About

Sports trader with an interest in data science & programming, using online courses and self learning to improve my skills. The site will share posts & projects mainly revolving around football. Analysis & visualisation will be done using software including; Python, RStudio, MongoDB & D3.

Personal Betting

• Majority of betting done on early asian handicap football markets & long term football markets.
• Ratings for major European leagues using both XG & non-XG models, both for short term bets above and long term bets.
• Use of API’s for notifications & pricing.
• Player specific databases used for further bets.
• Python & selenium used for web scraping, MongoDB used as the database, private Github repos for version control.
• Shiny apps & Rstudio scripts used for calculations.

Football Trader

Spreadex

September 2015 - Present

• Web scraping to maintain databases relevant for pricing (using Rvest & tidyverse).
• Shiny app development to simplify pricing process (using shiny & ggplot).
• Various short term ratings for top all leagues (using caret & Rstan).
• Long term pricing for leagues and tournaments.
• Modelling and pricing of niche markets.

Education

Post Graduate Diploma - Statistics & Applied Probability - Distinction (73%)

University Of Nottingham - 2014-15

• Time Series & Forecasting 84% (Analysis of time sequential data, model identification, parameter estimation, forecasting, assessment & implementation using R)
• Fundamentals of Statistics 73% (Introduction to basics of Probability, Statistics and Linear models, Statistical Inference)
• Computational Statistics 71% (Simulation, MCMC, Density Estimation)
• Advanced Stochastic Processes 70% (Martingales, Brownian Motion & Renewal Processes)
• Stochastic Models 65% (Poisson Process, Queueing & Reliability)

Bachelor of Science (BS) - Mathematics - 1st Class Honours (74%)

University Of Nottingham - 2011-14

Third Year Average 74%

Optimization, Differential Equations, Medicine & Biology, Game Theory, Scientific Computation, Coding & Cryptography, Fluid Dynamics.

Second Year Average 74%

Mathematical Analysis, Vector Calculus, Fourier Analysis, Complex Functions, Number Theory, Numerical Methods, Physics, Modelling.

First Year Average 77%

Analytical, Applied, Calculus, Foundations of Pure Maths, Linear, Structures, Probability, Statistics.

Data Analyst Nanodegree

Udacity 2015-17

Completed online course which included the following projects;

1. Testing a perceptual phenomenon - Compute descriptive statistics and perform statistical tests.
2. Investigate a dataset - Choose a dataset, perform an investigation and share findings.
3. Data wrangling - Audit, clean and import data into a database (MongoDB), then run queries on database.
4. Explore & summarize data - Scrape a dataset and perform a complete exploratory data analysis using R.
5. Identify fraud - Use machine learning (Python) to identify persons of interest in the Enron dataset. 6 . Data visualisation - Use D3 to build an effective visualisation.
6. A/B testing - Make design decisions for an A/B test and analyse results of a test.

MongoDB University

Present

Completing various online courses to improve Mongo competence.