Mohamed Salah at Roma and Liverpool

  1. Introduction

In this post, the shot performance of M Salah at Roma an Livepool is compared.  The objective is to find any statistically significant (p<0.05) and non significant (but revealing) differences.   Significant differences are indicated by the acronym SSD (Statistical Significant Difference) in their comment line.

The Decision Trees method (https://en.wikipedia.org/wiki/Decision_tree_learning) is used for the analysis, in particuar the CART algorithms.

  1. Stats and Analysis

Salah has played for Roma in Serie A in the 2016-17 season, and for Liverpool  in the EPL in 2017-18

Salah 01

Salah 02

Salah 03

Salah 04

Salah 07

3.  Summary

The analysis shows that Salah performance has much improved at Liverpool.  The number of goals scored – double his tally (31 vs. 15) at Roma with roughly the same number of matches and minutes played – is a strong indicator.  But we must account that at Roma he had fewer shots (74 vs. 132) as Dzeko was the main target there.

The quality of his shot has improved significantly (fig. 2); unfortunately, this is a rather subjective evaluation parameter, and can’t be given too much weight.  But he is definitely shooting more from his left foot at Liverpool (Fig. 3). And under more defensive pressure than at Roma (Fig. 4), while receiving more Open Play passes (fig. 5).

Salah shooting location has also shifted from the right to the centre-right.  At Roma, his shots came mainly from the right side of the goal (Pic. 1), while at Liverpool were more evenly distributed, though the right side remained favourite.   Logically, this is also the side where most of his shots assists came from.

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Data by @StrataBet
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This article was written with the aid of StrataData (www.stratagem.co), which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform (https://app.stratabet.com), in addition to StrataBet Premium Recommendations (https://stratatips.co).

 

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About soccerlogic

I am data miner/scientist of twenty four year analysis experience of analysing complex data using machine learning tools. After a long and successful career as a Business Intelligence consultant, I founded Soccerlogic, a company that pioneered the application of advanced analytics to improving performance in football and other sports. Believe that artificial intelligence can be a 'game-changer' in team sports as it has proved to be in many other applications. Therefore passionate about finding ways to applying deep learning methods (AI) to further the analysis of team sports, football in particular.
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