As the quality of football worldwide improves year on year, teams are finding ways to adapt to the ever-changing environment. Whist the traditional wingers are dying breed, there are still some who are true to its original form. The EFL Championship creates a platform for such wingers to showcase their abilities.
In modern football, wingers can perform a variety of functions, such as inside forwards, traditional wide man or creative number 10s. The data analysis will only consider players who qualify based on the following metrics: xA(90), xG(90), Crosses(90), Crosses success (%), Dribbles(90) and dribble success (%). The analysis will use these metrics as they fully encompass what it means to be a winger. The modern winger needs to have a high output. They need to be able to beat their full-back in one-on-one situations. They must also be a threat from out wide with deliveries into the box. The data analysis will also only consider those wingers who have played more than 1000 minutes. This is so there is a large enough sample size to provide the best data.
The data analysis will also only consider wingers attacking output. As previously stated, wingers can offer a variety of functions for the team, with some being used because of their defensive work-rate rather than their attacking ability. This analysis is solely focused on a wingers input in the offensive third.
When determining the best winger, the data analysis will provide a shortlist based on the data that has been provided. It will be determined using a cumulative score of all the metrics.
Expected goal contribution
The expected goal contribution metric combines the xA(900 and xG(90) of the wingers in the league. Therefore, those wingers further along the graph will have a higher xG, and those wingers higher up the graph a greater xA. As we can see from the graph, the data is varied and needs some context. For example, players with higher xG, such as Martyn Waghorn and Jarrod Bowen (no longer in the championship but was enjoying a fine season so was included in the data) play as inside forwards, therefore have a higher xG(90). Whilst the operate in a traditional winger position, they tend to drift inside towards goal, hence the inflated statistics.
The player with the highest xA is Sergi Canos of Brentford. The former Liverpool youth product has an xA(90) of 0.35 which would suggest he is the best creator. However, it is important to consider when these chance creations would have arrived in-game. Canos is not a regular starter, so it is likely his contribution comes towards the end of games when the opposition is tired and the game is stretched, giving more room to operate in.
When considering who the most rounded player in this instance would be, it is hard to look past Said Benrahma, also of Brentford. The Frenchman has been scintillating in his second season at Griffin Park, and he looks destined to play in the Premier League, with or without Brentford. Considering the data, he has a high xG(90) for someone who is not an inside forward like Waghorn. This shows he is able to get into good goal scoring opportunities, and his decent xA(90) highlights he can do so whilst still being effective and creative in other areas of the pitch.
Crosses per 90/Cross success (%)
The next metric that the data analysis will consider is cross success (%) and crosses per 90. Crossing is a key part of a wingers game. Naturally, they spend most of their time out wide, and having a winger who can provide from this area is a key asset. For example, Trent Alexander Arnold and Andrew Robertson (neither are wingers but both have excellent crossing ability and given the way Liverpool play, spend most their time in forward positions) both have excellent crossing ability. As a result, they provide a large number of assists for Liverpool and are a key attacking outlet. This just shows the importance of crossing and the impact it can have on a side offensively.
Now, considering the data given, we can see that James McClean of Stoke looks like the stand-out player. He provides eight crosses per game with a decent success rate of around 32%. This suggests that in wide positions he is a threat, and can deliver a dangerous ball into the area around a third of the time.
However, the data once again needs to be considered with context. McClean is very one-footed and plays on the left side, his strong foot. It is likely therefore that given his lack of confidence on his right foot, his only option is to go on the outside and deliver a cross. Therefore, if he were playing on the right flank more often, the numbers may tell a different story.
As a result, when considering a players crossing ability, it might be worth solely looking at the success rate. This is because the volume of crosses can be skewed by far too many variables. In that case, the highest % rate would belong to Chris Solly of Charlton, at nearly 50%. This is a clear indicator that he is constantly a danger in wide areas.
Successful dribbles %/ dribbles per 90
The data analysis will now consider the next metric, which is dribbles per 90/ dribble success (%). Dribbles are key to a wingers game. Wingers will often be one-on-one with the full-back, and it is important they are able to beat them. Doing so allows them to get in behind, where they can look to create or score a goal. Good dribbling from wingers will also assist their side in the counter-attack, and bring their team up the pitch in periods they are getting dominated.
Once again, considering the data provided, it is clear to see there is one standout name with regards to this metric. Kazenga LuaLua of Luton stands alone in this regard. The wide man attempts nearly 13 dribbles per 90 and has a success rate of around 65%. As a result, he is an opposition nightmare and is a real threat to his side. He is able to get in behind and provide a threat going forward.
What we can also see from the data is that players who would perhaps usually play as number 10s, such as Lewis Holtby, have a lower success and attempt rate of dribbles. This is not unusual to see in the data. Such players build their game on finding pockets of space and playing 1-2s as opposed to driving at the opposition with the ball.
The data analysis will now consider the statistics and provide a shortlist. As previously stated, the shortlist will be determined based on the cumulative score of the players. By doing so, the data analysis hopes to provide a shortlist with well-rounded players and those players who excel in one area. This is so contributions that impact a team greatly, such as LuaLua’s dribbling are included in any shortlist.
With that being said, the shortlist is as follows. Chris Solly, James McClean, Junior Hoilett, Matt Phillips and Harry Coulson. Now, this is a list that will surprise people, as some would have expected the like of Joe Lolley, Jed Wallace or Said Benrahma to feature. However, as stated, the method by which the list was determined allowed those players who excel in one area of being a winger to feature.
Therefore, the data analysis has provided a shortlist for the best wingers in the league. The data has been measured in such a way that it has given an opportunity for players who excel in certain aspects of wing play to be considered. This because each aspect is just as important as each other, and depending on the needs of the time, having a winger who is excellent at a crossing may be more important than a winger can beat his man, for example.
However, the analysis also highlighted an important element, which is that statistics often need to be considered with a degree of context. That is to say, the style of play of a team heavily influences the statistics of a player. Whilst statistics are becoming more and more important, they need to be analysed based on the style of play. Borussia Dortmund or Liverpool would be the perfect example of this in practice. They continuously make excellent signings under Klopp, and they often buy from teams who play a similar way, to try and make the transition for the player as seamless as possible.