La Liga teams radars and xG diff dynamics. Almeria anomaly. Matchday 7.

Mikhail Borodastov
5 min readSep 27, 2023

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La Liga preview.

  1. Dynamics

The chats show the dynamics of non-penalty xG difference for La Liga teams before the 7th round. There are considered 12 last games. The xG values are processed by moving average with 3 game window. It means that for last three Barcelona games with 0.4, 1.6 and 0.1 npxG we get one point on graph 2.1 / 3 = 0.7. (extreme point on right side for first graph).

The process of averaging is needed for getting representative picture that is comfortable for analysis.

There are also trendlines built for the games of current season. It can help to define positive or negative dynamic at this moment.

The best: Girona, Real Madrid, Athletic.

The worst: Cadiz, Getafe, Betis.

The one more thing that probably catches your eye is red trendline for Barcelona. It’s the single team from TOP5 with negative dynamics. This example is indicative case in point that why it’s highly important to look not only at statics values of metric at specific moment, but also at the trendline.

Next we will see that Barca is the leader by average xG and xG diff per game in La Liga.

2. Statics

The rank of Top3 teams by xG per game is surprised me. Here is no mistake. Almeria placed on 3rd row after Barcelona and Girona being last in La League by earning points. Almeria got 10.1 npxG and scored just 7 goals whithin Girona with the same 10.1 npxG scored 16 times. The same picture from the point of defense, Almeria concedes much more then opposition teams creates in average. They conceded 13 times with 7.3 npxG allowed.

3. Radars

3.1 Sevilla — Almería

Attacking radar

Almeria takes more then 6 shots on target in average per game and creates 1.68 expected goals. By shots on target Almeria got into 96 percentile that correspond best 4% of teams from Top5 league from last 5 seasons. It’s incredible for team from last place in the standings.

Defensive radar

Sevilla is on top by PPDA (passes per defensive action). It means that in average on each 7.8 opponent passes Sevilla players make a some defensive actions (interception, tackle, foul, challenge) that leads to difficulties in buildup and creating long passing chains for opposite team.

3.2 Mallorca — Barcelona

Attacking radar

On the fist sight result of comparison seams obvious. But later (game was played yesterday) we can one more time ensure that there are much more additional details which affect on the final result (injure of one of your key midfielder, lack of the best scorer on first minutes, grass being wet, good realization of your opponents and much more details finally didn’t allow one team dominate another).

Defensive radar

3.3 Athletic — Getafe

Attacking radar

Defensive radar

Athletic Bilbao alongside with Atlético Madrid share first place in La liga by expected dangerous per one shot from opposition teams and show just 0.07 xG. Granada has the worst result in league with 0.16 xG.

Athletic also show the best digits in La Liga by total xG earned by their opponents — just 0.75 xG per game. There are just 3 teams besides Athletic which also have less then 1 expected conceded goal per game: Atletico, Valencia, Las Palmas.

3.4 Real Madrid — Las Palmas

Attacking radar

Defensive radar

Las Palmas is ranked second place in La Liga by created xG (0.89) by opposite teams and by GCA against they are on the top in league with 0.83 actions per game. GCA (Goal-creating actions) is very controversial metric from point of interpretability. GCA includes itself two last attacking actions before scoring the goal.

It means that Las Palmas allows for opposition team less than 1 such of actions per match. This statist is closely tied with number of conceded goals. Las Palmas have just 4. Maximum you can earn 8 GCA for 4 scores, but Las Palmas has just 5.

Thus just one goal came with two useful actions in buildup phase (passes, tack-ons and drawing fouls). Another words it’s difficult to create chances from the open play.

3.5 Villarreal — Girona

Attacking radar

Defensive radar

3.6 Cádiz — Rayo Vallecano

Attacking radar

Defensive radar

3.7 Valencia — Real Sociedad

Attacking radar

Defensive radar

3.8 Celta — Vigo Alavés

Attacking radar

Defensive radar

3.9 Granada — Betis

Attacking radar

Defensive radar

3.10 Osasuna — Atlético Madrid

Attacking radar

Defensive radar

More information about football metrics, analysis football data via python and much more you can find here t.me/footsci_eng.

PS

Sources of data

https://fbref.com/ - FBRF data

StatsBomb radar bulding

https://github.com/Slothfulwave612/soccerplots/blob/master/docs/radar_chart.md

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Mikhail Borodastov
Mikhail Borodastov

Written by Mikhail Borodastov

ML Product Manager 🚀 | ex- Data Scientist 📊 | Football Analytics Enthusiast ⚽

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