Tuesday 29 October 2019

Liverpool by One.

Old style goals based analysis hardly gets a run out nowadays with everyone arguing xG strawmen. So, let’s go the goals route to see if Liverpool’s record in single goal margin wins is “knowing how to win”, “unsustainable” or “about what you’d expect”.

Liverpool won 10 games by a single goal margin last season. That’s a lot, but well below the single season record held by Manchester United of 16 in 2012/13 and 2008/09.

United’s number of single goal wins in those subsequent seasons fell to five and eight respectively (although something more impactful may have also occurred in 2013/14). Their points tally fell as well, by 25 points in 2013/14 and by 5 in 2009/10.

To dilute the Fergie/Moyes effect, let’s look at the average record in the next season of teams who won 10 or more games by a single margin.

There’s over 90 of them during the 20 team history of the Premier League and 80% of those had fewer wins by the narrowest possible of margins during their next Premier League season, 74% also saw their points total fall.

These teams who edged lots of close matches one season shed around 10% of their points in the next season.

Initially, it’s not looking too rosy for Liverpool’s ability to sustain these narrow wins.

However, there’s another factor to consider.

Single goal wins, on average account for 41% of a side’s Premier League points total, but in our sample of 90+ teams who won 10 or more, 80% of them accrued more than 41% of their points from such victories.

Everton won 76% of their 59 points in 2002/03 from single goal wins and then tried their very best to get relegated in 2003/04 as their “luck” in narrow games returned to earth and they won just 39 points.

In Liverpool’s case in 2018/19, one goal margin wins only accounted for 31% of their 97 points. Therefore, their ten such wins places them in a group of sides who typically regress, but the percentage of total points they win in this manner is entirely atypical of that group.

To see where Liverpool stand as being adept at winning single goal margin games, we need to look at their underlying goals record.

In 2018/19 they scored 89 and conceded 22, taking the Poisson route, that’s consistent with winning nine games by a single goal over 38 games. They won, as we’ve seen ten, hardly a worryingly large over-performance.

You can lump Liverpool in with a group of teams who have achieved good things, partly as a result of “knowing how to win” (Leicester 2015/16 spring to mind, 14 single goal wins where nine would have been a more equitable return), but unlike most of these sides, the Reds have the underlying numbers to deserve their record.

Expect a few more 2-1’s between now and May.

Monday 21 October 2019

Closing the Door.

One of the most fun aspects of football data analysis is when the team you're part of derives some exciting newly derived metrics from the raw data that allows you to look at old problems with a new light.

Some real heavy data lifting has been put into deriving our Non Shot expected goals model. So first a quick recap on what it does.

Whenever the ball is moved around the pitch there is a likelihood of scoring  from each location it finds itself in. We express this value as non shot xG and the difference between these values when an action is completed is the change in NSxG via that action.

There's also a "risk/reward" aspect for when you concede possession.

Finally, each team has (nearly always) a different NSxG for the same pitch location, because one major input is the distance to your opponents goal.

We've mainly looked at passing and ball carrying, so far, quantifying the differing importance to your side of moving the ball five yards out of your own penalty area or five yards into your opponents. But there's an obvious extension of this that flips the focus and examines how well a team prevents an opponent progression the ball.

This isn't just by making passing difficult, it's also by making it harder or easier for opponents to carry the ball forward as well.

It used to be call closing a player down, it's called any manner of terms nowadays.

Here's how sides are fairing in preventing ball progression in 2019/20.

The first thing you need is a benchmark figure to measure how well a side is closing down the opposition.

There's only been nine matches played by each Premier League team to date and they may have played a bunch of sides who aren't that good or willing to play out from the back, so we need to find a set of figures that reflect this possible imbalance of intent and talent.

Let's take Manchester United. They've played nine teams, Chelsea, CP, Leicester, Newcastle, Southampton, WHU, Arsenal, Wolves & Liverpool.

Those teams, in turn have also played nine teams (except Arsenal, who play tonight), that's 80 teams of which nine are Manchester United.

That's almost guaranteed to include every Premier League team at least once and makes up a decent sample of around 70-80 games depending upon how you slice it.

We therefore, we took those 71 non Manchester United matches played by Manchester United's opponents and looked at the "risk/reward" ball progression via both passes and ball carries for 100 pitch segments.

For each segment we calculated the average NS xG gained (or lost) per 100 pass & carry attempts. That was our baseline for United's opponents progression against a broad selection of opponents this season.

Then we repeated the exercise, but for these sides in their matches against Manchester United and ran a heat map to see where on the field these teams were finding it difficult to progress the ball against United and where they were having a easier time compared to their benchmark numbers against the rest of their opponents.

This is what it looks like ( ignore the numbers for now).

The red areas are where United's opponents are progressing the ball at lower levels against United than they've managed as a group against a basket of 71 other Premier League sides. Blue, they're doing better.

It's a pretty stark and clear picture of where on the field United have been making it difficult for their opponents to get the ball into more dangerous areas. Firstly, beginning in front of their opponent's own box and then aggressively in front of United's own. They aren't too fussed about targeting wide positions on halfway and not too good(?) at stopping runs or passes from the bye-line & in the box.

Here's Everton and they do harry the opposition, but it's a much more chaotic process, with very little structure, especially compared to United's disciplined approach.

And finally, here's Aston Villa.

There's no overt closing down of the opposition until they reach the box, at which point it seems to become all hands to the pump.

Wednesday 2 October 2019

Passing Risk Reward in the Premier League

The availability of richer data sources has naturally led to an interest in passing and ball progression.

The generally quoted passing metrics still gravitate towards event data such as goal attempts and actual scores as the major framework.

Passes that lead to a potential goal scoring attempt predominate in most current passing metrics and little has been done to differentiate between the contribution made by individual players involved in these possession chains.

In contrast, we've broken down the value of each pass attempted by referencing how likely a possession anywhere on the pitch has historically led to a goal, whether or not the possession ultimately result in an attempt on goal.

This so called non shot xG metric not only allows a route to value every ball progression, be it a pass or a carry, but also quantifies individual involvement, rather than sharing the credit equally between all those participating in the possession.

However, as often is the case in football metrics, only one side of the ball has been investigated.

Each pass attempt comes with a risk and reward.

The player attempting the pass has custody of a valuable team resource, namely the non shot xG value for possession of the ball at that precise position on the field.

The potential reward in making a progressive pass is to advance the ball to a more dangerous area of the field.

And the ever present risk is the cost of a turnover. The passing team lose the NS xG value they had by owning the ball and the opponents gain their own NS xG by taking possession of the ball.

Weighing a player's NS xG leger is problematical, but one way to express the risk reward balance of a players passing performance is to add up the NS xG value of every progressive pass they complete and compare this to the sum of the NS xG he loses through incomplete passes, along with the NS xG gained by the opponent taking possession of his errant attempts.

For example, in the nascent Premier League, Matteo Guendouzi's completed open play progressive passes have been received at areas on the field that totals 6.69 NS xG.

On the minus side, his picked off pass attempts has "lost" Arsenal 1.67 N xG. This is made up of loss of pitch position for Arsenal and the combined NS xG value for the opponent based on where possession is won.

Overall, and without regard for pass volume or minutes played, Guendouzi has a net positive 5.02 NS xG for Arsenal in 2019/10.

This puts him top of the Arsenal "risk/reward" passing charts and we feel is a much better single figure metric to describe a player's involvement in progressing his side towards the opponents goal.

Not only does it quantify individual involvement and utilses every pass attempted, it also penalises reckless or sloppy execution that leads to change of possession.

Here's the current pass risk/reward numbers for all 20 Premier League players with a minimum number of attempts.