## Monday, 7 January 2019

### Are Teams More Vulnerable After Scoring?

One of the joys from the "pencil and paper" age of football analytics was spending days collecting data to disprove a well known bedrock fact from football's rich traditional history.

2-0 = dangerous lead has been a "laugh out loud" moment for those who went on more than gut instinct for decades.

Nowadays, you can crunch a million passes to build a "risk/reward" model and the only limitation is whether or not your laptop catches fire.

Myth busting (or not) perceived wisdom is now a less time consuming, but still enjoyable pastime.

Teams being more vulnerable immediately following a goal turned up on Twitter this week, although I've lost the link, so does it hold water?

Here's what I did.

Whether a team scores in the next 60 seconds depends on a couple of major parameters.

Firstly, a side's goal expectation.

Again not to be confused with expected goals, goal expectation is a term from the pre internet age of football analytics which is the average number of goals a side is expected to score based on venue, their scoring prowess and the defensive abilities of their opponent on the day.

Secondly, how long has elapsed.

Scoring tends to increase as the game progresses.

45% of goals on average arrive in the first half and 55% in the second. So if you want to predict how likely a side is to score based on their initial goal expectation, it will be smaller if you're looking at the 60 seconds between the 12th and 13 minute, compared to between the 78th and 79th.

Therefore, you take the pre game goal expectation for each team and when one team scores you work out the goal expectation per minute from this general decay rate for the other team over the next ten minutes.

Then you work out the likelihood that the "scored on" team scores in each 60 second segment via Poisson etc.

And then you compare that to reality.

The model doesn't "know" one team has just conceded, so if their opponents are really more likely to concede following their goal, the model's prediction will significantly under estimate the expected number of goals compared to reality.

There's a few wrinkles to iron out.

The first minute after conceding is going to be taken up with one team doing a fair bit of badge kissing and knee sliding, so it won't last for 60 seconds.

It's also going to be difficult to reply in the sixth minute after conceding if you opponent scores in the 94th minute and the ref has already blown for fulltime.

There's also the question of halftime crossover, where the 6th minute might actually be 21 minutes after the goal is conceded.

You can deal with these fairly easily.

I took time stamped Premier League date, ran the methodology and found 91 occasions where a side scored within ten minutes of conceding.

(I also split the ten minutes into 60 second segments, but I want to keep this short & more general).

From the model, in that timeframe, you would have expected those teams to score , wait for it.......91 goals, based on when the goal was conceded, how good their attacking potential matched up to the opponent's defensive abilities and allowing for truncated opportunity at the end of the game & through celebration.

There's no need to invoke scoring team complacency or a conceding teams wrath to end up with the scoring feats achieved, at least in the sample of Premier League games I used.

Are Teams Vulnerable After Scoring?

Probably not.