SUCCESS STORY
Sport Event Machine Learning Analytics Prediction (SEMLAP) Software
Computers increasingly play a central role in sports. Applying machine learning (ML) to all the data generated means you have new ways to understand the outcomes of sporting events.
THE PROBLEM
Develop Event Prediction Software Utilising Distributed Computing
This project was to design and development event prediction software which utilises the latest advances in distributed computing.
While the field is developing quickly, ML techniques are a natural fit for sporting events because they have:
- Multiple variables interacting dynamically (many inputs)
- Concrete success metrics (single output)
- Explicit rules (systematic functions)
- Repetition (repeated experiments).
Other events with these traits happen all around us all time too: scientific research, financial investments, insurance assessments and political elections, among many others. Apply proven machine learning techniques and they can all be understood and predicted at an unprecedented level.
With our in-house ML expertise, Hunted Hive developed a platform codenamed SEMLAP (Sport Event Machine Learning Analytics Prediction) to give you those predictions.
Critical patterns in the inputs and results of these events are there to be found, but they are subtle and concealed in vast datasets. Only advanced machine learning analysis can detect them among the statistical noise.
SEMLAP can find these “unknown factors” to give you a secret edge. Do the traditional odds match the actual probability of an event occurring? If not, you may know something everyone else doesn’t. It’s a game changer.
"A event prediction software like no other.”
Roger Chappel, Data Scientist
How We Delivered Value
- Build your solution on a unique framework, meaning no other prediction system will operate the same way and give someone else the same edge
- Develop a system that searches for and backtests strategies within event rules
- Match your business logic to the mathematically optimal decision strategies
- Rebrand and customise SEMLAP for any suitable application
- Launch your solution behind an ultra-secure VPN
- Develop you an easy-to-use web interface to control your SEMLAP solution.
Our Role
- Conducted bespoke development to predicting events through input:output optimisation strategies
- Tracked the latest ML and statistical research
- Mastered the deep theoretical mathematics that underpins machine learning
- Developed algorithms using proven approaches like support vector machines (SVM) and clustered linear regression (CLR)
- Developed a unique backtesting framework
- Developed processes for configuration management to maintain servers and network
- Built a reliable maintenance and support team.