The 2019/20 season has spawned a very talented set of teenage stars in the Premier League such as Mason Greenwood, Bukayo Saka, Billy Gilmour, Gabriel Martinelli, Callum Hudson-Odoi and more.
Some impressed more than others, but the Manchester United man is someone who is amongst the very best in that list of names. Mason Greenwood registered 17 goals and 5 assists across all competitions for the senior team this season.
Initially, the United academy graduate was given more than his usual share of first-team minutes, after new arrival Daniel James proved to be rather unreliable in a starting role. Since then, the forward has proven to be what James could not be.
The youngster is clinical, versatile, intelligent, and rapid. In his debut season, the Englishman impressed the world with his style that closely resembles Robin van Persie and almost elite levels of finishing. It is fair to say that the teenager is not someone to be taken lightly. Moreover, the striker is also a delight to watch, on top of how much his stats impress.
However, there are areas of concern. These are areas that casual fans would never bother with, even some serious fans wouldn’t. But anyone could bet a fortune that the Red Devils’ analytics team and coaches are giving their attention to this.
Advanced metrics have brought a completely different dimension to football analytics. These stats are a window into a player’s underlying performances; numbers that may not be obvious to the eye or be completely different from regular stats fans usually deal with. And it is one of these metrics that the England U-21 international lacks in — xG.
According to Opta, xG (expected goal) ‘measures the quality of a shot based on several variables such as assist type, shot angle, and distance from goal, whether it was a headed shot and whether it was defined as a big chance.’
The expected goal statistic primarily measures the quality of a goal. It is used to measure the likelihood of a goal occurring based on several aforementioned chances. And by adding this metric up, one can determine how many goals a team, or a player is expected to score by the end of a campaign.
The xG for Mason Greenwood in the Premier League this season was calculated to be 3.39. But the 18-year-old has outperformed that figure by scoring 10. The first insight we can draw from this stat is that the young forward is scoring from tougher positions and chances.
Although this does make him very talented, there’s a negative aspect to it too. Outperforming xG is not very sustainable, because in the long run, xG almost surely catches up with the team or a player at some point. However, a player outperforming expected metrics could also be seen as a sign of improvement.
For Greenwood in our case, what can be derived from this is that Greenwood has lucky in the number of goals scored this season and his xG might catch up to him soon during his dry spells.
On the other hand, if a team is outperforming xG, it means that the goals scored have come from luck and unexpected mistakes. This implies that at some point, the results will reflect the same numbers calculated as xG.
A prime example of this would be Unai Emery’s Arsenal last season during their 22-game unbeaten run. The Gunners managed to get points during this run but most of the time, they were outscoring their expected goals. Ultimately, they ran out of steam and Emery ended up getting sacked a year later.
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It is up to one’s views if they would like to take advanced metrics such as xG, xA (expected assists), etc. seriously. But keep in mind that these are statistics clubs take very seriously, especially when it comes to finding players to sign based on the team’s immediate needs.
The discourse regarding advanced metrics is very chaotic. One side insists on its relevance whilst the other refutes its practicality. Most of the time these stats do catch up but sometimes they don’t — what will it be in Greenwood’s case? Only time will tell.
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