3 Moises Caicedo alternatives Arsenal should consider before the deadline
For Arsenal, their objective before the January transfer deadline couldn’t be any clearer: sign a midfielder.
Thomas Partey may not have sustained a serious injury in the FA Cup defeat to Manchester City, but Arsenal’s depth behind the Ghanaian has been further compromised by Mohamed Elneny’s projected absence. With the veteran Egyptian poised to be sidelined for potentially the rest of the season, the onus will fall on the unready Sambi Lokonga should Partey be forced to miss time during the second half of the season.
That’s a scenario Mikel Arteta will want to avoid as he goes in search of the Premier League title.
Their approach for Brighton’s Moises Caicedo is a signal of their intent in the closing stages of the January window, but the Seagulls’ lofty valuation of the 21-year-old, one they seemingly won’t shift from, means a move is unlikely to transpire before the deadline.
3 Moises Caicedo alternatives Arsenal should consider before the deadline
Thus, with Arsenal intent on bolstering their midfield, an alternative must be sounded out. Here are three options the Gunners should consider.
1. Ibrahim Sangare
Arsenal caught a first-hand glimpse of Sangare this season as they took on PSV in the Europa League group stage. For me, the holding midfielder was the Dutch side’s standout performer in the Gunners’ 1-0 win at the Emirates, and he impressed again in the reverse fixture – although, Xavi Simons stole the show on that occasion.
The Ivorian is a physical behemoth; a midfielder that combines robustness with elegance in possession. He’s press resistant and excellent at finding his way out of tight spaces, while athleticism allows him to eat up ground at a canter. Overall, he’s not too dissimilar to Partey.
Sangare has to be playing in a top-five European league soon despite committing his long-term future to PSV in the summer. FBRef’s scouting report depicts the 25-year-old’s recent proficiency, as he stands out in almost every relevant statistical category.
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