Intuitively, football appears a numerical puzzle that can easily be solved – certain patterns, like the percentage of home wins and goals per game, repeat year after year – and the same teams always seem to end up in similar positions.

However, in reality, football numbers are not so easily tamed. Firstly, many outcomes are genuinely random (even if there appears to be an emerging pattern). Secondly, some important factors that seem to affect a football match are difficult to quantify, even if there is now an enormous quantity of data available.

But this complexity only makes football even more fascinating to analyse and model. Added to this, betting odds (and even fantasy football competitions) provide a real-time market to compare any forecast against. So analysing football need not just be about assessing the underlying merits of individual players and teams – it can also offer real insight into demand and supply factors and imperfections fuelling a thriving and constantly changing market.

At this site I aim to provide football insight, forecasts and comments on the market. I only use publicly available data (I haven’t go access to anything else) and try not to get too geeky. I’m from a financial services and actuarial background (and this influences my analysis) but I’ve followed football for many years, whilst trying to understand why things happen and influence the markets. I support Ipswich Town.

Please use the contact form if you have any feedback or ideas. Thanks for reading.

Steve Jackson

Explanation for Adjusted Goals rating system I use for forecasting projections

Rationale for Adjusted Goals as a rating system

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