How AI changes the football industry

How AI is changing football match analysis?

A quick analysis by me on the current and future reality of the football data industry.

The future winning formula is: AI + human QA (football intelligence, tactical and contextual understanding) = fewer, but more qualified people needed --> overall cost savings for companies.

Today, a single match takes approximately 8 hours for a human tagger to process, analyzing both teams with a range of 2 000 - 3 000 events.

But with AI + human QA, that drops to ~3 hours.

Here’s what’s actually happening:

• 70-85% of events are objective

(passes, shots, crosses, recoveries) → AI can handle these with high accuracy, while also reducing human errors (wrong player tagging, incorrect team formation selection, wrong clicks on the buttons/actions selection)

• 15-30% are subjective

(smart passes, pressure, subjective intention) → still require human expertise

 New workflow:

• AI processing: 30-60 minutes (based on current AI capabilities, which are expected to improve significantly)

• QA specialist review: 2-3 hours

• Total: ~2.5-4 hours per match

 What changes:

• Fewer entry-level tagging roles

• Less manual work

 What increases:

• Demand for QA specialists

• Experts with tactical understanding

• AI + football intelligence profiles

• Data validation roles

Bottom line:

Before:

100 taggers → 100 matches in 8 hours

(1 human tagger = 1 analyzed game / 2 teams)

After AI:

~35 QA specialists → 100 matches in 8 hours

(1 QA specialist = ~3 analyzed games / 6 teams)

Almost 3x fewer people needed, but more qualified.

Key takeaway: AI won’t replace football analysts. The industry is shifting from quantity of taggers to quality of specialists.