For some time now, football has incorporated a term of Anglo-Saxon origin. Are the ‘expected goals’ (expected sips) or simply xG, an abbreviation used for a metric that measures the probability of a shot ending in a goal. This value allows us to know how much danger a player generates and what capacity he has to transform it into points. The result is the XGdifthat is to say, the difference between great occasions and their outcome. The undisputed leader of LaLiga in this section is Jude Bellingham, top scorer for Real Madrid and the tournament.
According to data from WhoScored, a portal specialized in football statistics, The Real Madrid midfielder has a figure of 10.43 expected goals. However, he has managed to score 16 goals so far this season. To understand this difference there is the xG model, which takes into account distance to goal, angle with respect to the goal, part of the body with which a shot is taken, the type of assistance or previous action.
Bellingham, Kirian and Savinho, the most successful
‘Expected goals’ are an indicator of ‘Big Data’, a set of tools used by all professional teams. With this information, the system attributes a value between 0 and 1 to each shot, which expresses the probability that it will end in a goal. Therefore, Bellingham has scored more goals than would be expected given the quality of the chances it has had. When a footballer scores more than his xG suggests, it is concluded that his finishing is good.
The 29 days played in the League allow a reliable calculation to be made. Bellingham did not become Real Madrid’s top scorer, but with his goals he has filled part of the void left by Benzema. Ancelotti has only one pure ‘9’ this season, Joselu, but The Italian has chosen to play many games without a fixed reference in attack. To better understand the meaning of xG, the Galician striker has a negative indicator of -1.09 xGDif. That is to say, the striker has had opportunities to generate 9.09 goals, but he has only managed to score eight.
The second LaLiga player with the best differential balance is Kirian Rodriguez, from UD Las Palmas, with an xGDif of 4.09; followed by Savinhofrom Girona (3.26 positive); Borja Mayoral, now injured, but the top Spanish scorer in the championship (3.24); and Sorloth, from Villarreal, completes the list (2.96).
The most lethal players in LaLiga
Jude Bellingham (Real Madrid): 5.57 xGDif Kirian Rodríguez (Las Palmas): 4.09 Savinho (Girona): 3.26 Borja Mayoral (Getafe): 3.24 Alexander Sorloth (Villarreal): 2.96 Dani Carvajal ( Real Madrid): 2.75 Willian José (Betis): 2.66 Ricard Sánchez (Granada): 2.49 Darwin Machís (Cádiz): 2.43 Marcos Llorente (Atlético): 2.42
Larin and Alavés, the most mistaken player and club
But there are not only forwards in the ‘top 10’ of lethality in the championship. The four goals scored by Carvajal compared to the 1.25 xG value given to him by ‘Big Data’ put him in sixth position. They follow him Willian José (2.66), from Betis; Ricard SanchezGranada winger (2.49); Darwin Machisfrom Cádiz (2.43) and Marcos Llorentefrom Atlético (2.42).
The table of footballers who waste the most opportunities is led by Cyle LarinMallorca forward, who due to the quality of the chances he has had should take at least eight goals (8.68) and only accumulates two. It has a differential of -6.68, almost double that of the second on the list, Kike Garciafrom Alavés (-3.72), who is followed by his teammate Samu Omorodion (-3.5). With the values of their main forwards it is not surprising that The Basque team has the worst xGDif of the entire category (-16.32).
The list of the players who have managed to score the least compared to the expected goals continues with the names of Alex Baenafrom Villarreal (-3.26); Jungle Sancetdel Athletic (-3,12); Vedat Muriqifrom Mallorca (-3.1); Iago Aspasfrom Celta (-3.05); Jon Guridifrom Alavés (-2.78); Antonio Puertasfrom Granada (-2.7) and closes the ‘top 10’ Robert Lewandowski, from Barça.
Robert Lewandowski, against Lino and Witsel in FC Barcelona – Atlético del Metropolitano. / Valentí Enrich
Barça is the sixth that fails the most and Girona leads the success
Logically, despite the mistake, the more opportunities are generated, the more likely it is to score, which is why footballers who have scored many goals appear in the statistics of negative values. In fact, the absolute leader in expected goals is Lewandowski (15.66); in front of Moratafrom Atlético (14.46); Artem Dovbykfrom Girona (13.83); Budimirof Health (12.9); Larsenfrom Celta (12.01); Vinicius, from Real Madrid (11.57); Own Omorodion (11,5); Guruzetafrom Athletic (11.47) and Myrto Uzunifrom Granada (10.8).
The ‘expected goals’ have been on the lips of coaches like Xavi. After a difficult victory against Celta in Balaídos (1-2), the FC Barcelona coach said the following: “According to ‘Big Data’ we would be leaders of LaLiga due to the opportunities created”. The statement caused a revolution, because logically football is not an exact science, but the Barça coach’s phrase was and is true. FC Barcelona is the leader in xG, with 65.76 expected goalswell above the second in this statistic, Real Madrid, with 59.12 xG.
But the reality is that the ‘culé’ team has scored 57 goals, so they have a negative difference of -8.76, the sixth worst in the entire First Division. The most unfortunate team is Alavés, with only 23 goals scored out of the 39.32 that the ‘Big Data’ gives them (-16.32 xGDif), ahead of the bottom team Almeria (-10.75) and the Celta (-9,81).
On the contrary, the Girona, revelation of the category, is the one that best differentiates ‘Expected Goals’. With just 367 shots he has scored 59 goals compared to the 54.7 he should have due to the danger generated. Secondly there is the Real Madrid, with 62 goals scored for the expected 59.12, which translates into a positive xGDif of 2.88. In third position is the OUT Las Palmas, with expected goal difference of 0.98: 29 goals for 28.02 xG. Only five First Division clubs have positive values, which shows the pending work in this matter.
The teams with the least success in LaLiga
Alavés: -16.32 xGDif Almería: -10.75 Celta: -9.81 Mallorca: -9.63 Rayo: -9.19 Barcelona: -8.76 Cádiz: -7.67 Granada: -6.9 Seville : -5.11 Betis: -4.48
How can ‘expected goals’ be improved?
The expected goals with a useful tool. They serve to explain, for example, why certain teams give the sensation of dominating a match, but do not end up winning it. The metric allows us to understand, and above all quantify, the performance of the shots. This way, issues such as a player’s scoring positions can be corrected.
If you work to find better shooting options or ones that suit you better due to their characteristics, you can correct poor scoring differentials. However, like all data, it can be interpreted in a match context. A team can have a very high xG value in a match because it has dedicated itself to coming back during the match.
In a perfectly assembled squad, where everything works, the value of high-quality options is always high. Also the conversion. Using the data collected by xG, companies like StatsBomb have drawn several conclusions.
For example, the central areas of the area are better than the lateral ones; from the same distance, shots with feet are more likely to end in a goal than those with headers; crosses are more difficult to convert than low or deep passes; and? The position or properties of a shot are much more important than the player who takes it. Notes that seem logical, but are not applied so naturally, as demonstrated by the differentials that obsess teams in their search for excellence.
Launch of a match between Athletic and Alavés, the team with the least aim in LaLiga. / JAVIER ZORRILLA / EFE
2024-03-28 07:04:26
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