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Timothy Omolo — Founder of PredictLix
Founder · Mathematician · Data Scientist

Timothy
Omolo

Founder & CEO — PredictLix

Mathematician turned data scientist from Kenya. I built PredictLix to make AI-powered football analysis accessible to everyone — free, transparent, and backed by real statistical methodology.

Kisumu, Kenya [email protected] predictlix.com

About Me

I'm Timothy Omolo — a mathematician and data scientist from Kenya. I hold a BSc in Mathematics and Statistics from Maseno University (2005–2009). My academic foundation in probability theory, statistical inference, and quantitative analysis became the core of everything I build.

After years working with data in analytical roles, I channelled that expertise into football — the sport I love most. On 27 February 2026 I founded PredictLix, a free AI-powered football predictions platform that analyzes each match across 20+ statistical factors including recent form, head-to-head records, home/away performance, and live bookmaker odds.

My mission is simple: football predictions should be based on real data and transparent methodology — not guesswork. No subscriptions, no paywalls. Every prediction includes a Confidence Score so you always know the statistical strength behind each tip.

2026 PredictLix founded
42+ Leagues covered
20+ Statistical factors
100% Free access

Work Experience

Feb 27, 2026 — Present
Founder & CEO
PredictLix · Kisumu, Kenya · Full-time
Built an AI-powered football predictions platform from scratch.
  • Designed statistical and ML models powering match predictions across 20+ factors
  • Launched coverage of 42+ leagues: Premier League, La Liga, Bundesliga, FKF Premier League, NPFL and more
  • Developed free-access model with Confidence Score for full statistical transparency
  • Built go-to-market strategy targeting Kenya, Tanzania and Pakistan markets
AI / ML Football Analytics Statistical Modeling Product Strategy Data Science
Jan 2010 — Jan 2026
Independent Researcher & Mathematics Tutor
Self-employed · Remote · Kenya
Over 15 years of independent work at the intersection of mathematics, statistics, and football analytics.
  • Delivered remote mathematics tutoring across secondary and university level — covering probability, statistics, calculus and linear algebra
  • Conducted independent research into football match outcomes, studying statistical patterns across African and European leagues
  • Developed early predictive frameworks and personal models for match result forecasting — the foundation of what later became PredictLix
  • Built expertise in quantitative modeling, data collection methodologies, and betting market analysis
Mathematics Tutoring Football Research Statistical Modeling Self-employed

Education

Bachelor of Science
Mathematics and Statistics
September 2005 – November 2009 · Kisumu, Kenya
Probability Theory Statistical Analysis Linear Algebra Calculus Operations Research Numerical Methods

Core Skills

AI (Artificial Intelligence)
Neural networks, LLM integration, AI-driven automation for sports prediction systems
Consulting
Advisory on sports data products, analytics strategy and go-to-market for African markets
Data & Analytics
End-to-end data pipelines: collection, cleaning, analysis and reporting
Gambling
Betting markets structure, odds analysis, responsible gambling frameworks
Data Science
Pandas, NumPy, scikit-learn, statistical visualization
Football
Deep domain expertise in football: leagues, teams, match dynamics across Africa and Europe
Football Analytics
Form analysis, head-to-head, home/away metrics, bookmaker odds modeling
Football Predictions
Daily match predictions across 42+ leagues — 1X2, BTTS, Over/Under, Correct Score markets
Machine Learning (ML)
Feature engineering, model evaluation, automated prediction pipelines
Mathematics
BSc Mathematics & Statistics — linear algebra, calculus, numerical methods, operations research
Predictive Analytics
Confidence scoring, multi-market prediction: BTTS, Over/Under, Correct Score
Product Strategy
Building free-access sports data products from zero to launch
Sports Betting Analytics
Bookmaker odds modeling, value bet detection, market movement analysis
Sports Statistical Modeling
Poisson distributions, Dixon-Coles, Elo ratings applied to football outcomes
Statistical Modeling
Regression, Poisson models, Bayesian inference for match outcome prediction

Certifications & Awards

Machine Learning Specialization
DeepLearning.AI & Stanford University · Coursera
September 2022
Sports Performance Analytics Specialization
University of Michigan · Coursera
April 2023
Professional Data Analyst Certification
DataCamp
October 2023
Mathematics for Machine Learning and Data Science
DeepLearning.AI · Coursera
March 2024
Introduction to Football Analytics
Stats Perform
November 2024
Microsoft Certified: Azure AI Fundamentals (AI-900)
Microsoft
June 2025

Let's Connect

Find me on these platforms or reach out via email.