UPDATE: Caley informs me now that his ExpG model underwent some significant edits after the season’s opening weeks and so some of these maps below have since been revised.

Thanks to the generous Michael Caley I am going to be starting a new stats project here at Inside Channel. One of the biggest problems with the conversation about advanced stats right now is that a lot of the data is only beginning to become more accessible to people.

Paul Riley’s data is a huge improvement for fans and Michael Caley’s extensive posting at Cartilage Free Captain is also incredibly helpful. He has put together posts with extensive advanced stats data for England and for the other top three leagues in Europe. Here are some of his greatest hits if you’re curious to revisit them:

  1. His latest post on his full ExpG method
  2. A Defense of ExpG
  3. Shot Location and ExpG
  4. English Shot Type and Pass Type
  5. The Incredible Through Ball
  6. Shot Quality
  7. Player Shooting Skill
  8. Player Shooting Data
  9. Stats for Managers
  10. Atletico Madrid Facts
  11. Shot Distribution in European Football
  12. International Shot Type and Pass Type
  13. Advanced Stats and Tiki Taka
  14. Why Defense Stats Aren’t Very Good

That being said, a lot of the advanced stats writing that is going on is still being done by people who have access to data that ordinary fans simply do not have. It’s no surprise, then, that there’d be a certain amount of ignorance about these stats; the only place those stats live in the eyes of most fans are in a spreadsheet some random person built using data scraped from Opta. Thanks to the first three links shared above, that problem is starting to be fixed, but most of the data available in those places is either aggregate data or match-specific data that takes a little work to access.

For that reason, I’m going to start posting week-to-week ExpG data for the Premier League here at Inside Channel. For each post I will put the scoreline in plain text along with the embedded tweet from Caley that includes his ExpG maps. (I asked for and received Caley’s permission to do this, FYI.)

I will also include a link to the WhoScored page for each game so that curious readers can cross reference Caley’s maps with the charts in WhoScored to see who had the highest ExpG value chances in a game and how those chances were created. (That is the process I used to do some of my analysis in this post for CFC.) The goal of doing this is making it easier for individuals to play with advanced stats data for individuals.

So without further delay, here is the data for expected goals data for match day one in the Premier League. I will post these updates fairly regularly until I have caught up to the current place in the schedule so there should be a fair number of posts on here over the next week as I try to get caught up before the end of the international break.


Result: Manchester United 1-0 Tottenham Hotspur
ExpG Result: Manchester United 0.5-0.7 Tottenham Hotspur
WhoScored Link

Result: Stoke City 0-1 Liverpool ExpG Result: Stoke City 0.4-0.5 Liverpool WhoScored Link

Result: Arsenal 0-2 West Ham
ExpG Result: Arsenal 1.3-0.7 West Ham
WhoScored Link

Result: Newcastle 2-2 Southampton ExpG Result: Newcastle 1.7-1.3 Southampton WhoScored Link

Result: Chelsea 2-2 Swansea City
ExpG Result: Chelsea 0.7-1.7 Swansea City
WhoScored Link

Result: Everton 2-2 Watford ExpG Result: Everton 0.7-0.8 Watford WhoScored Link

Result: Bournemouth 0-1 Aston Villa
ExpG Result: Bournemouth 0.8-0.9 Aston Villa
WhoScored Link

Result: Leicester City 4-2 Sunderland ExpG Result: Leicester City 2.1-1.6 Sunderland WhoScored Link

Result: Norwich City 1-3 Crystal Palace
ExpG Result: Norwich City 1.1-2.0 Crystal Palace
WhoScored Link

Result: West Bromwich Albion 0-3 Manchester City ExpG Result: West Bromwich Albion 0.5-2 Manchester City WhoScored Link

Recap of Match Day One

Out of ten games, here is how Caley’s ExpG stat did at predicting results:

  • There were three screwball results—Man United’s win against Spurs thanks to poor finishing from Spurs and a Kyle Walker own goal, Arsenal’s home defeat against West Ham due to a couple Petr Cech howlers, and Swansea’s draw at Stamford Bridge due to some lucky breaks for the Blues and poor finishing from the Swans.
  • Beyond that, every result basically holds up—ExpG either gets the winner right or it gets the result close for a match that ends in a draw or with a one goal margin of victory.
  • The big things to note here are that Spurs and Chelsea have both basically lived up to what we saw in week one: Chelsea is way worse than expected; Spurs have been a pleasant surprise. The results for both teams were different than what ExpG predicted for one week, but over the first 12 matches the actual results have come much closer to the ExpG results.
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