Data ingestion
Give each observation a reliable origin.
ENGINEERED
FOR UNDERSTANDING.
Intelligence is a chain of careful decisions. About data, about models, and about the way a result reaches the person using it.
Explore the architectureFrom source.
To significance.
A high-level view of the discipline behind a sports intelligence platform. Each layer has a distinct purpose.
Feature engineering
Translate observations into useful context.
Machine learning
Investigate relationships across that context.
Model evaluation
Test against evidence the model has not seen.
Intelligence systems
Bring complementary perspectives together.
Probability generation
Express uncertainty, not false certainty.
Live scoring
Design for timely, traceable updates.
Delivery
Make the result clear and usable.
The principles underneathQuestions first.
Questions first.
Models second.
Data with context
An observation becomes useful when its source, timing and sporting context are understood. Data quality is part of the intelligence problem.
Evaluation with discipline
A convincing result needs more than a good fit. Useful evaluation separates development evidence from the evidence used to judge an approach.
Engineering with purpose
Traceability, predictable delivery and clear interfaces matter as much as a model. An output should be understandable from source to presentation.
Each sport, on its own terms
The engineering principles can be shared. The questions, signals and language of each sport need their own attention.