The Expected Goals Philosophy: A Game-Changing Way of Analysing Football

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Has the surge in popularity coincided with Match of the Day and Sky Sports using xG, or do you think there’s something else driving the interest? We can use these analytics more effectively over the course of the season though, and you can use the xG metric to help determine how a team or player has performed when compared with their expected values. In his own words, an appreciation of xG requires only “an open mind and the mathematic understanding of a fourteen-year-old”. The formulae used to calculate expected goals and other related stats are explained in a straightforward manner by Tippett and are accompanied by easy to follow examples and graphics. Imagine you are in a maze and you have four different paths to go: north, east, south, west and two people. Person A without a map and person B with a bad map, even though he thinks, incorrectly, that he has a good map. If that is all we know, most people would give person A a chance of 25% of choosing the right path. But as it is highly likely that person B will choose the path that his map incorrectly highlights as the correct path. So the chance of person B actually choosing the right path is probably below 1%. Such is the danger of incorrect maps! The solution

In fact, the media are more interested in being interesting than being right. But if you look at a betting operator, for instance, whose whole existence depends on being right (i.e. accurately forecasting the outcome of matches), they are always going to use xG to power their models. The xG scoreline for this game was 1.1 – 2.54 in favour of the Gunners, so whilst Arsenal probably should have won the game, Burnley appear to have fully deserved their goal based on performance.Whilst the location of a shot forms the main basis of its danger level, other factors also play their part. Shots which come from crosses are considerably harder to convert than shots which take place when the ball is standing still. Whether the shot is headed, volleyed or hit from the ground also affects its chance of success. So too does it matter whether the effort is taken on a player’s weaker foot. Analysts account for a whole range of such factors in their Expected Goals models. Only when we fully embrace the Expected Goals method can pundits begin to more accurately comment of football. Only then can managers give more reasonable post-match interviews. Only then can the fans select the best players for their fantasy teams. Only then can we haul football out of the dark ages and into a more intelligent era of analysis. The noticeable absence of a smart, analytical and scientific voice in the mainstream football media reflects onto he fans who follow such broadcasting. Stupidity breeds stupidity.” The longest section of the book explores expected goals’ role in betting to date. Tippett describes how Smartodds produced their own expected goals model to identify value in betting markets and place money on teams that the model recognised as having a better chance of winning than the bookmakers’ odds suggested. With 10.79xG created, Brentford have been the most proficient team in the league so far this season at creating goalscoring opportunities," said James Tippett, the founder of the xG Philosophy account and author of the book The Expected Goals Philosophy.

This statistical approach is especially useful for properly rating teams and players. From a club’s perspective, holding more reliable information about players can help it maintain a competitive advantage by identifying proverbial diamonds in the rough when scouting players. Part of the book is devoted to xG’s role in soccer scouting and the example of Brentford, owned by Smartodds founder Matthew Benham. Benham decided to use expected goals data to lead Brentford’s transfer strategy following their promotion to the Championship in 2014. Rather than try to be inclusive and understanding of the limitations of the xG model in the mainstream, the writer (James Tippett) is completely exclusive, and devalues the opinion of a large portion of football fans.At half-time of England’s game with Poland on Wednesday, however, we were treated to one rare example of xG landing perfectly, and it was oddly satisfying (though it would have been better if Poland had been in front). An interesting concept mentioned in the book which may be new to soccer bettors is the Justice Table. The Justice Table ranks teams in a division according to the Expected Points (xP) they have accumulated over the course of the season. Tippett draws a connection between xG and Moneyball via their facility to refine gauging a player’s ability to one number. Update 21-11-2022: I found out that there is no correlation between goals and xG. This is of course not a criticism as xG and goals aren’t meant to correlate as xG is an alternative way of trying to explain the match other than the actual goals. Nevertheless, it is note worthy that this means that xG has zero explanatory power in explaining goals. To be clear: a high correlation between xG and goals would actually be bad for xG as xG is an alternative measure to explain the match than goals. If the correlation were to be high, it wouldn’t be an alternative.] A bad map is better than no map at all

This can for example be seen in the Premier League at the difference between xPoints based on xG and xPoints based on PSxG. xPoints are expected points scored in the league based on either xG or PSxG.It only takes a handful of good chances to be missed (0.50xG or thereabouts) for your team to be underperforming by a couple of goals," adds Tippett. As you might expect, it doesn’t always work out that way. One of the brilliant things about a low-scoring game like football is that fluke results can happen and, sometimes, wins can be snatched against the run of play, something that expected goals doesn’t account for. Put yourself in Bryan Mbeumo's shoes in the 46th minute of last weekend's Premier League clash against Bournemouth. The ball has been squared onto your good foot and the far corner is gaping, you know exactly what to do. A crisp side-foot finish into an inviting net and you'll be off basking in the adulation. This is your moment.

As soon as I started reading up about xG, I knew it could become hugely popular. It’s such a powerful metric for predicting future performance and it’s really intuitive once you begin to understand it. I can't even figure out who could be a good audience for this book. An average fan, trying to dip his toe into advanced statistics? The book litters him with way too much numbers while teaching precious little. Someone, who is more interested in the depth of football and/or advanced statistics? The deepness of the actual coverage of xG here is extremely shallow, offers almost no insights on modeling, mathematical or any other level. I can't picture anyone who would like more than a third of this book. As you can see now that we are excluding the worst performing players in regards to scoring, the correlation drops from 68% to 63%. This trend continues the more low performing players we eliminate: The new approach relied on using the data to find undervalued players in the market. It was a massive success and helped Brentford achieve five successive top half finishes despite having one of the division’s smallest wage budgets and fanbases. However, I would've liked a more detailed description of how xG is actually calculated rather than just the categories used (e.g., location of the shot, strong vs. weak foot, cross vs. entry pass, air vs. ground, etc.). Plus, there are a bunch of grammatical errors, and that drives me nuts.To remind you: Ashes has looked at the top 5 leagues and the Russian league. Personally, I am more interested in the smaller leagues, especially the Eredivisie. And I am more interested in whether it helps to use xG in concrete player recruitment, especially in finding exceptional players. At my work at FBM we have found the striker Dalmau for Heracles. Not only did Dalmau become the #3 top scorer that season, we also predicted that he would be worth 1.75 million in transfer fee for Heracles the next year and Heracles did receive 1.7 million for Dalmau (700K transfer fee and Dessers, a striker valued at 1 million). Really interesting and accessible introduction to expected goals. I managed to get through the book in a 24 hour period. I was thoroughly gripped and learnt a lot. I found the comparisons between Moneyball and Brentford revealing and insightful, particularly how Brentford have utilised xG to exploit the transfer market. Tippett explores the differences between results and performance in an engaging and easily understandable way. The graphics, data and presentation of maths was easy to follow. The parts about gambling and how to make money were the least interesting as that isn't why I watch football. It seems like only the rich syndicates will ever make.money from that.