Tuesday, 29 January 2019

Simulating Post Game Outcomes with a Non Shot xG Model.

First there was xG, ExpG, expected goals, chance quality or whatever you wished to call it.

Then we simulated the shooting contest to create a likelihood and range of possible scores.

Next we added the different scoreline probabilities to arrive at a post game chance of the shooting contest ending as a win or a draw.

Undeniably these approaches help to illuminate the story of a single game, but there are occasions when a shot based approach can mislead.

Game state, (the combination of time remaining, scoreline and the talent differential of the two teams), can sometimes lead to a side prioritising winning the game as opposed to maximising the number of goals they may score.

The obvious example of these game state effects might be a side leading by a single goal deep into stoppage time heading for the corner flag, rather than the opposition penalty area or the reverse where a trailing team attempts a speculative long range effort instead of choosing to progress the ball and perhaps losing it before they can shoot.

Therefore, a simple xG tally can sometimes become distorted by attempts that aren't taken and attempts that perhaps shouldn't have been.

Non shot xG models may provide a partial solution to this occasional disconnect between xG totals and an eye witness account of a game.

Instead of using goal attempts when assessing the performance of each team, possessions my the chosen currency in a non shot chance quality model.

Non shot xG models aren't too concerned with how a team choses to use their possession.

Instead it takes a weighted midline between the situations where scoring a goal is the main aim and when alternatively preserving a lead is paramount.

A side who isn't being overwhelmed by a trailing opponent can therefore still build up non shot xG credit by claiming a fair share of possessions in varying areas of the pitch......even if they don't chose to convert them into actual goal attempts that would register in a shot based xG framework.

In short, a side may go shot-less for the final half hour in a game they lead, but still be largely in control of managing the advantageous scoreline.

Earlier this season, Liverpool went to Huddersfield and won 1-0 with a Salah goal in the 24th minute.

Huddersfield "won" the shot based xG contest 0.9 to 0.6 and whether you want to simulate every chance (some of Liverpool's were related opportunities) or simply run the relative xG totals through a poisson, you'll find that shot based xG thinks that Huddersfield were more likely to win the actual game than Liverpool.

The 1X2 splits are around 40/35/25.

So this is one of those occasions when shot based xG thinks the wrong team won, although it is blind to the superior team holding an early lead.

However, a possession based, non shot model, which values every possession and doesn't need a goal attempt to trigger a plus for either teams sees things rather differently.

Liverpool's possessions were, on average around 15% more valuable than Huddersfield's.

I only vaguely remember watching the match, but I didn't get the impression that Liverpool were very lucky to win, nor that, if needed they wouldn't have turned their superior possession chains into more chances.

If we now simulate the likelihood of each side turning their possessions into goals (with no regard for tactical, game state related nuances), Liverpool now win a non shot simulation 44% of the time compared to just 26% for Huddersfield.

There is no right answer when looking at who deserved a win or a loss, and while shot based xG offers one probabilistic opinion, as they say others are available and sometimes they will disagree.

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