculate figures, or choose from computed ones? A language model that writes queries or code can produce a plausible wrong number. Ask what it is allowed to do.
  4. Does every total reconcile to a control figure? Ask to see a bridge that does not sum and what the product does about it.
  5. Can every figure be opened to its rows? An answer nobody can check becomes a debate in the meeting.
  6. What does it cost in the first year, all in? Licences, consumption, implementation, modelling and training, not only the seat price.
  7. How does data arrive, and who holds credentials? A file your systems already export, a scheduled drop, or a live connection with the vendor holding keys.
  8. What happens to the data, and where is it stored? Residency, retention, deletion, and whether names can be replaced with identifiers.
  9. Can we see it on our own data before we sign? A demonstration on a sample dataset tells you little about your own.
  10. What does the tool do when it cannot answer? It should say so. A confident guess does more harm than no answer.

Checks specific to sports

Ask whether the tool enforces these, and what it does when they fail:

  • Delivery: Rights contracted = delivered + scheduled + at risk + undeliverable
  • Inventory: Available = sold + unsold + withheld, per fixture
  • Hospitality: Seats held = used + unused, per partner per fixture
  • Renewals: Partners due = renewed + lost + in negotiation

The traps

Delivery ratio. Contracts are detailed and the delivery log, if any, is a spreadsheet nobody reconciles to them.

Hospitality used against held. Attendance data exists in ticketing and is rarely read by partner.

Renewal timing. Renewal is reported as signed or not. How late it was signed is forgotten.

Measures to leave out

Number of partners. Value, delivery and renewal by partner.

Impressions and reach, alone. Partners ask what was delivered against the contract.

Hospitality sold. Used against held is the renewal signal.

A scorecard

Criterion Weight Tool A Tool B Covirage
Answers our six questions on our own data High
Time to the first answer High
Needs a warehouse or data team Medium
AI calculates figures, or only explains computed ones High
Every total reconciles; figures open to rows High
First-year cost, all in Medium

Where Covirage fits

Covirage reads the exports above, answers the questions with figures our tools compute and check, and is set up for you within a week. See analytics software for sports compared, AI analytics for sports and Covirage for Sports.

For the measures in full, with formulas and exports, read Commercial KPIs for sports clubs and rights holders.

Questions people ask

What should sports organisations look for in analytics software?

The answer to their own questions, from the data they already hold, with every figure reconciled. Features matter less than what the tool needs before the first answer and who maintains it.

Is a BI suite enough for sports organisations?

It can be, with a warehouse and someone to build and maintain the model. Without them, the dashboard shows what changed and the explanation is still an analyst's job.

What data do sports organisations already hold?

Usually: contracts, delivery log, rate card, inventory register, hospitality and ticketing systems, activation records. Most analytics questions in this industry can be answered from those exports.

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