2018/19 Premier League Projection

Here’s my 2018/19 Premier League projection

I use a simple shot based model to assess teams, it’s explained here – but to summarise, it works out each team’s attacking and defensive strength by applying factors to goals, shots and shots on target, to produce a rating I call “adjusted goals”.

Adjusted goals for and against = 45.0%*Goals+2.8%*Shots+8.4%*Shots-on-target.

How is the 2018/19 projection calculated?

  1. Last season’s ratings

My starting point (and most important component) for estimating the relative team strength for this season is last year’s Adjusted Goals rating. This gives the following (after making adjustments for the promoted teams to take account of the higher standard of opposition).


2. Player turnover

With an ever increasing amounts spent on new players during this year’s Premier League close season – incoming and outgoing players will surely have a significant effect on relative team strength. And this season I have the advantage of an early transfer window closure.

To assess the effect of player turnover, I adapt my Adjusted Goals rating to individual player level by trying to determine each player’s contribution to their team’s rating – taking account of attacking and defensive actions such as goals, assists, passes, tackles and blocks. Converting my team ratings to a player rating does have flaws, but it gives a reasonable indication of the effectiveness of new players.

[Note – this excludes any transfers prior to 8 August]

3. European Competition

I’ve made adjustments for those involved in European Competition that weren’t last season (and vice versa). The logic being that European fixtures will be detrimental to Premier League performance. Burnley are the big loser here.

4. World Cup involvement

I’ve taken account of the number of players involved in the World Cup for each team, weighted by how far each player progressed (just a small adjustment, to account for fatigue, and availability earlier in the season).

However – I haven’t allowed for managerial changes. For example Pellegrini and Sarri may have a significant impact on their new teams, but any adjustment would be too subjective (so I haven’t made any)


full projection


What’s going on here?

OK – some of these projections look a bit strange. It’s certainly not how I’d order the table based on my own perception of each team’s strength. Whilst the top six aren’t far from my expectations, are Newcastle really the 7th best team? Newcastle’s lofty projection is driven by their shot data from last season, where they performed well (particularly defensively).

Conversely, West Ham in the bottom 3??? Again this is based on their shots record last season – which was grim (both for and against).

And Burnley second last? I’m not particularly comfortable with this one, as Sean Dyche’s team consistently outperform my model. But their poor shot performance, together with a European adjustment put them in serious relegation trouble (according to the model).

Where’s the betting value?

There are many factors my model doesn’t properly allow for – e.g. it ignores managerial changes, and makes fairly blunt adjustments for other factors. But, I still use it to identify potential value in the market. Here I’ve compared the projected probabilities against the best odds in the market (from oddschecker.com).

What’s evident (as I expected) is that there is potential value. I’ve actually identified some value in Man City for the title, despite a best price of 1.7. My model loves City from last season – posting spectacular shot numbers – and has them well ahead of the opposition, even an improved Liverpool.

Other potential value – Chelsea top 4. Burnley, Southampton and West Ham to be relegated. Newcastle, Bournemouth, Fulham, Watford, Cardiff, Brighton top half. Everton bottom half.


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