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Wednesday 22 November 2017

An xG Timeline for Sevilla 3 Liverpool 3.

Expected goals is the most visible public manifestation of a data driven approach to analyzing a variety of footballing scenarios.

As with any metric (or subjective assessment, so beloved of Soccer Saturday) it is certainly flawed, but useful. It can be applied at a player or team level and can be used as the building block to both explain past performance or track and predict future levels of attainment.

Expected goals is at its most helpful when aggregated over a longer period of time to identify the quality of a side's process and may more accurately predict the course of future outcomes. rather than relying on the more statistically noisy conclusion that arise from simply taking scorelines at face value.

However, it is understandable that xG is also frequently used to give a more nuanced view of a single game, despite the intrusion of heaps of randomness and the frequent tactical revisions that occur because of the state of the game.

Simple addition of the xG values for each goal attempt readily provides a process driven comparison against a final score, but this too has obvious, if easily mitigated flaws.

Two high quality chances, within seconds of each other can hardly be seen as independent events, although a simple summation of xG values will fail to make the distinction.

There were two prime examples from Liverpool's entertaining 3-3 draw in Sevilla, last night.


Both Firmino goals followed on within seconds of another relatively high quality chance, the first falling to Wijnaldum, the second to Mane.

Liverpool may have been overwhelming their hosts in the first half hour, they were alert enough to have Firmino on hand to pick up the pieces from two high quality failed chances, but a simple summation of these highly related chances must overstate Liverpool's dominance to a degree.

The easy way around this problem is to simulated highly dependent scoring events as such, to prevent two goals occurring from two chances separated by one or two seconds.

It's also become commonplace to expand on the information provided by the cumulative xG "scoreline" by simulating all attempts in a game, with due allowance for connected events, to quote how frequently each team wins an iteration of this shooting contest and how often the game ends stalemated.



Here's the xG shot map and cumulative totals from last night's match from the InfoGolApp.

There's a lot of useful information in the graphic. Liverpool outscored Sevilla in xG, they had over half a dozen high quality chances, some connected, compared to a single penalty and other, lower quality efforts for the hosts.

Once each attempt is simulated and the possible outcomes summed, Liverpool win just under 60% of these shooting contests, Sevilla 18%, with the remainder drawn.

Simulation is an alternative way of presenting xG outputs rather than as totals that accounts for connected events, the variance inherent in lots of lower quality attempts compared to fewer, better chances and also  describes most likely match outcomes in a probabilistic way that some may be more comfortable with.

Liverpool "winning" 2.95-1.82 xG may be a more intuitive piece of information for some (although as we've seen it may be flawed by failing to adequately describe distributions and multiple, common events), compared to Liverpool "winning" nearly 6 out of ten such contests.

None of this is ground breaking, I've been blogging about this type of application for xG figures for years, But there's no real reason why we need to wait until the final whistle to run such simulations of the attempts created in a game.

xG timelines have been used to show the accumulation of xG by each team as the game progresses, but suffer particularly from a failure to highlight connected chances.

In a simulation based alternative, I've run 10,000 attempt simulations of all attempts that had been taken up to a particular stage in last night's game.

I've then plotted the likelihood that either Liverpool or Sevilla would be leading or the game would be level up based on the outcome of those attempt simulations.


Liverpool's first dual attempt event came in the first minute. Wijnaldum's misplaced near post header, immediately followed by Firmino's far post shot.

Simulated as a single event, there's around a 45% chance Liverpool lead, 55% chance the game is still level and (not having had an attempt yet) a 0% chance Sevilla are ahead.

If you re-run the now four attempt simulation following Nolito's & Ben Yedder's efforts after 19 minutes, a draw is marginally the most likely current state of the game, followed by a lead for either team.

A flurry of high quality chances then make the Reds a near 90% to reach half time with a lead, enabling the halftime question as to whether Liverpool are deservedly leading to be answered with a near emphatic, yes.

Sevilla's spirited, if generally low quality second half comeback does eat into Liverpool's likelihood of leading throughout the second half, but it was still a match that the visitors should have returned from with an average of around two UCL points.






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