Analyzing the Premier League table based on Expected Points (xP)

The use of probability models in football to calculate Expected Goals, Expected Goals Conceded and Expected Points, have taken off to new heights in recent years – with more fans, coaches, managers and even players paying attention to these hypothetical numbers. Between statistical probability, the actual result, and the expectations for all that has been produced, we analyze how many points each team should have won in each match, based on Expected Points.

GOING DEEPER INTO THE DATA…

Football is a sport where many factors come together, but advanced statistics can argue that a team is more likely to win if they continue to generate more quality chances than their opponents.

The Expected Points (xP) model is based around the Expected Goals (xG) of a match. Once we have the xG of each team, we intricate through a distribution model, what would happen if we simulated the same match thousands of times, getting to know the probability each team would have to win, draw and lose with the same expected goals generated. In this way, we obtain a probability percentage for each team and a value of Expected Points.

HOW xP IS CALCULATED

Expected Points (xP) takes into consideration a team’s underlying numbers in xG and xG against. Teams higher in xP typically have a high xG, and a low xG against. So you may be asking – what is xG?

xG (Expected Goals) takes into consideration the quality of chances in a match, based on several factors – including distance from goal, pressure applied, and the type of shot taken. An absolute worldie that results in a goal, such as Andros’ Townsend’s goal against Manchester City a few years back, may even have an xG of 0.01 – meaning that you would expect that kind of goal to be scored one out of every one hundred times.

After simulating with the distribution model and multiplying each percentage obtained by the value of each sign (win, draw, loss), we obtain the expected points of that match if it happened thousands of times. And therefore, we would obtain a form of deservedness that becomes useful to study at any point in the Premier League season.

Let’s take as an example, the Premier League table until today – February 21, 2022.

Rank	Team	GP	Goals	Conceded	Pts.
1	Manchester City	26	63	17	63
2	Liverpool	25	64	20	57
3	Chelsea	25	49	18	50
4	Manchester United	26	44	34	46
5	West Ham	26	45	34	42
6	Arsenal	23	36	26	42
7	Wolverhampton Wanderers	24	23	18	40
8	Tottenham Hotspur	23	31	31	39
9	Brighton & Hove Albion	25	25	28	33
10	Southampton	25	32	37	32
11	Leicester City	23	37	43	27
12	Aston Villa	24	31	37	27
13	Crystal Palace	25	32	36	26
14	Brentford	26	27	42	24
15	Leeds United	24	29	50	23
16	Everton	23	28	40	22
17	Newcastle United	24	26	45	22
18	Watford	24	24	43	18
19	Burnley	22	20	29	17
20	Norwich City	25	15	53	17

If we take into consideration, the xG, xG Conceded, and xPoints, the picture would be different in many cases. As you can see in table 2, the first 4 teams are in a fair position and until now, they have accumulated the points they statistically deserve. The bottom feeders also remain in the same places, with only Everton achieving a significant change. Here is how the table would look based on Expected Points rather than actual points.

Rank	Teams	Points	xP	Difference
1	Manchester City	63	60.5	0
2	Liverpool FC	57	54.2	0
3	Chelsea	50	45.5	0
4	Manchester United	46	37.3	0
5	Arsenal FC	42	36.3	0
6	West Ham United	42	33.7	0
7	Brentford	24	32.4	+7
8	Crystal Palace	26	31.1	+5
9	Brighton & Hove Albion	33	30.4	0
10	Tottenham Hotspur	39	29.6	-2
11	Southampton	32	29.1	-1
12	Everton FC	22	28.4	+4
13	Wolverhampton Wanderers	40	28.1	-6
14	Aston Villa	27	23.7	-3
15	Leicester City	27	22.7	-3
16	Newcastle United	22	22.1	+1
17	Leeds United	23	21.3	-2
18	Watford	18	18.6	0
19	Burnley	17	18.1	0
20	Norwich City	17	12.2	0

As you can see from the table, Brentford, Crystal Palace and Everton are the clubs who have been the most “unlucky”, otherwise known as “underperforming”. On Expected Points, Thomas Frank’s Brentford would be 7th place, above the likes of Spurs, Wolves and Brighton. The example of Wolverhampton Wanderers also provides an interesting case study. Bruno Lage’s Wolves sit in 7th place at this time, but based on Expected Points, they wouldn’t even make the top ten, falling all the way to 13th. Interestingly, Antonio Conte’s Spurs would be tenth, despite their positive performances under the Italian to make up for Nuno’s horrific start.

In addition to xP, a team’s control of the possession, or lack thereof, is another intriguing data source to study. While possession isn’t the be all end all, it typically allows a team the possibility to create more chances, and more chances of a higher quality. By re-organizing the table based on possession, we can attempt to discover whether or not this thought process is in fact true, or a myth.

Rank	Team	Possession %	Chances	Goals Scored	Conversion Rate
1	Manchester City	67%	227	63	28%
2	Liverpool FC	61%	227	64	28%
3	Brighton & Hove Albion	57%	134	25	19%
4	Chelsea	56%	180	49	27%
5	Leeds United	54%	112	29	26%
6	Manchester United	52%	191	44	23%
7	Arsenal FC	52%	141	36	26%
8	Crystal Palace	51%	131	32	24%
9	Tottenham Hotspur	49%	140	31	22%
10	Southampton	49%	124	32	26%
11	West Ham United	48%	168	45	27%
12	Leicester City	48%	129	37	29%
13	Wolverhampton Wanderers	47%	96	23	24%
14	Aston Villa	46%	106	31	29%
15	Brentford	45%	127	27	21%
16	Norwich City	44%	91	15	16%
17	Everton FC	43%	121	28	23%
18	Watford	43%	117	24	21%
19	Newcastle United	41%	100	26	26%
20	Burnley	39%	110	20	18%

Based on the above possession data, the Premier League table would not vary greatly. Wolverhampton and West Ham drop undeservedly into the bottom half, while Vieira’s Crystal Palace moves into 8th. The biggest leap of all sees Leeds United move into fifth, with Brighton in third. Beyond those outrageous moves, the Premier League table based on possession doesn’t look drastically different from the actual Premier League table. This suggests that possession could be a potentially underrated value, even if it’s not the be all end all – as demonstrated by Leeds and Brighton.

Conclusion

Data analysis in football continues to grow, with xP and xG providing a different way of examining the game, and examining a team’s performance. While these underlying numbers only tell one side of the story, it has to be said that actual point and actual goal data may also only tell one side to the story, and that both metrics can be useful to understanding the context of the game.

Processing…

Success! You're on the list.

Whoops! There was an error and we couldn't process your subscription. Please reload the page and try again.

Canadian Premier League Scouting Database – Matteo de Brienne

Matteo de Brienne arrived onto the scene of the Canadian Premier League just last year, coming to life toward the end of the campaign to score one of the most outrageous hits. The young Canadian would have expected to have more of a role to play this season, but I don’t think anyone expected such…

by Rhys Desmond June 6, 2023

The next evolution of my ‘Role Continuity Evaluation System’ one year later

At the beginning of 2022, I established twenty-two player roles that footballers often adopt on the pitch. One of the objectives of the RCES and the presentation of ‘IQ scores’ pertaining to a player’s specific role was to present an alternative to the statistics sites that use data as their sole metric for evaluating players.…

by Rhys Desmond June 5, 2023June 5, 2023

How I create scouting reports for pro clubs

Scouting seems to be one of those professions that just about anyone thinks they can get into. And to an extent – with good reason! With a knowledge and passion for your sport of choice, it’s not incredibly difficult to take the necessary courses and begin the path toward being a scout. But talent identification…

by Rhys Desmond May 23, 2023May 25, 2023