Where the model has them

The model has Liverpool finishing around 4th, with a 0.65% chance of lifting the title, a 26.91% shot at the top four, and a 0.91% risk of relegation. This projection comes from their attack strength multiplier of 1.16 and a defence multiplier of 0.98. The attacking Elo is 1710 and the defending Elo is 1712. Simply put, the model sees them as a touch above average in attack and a hair below average in defence.

In attack

Liverpool’s attack strength multiplier of 1.16 indicates they’re slightly stronger than the league average. Key to this is Hugo Ekitiké, who scored 14 goals last season, contributing 28% of the team’s total. He also had 75 shots, appearing in 80% of games. Dominik Szoboszlai provided 11 assists in 47 appearances, making up 21% of the team's assists. Other top scorers include Szoboszlai with 11 goals and 11 assists, and Cody Gakpo with 9 goals and 5 assists.

In defence

Defensively, Liverpool’s multiplier of 0.98 shows they’re just a shade below the league average. The defensive-actions leaders are Trey Nyoni with 5.07 per 90, Ryan Gravenberch with 3.59 per 90, and Jérémy Jacquet with 3.34 per 90. Jacquet also won 27 tackles in just 19 appearances, showing a solid presence at the back.

What the window changed

The transfer window saw some shifts. The attack multiplier dropped from 1.19 to 1.16, mainly due to the departure of Mohamed Salah, who scored 9 goals last season. Victor Muñoz joined, contributing 6 goals last season, but it wasn’t enough to fully offset Salah’s exit. Defensively, the multiplier rose slightly from 0.96 to 0.98 with the arrival of Jérémy Jacquet, who had 62 defensive actions last season. The departure of Ibrahima Konaté had a minor impact, but Jacquet’s addition helped stabilise the backline.

Weaknesses and risks

The model doesn’t flag any specific weaknesses for Liverpool. The main risk to their projection lies in the slight drop in attack strength post-Salah and the need for Jacquet to immediately fill the void left by Konaté. If they can manage these transitions smoothly, their projected finish around 4th looks fair.

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Key players (last season)

CategoryPlayerTotalPer game1+ rate
GoalsHugo Ekitiké140.3528%
AssistsDominik Szoboszlai110.2321%
ShotsHugo Ekitiké751.8880%
Tackles wonJérémy Jacquet271.4279%
Fouls drawnVictor Muñoz541.5982%
Fouls committedDominik Szoboszlai491.0466%

Defensive-actions leaders (per 90)

PlayerTackles+Int+Blocks /90Apps
Trey Nyoni5.078
Ryan Gravenberch3.5946
Jérémy Jacquet3.3419

Transfer impact (model)

_Model profile generated from the BetSignals season simulation. Player figures are last season's totals._