Los Angeles FC: identifying problems and suggesting solutions

xG analysis goals scored and conceded

When we take a closer look on the goals scored and conceded of LAFC for the last season and the other teams that competed in the MLS Play Offs and compare those numbers with Expected Goals values, the following numbers are found for goals scored:

The goals scored per 90 minutes are corrected for the different amount of games the teams played in both the regular season and the playoffs. Except for champion Atlanta United, Los Angeles FC scored the highest amount of goals per 90 minutes. The xG model we use expected only 62.7 goals instead of 70. LAFC was able to score more often compared to what could be expected based on the quality of their scoring opportunities. This shows their attacking quality in finishing scoring opportunities. Only four teams scored more goals than could be expected based on xG.

However, the xG values on goals scored shows LAFC defensive vulnerability on the other hand. The team conceded 55 goals in total. The amount of goals conceded per 90 minutes (1.57) is only surpassed by Real Salt Lake City with an average of 1.76 goals conceded. Based on Expected Goals, an amount of 47.9 goals conceded was expected. LAFC was somehow not able to defend scoring opportunities as could be expected based on xG.

In short, based on Expected Goals values LAFC combined attacking quality in finishing scoring chances with defensive vulnerability in defending scoring opportunities and defending opponent’s attacks.

Characteristic team stats Los Angeles FC

After the xG analysis of the goals scored and conceded, we will have a closer look on general team statistics for the 2018 season. With an average ball possession percentage of 54%, the team was one of the most dominant teams in terms of possession. The team used this possession to have an attacking output of 13.4 shots per 90 minutes, which was only surpassed by Sporting Kansas City. Except for two teams, LAFC used the least amount of crosses in the league but was able to reach the opponent box using among others through passes and smart passes (only New York RB used more on average). LAFC was reluctant in using long passes, no team in the MLS used less long passes. Benny Feilhaber, who left the club after the end of the 2018 season, was one of the key players in possession with high presence in passing, through passing and passes to the final third. Furthermore, the team was dependent on the creativity of Rossi and Vela in creating chances, sending through passes and in attempting shots. The arrival of Diomande in May 2018 helped them as well in finishing scoring chances.

In defense, LAFC conceded 10.7 shots per 90 minutes. In the MLS, 5 teams conceded less and among others is Atlanta United. LAFC showed a decent success percentage in aerial duels (only 3 teams scored higher), but their success in defensive duels is low compared to other teams in the MLS playoffs.

Team strength in 2019

LAFC had a great start of the 2019 MLS season, grabbing 24 points in 11 games. Let’s have a look at the strength of the team using SciSkill Index values and compare them to the other MLS teams. We will use a general 1-4-3-3 formation to compare the players and their SciSkill Score and SciSkill Potential to get an overview of the quality and composition of the teams.

Based on this League Map, the differences are small but Los Angeles FC has one of the strongest teams in the league. Clearly, their quality can be found in the attacking positions with Vela, Rossi, Blessing and Diomande having high SciSkill Scores compared to the attackers of other teams. However, in defense, other (strong) teams can field players with a higher SciSkill Score. Goalkeeper Miller is only starting his second season in the MLS and faced a higher amount of goals conceded than was expected last season. Moreover, at the left back position LAFC has the 35-year-old Harvey, El-Munir and the 22-year-old Niko Hamalainen who came on loan from QPR. The last one only played a few games in senior football but was talented enough to be handed his Finland national team debut. What does the team look like in the Shadow Team functionality in SciSports’ platform?

© SciSports Platform

When you take a look at how the team looks in our Shadow Team function in SciSports’ platform, you will see that when we compare the players with the average league SciSkill Score especially on the left back position and the goalkeeper position, the level is below average and differs a lot compared to the other players. If we compare the SciSkill Potential values, as you might want to field a player with a high potential to give them the much needed playing time, you will see that on those positions the SciSkill Potential is also low.

What would it look like if Los Angeles FC would use SciSports’ platform to find a good left back that is able to strengthen the team? Let’s get started with setting the right criteria:

• Age: We want to bring in young and ambitious players, not older than 25 years.
• SciSkill Level: The player needs to be a direct reinforcement of the team so let’s state that he at least needs to be above the league average SciSkill Level. We will use a range of SciSkill 60 to 80.
• Let’s assume LAFC is looking for a Wing Back or Inverted Wing Back to strengthen their attacking play. The player does not necessary be good in crossing, as we are not attempting headers a lot. We will look for players that have a similar ‘Player Role’ as Jordi Alba.
• As we don’t want to search for players that are too expensive for the club, we put the market value estimate to a maximum of 2 million Euros. We will search for players that have a contract until the end of 2020.

We find a list of 41 players that have the level to play for LAFC, who are used to play in a Wing Back role and are an immediate reinforcement to the team. The first names with the highest similarity score compared to Jordi Alba:

© SciSports Platform

Want to find out the other names? Or want to find out who is the best in defending actions?