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Most Improved Scorers and the One-Man-Show’s

(Follow @Row-Z Report)

In this post, I try to look at the current status of Europe's attacking players. Although the sample size of matches are quite small (around eight games have been played in all leagues), per 90 minute figures might give some indicators for the remaining of the season. Let's go.

xG per 90

Using the Row-Z Report expected goals model, let’s take a look at the xG per 90 numbers for select players in Premier League. Below graph includes players with at least 1/3 of the total minutes played. (NPxG : non-penalty expected goals)

Building up on his marvelous 16-17 campaign, Harry Kane actually improved even further and became probably one of the best strikers this season in Europe. His xGp90 has increased from 0.5 to 0.8 (%59). Looking at the shot chart, it is impossible not to be impressed by his performance.

Other notable players:

  • Aguero was perfect, as always, but has been injured for some time now.

  • Joselu is on fourth spot with 0.78 xG per 90 minutes. He played an important role in Newcastle’s good start

  • Lukaku proved his worth and is now expected to score 0.66 – a 40% improvement on last season (but there may be a caveat, keep reading)

  • Sturridge, Pogba, Sterling and Vardy have also improved their production

  • Alexis Sanchez (Arsenal) and Coutinho (Liverpool) have had some difficulties so far – revealed by the drop in xG p90. Coutinho is particularly interesting, given that he has been the leading actor in summer’s biggest transfer saga.

xG trend over time For a more thorough analysis, let’s take a look at the xG p90 trends. To avoid sharp turns in the graphs, I used the 6-week moving averages.

After a slow start to the season, Harry Kane reached the level of 0.5 NPxG (i.e. a goal every other match) around November 16. He has been steadily producing since. Actually, Kane went up another gear this season– average around 0.8 – en route to his superstardom.

The transfer story Philippe Coutinho hasn’t been doing well this season. As seen on the graph, he has performed way below his last season performance so far, with around 0.16 NPxG p90.

How about United? Well, they have been good so far this season, but with volatile players.

Lukaku, for example: His output took a dive around November 16 and basically from that point onwards he used all the credit from his magnificent start. At the end of his season at Everton, his overall average regressed to around 0.5 xG p90. That is why I would take his current season numbers with a pinch of salt. Let’s wait and see. Pogba has a different story. He seems to have found his rhythm as the 16-17 season went on – and he had a good start this year as well.

We surely don’t need any graphs to say that Aguero’s injury is a misfortune. But do City really miss him? Probably not, given the latest results. What about other teams, though? Leicester’s Vardy, for example, has been a goal machine(0.40 NPxG p90 over two seasons) for Leicester . How much could his injury hurt?

Contribution to xG

Trying to answer that question, let’s now turn to xG contributors. For that, I calculate each player’s portion in team’s total xG created. By doing so, I try to estimate the individual contributions to team output. Here are top 3 xG contributors for some Premier league sides.

God bless Vardy! As seen on the graph, a whopping 81% of Leicester’s total xG came from three players this season. Vardy himself is very crucial – he accounts for half of his team’s xG – a one-man-show. For the whole season last year, the same ratio was only 23%. This might be a consequence of Leicester’s style of play and formation but let’s save that for a future post.

  • Palace are not that much ‘egalitarian’ either. Benteke was their clear leader with 36% of total xG last year. Their dependence on him decreased lately – 19% on the same metric this season

  • Tottenham depend on his star heavily as well: Harry Kane accounts for 40% of the xG

And here is a similar graph for Serie A teams. Percentage shows the ratio of total xG created by that player in 17-18 (eight matches). Icardi (Inter), Immobile (Lazio) and last year’s top scorer Dzeko (Roma) are spotted at the top, according to this ‘one-man show’ metric.


In sports analytics field, value of a player (to his/her team) is heavily researched. To make a fairer assessment, one needs to account for the ‘incremental’ value that a player creates. After all, if Vardy gets injured, he will be replaced by another player. Therefore, Vardy’s real value lies on his ‘additional’ output.

Namely the value over replacement player, this metric (and its variants) are quite commonly used in basketball and baseball. In football, The Rangers Report has an excellent work on the topic, where he ranks Scottish players with regard to their incremental scoring ability. I highly recommend everyone to take a look. Here at Row-Z Report, I certainly want to touch on this topic as well. Hopefully soon.

Until next time!


If you liked this post, you could also follow me on Twitter: @RowZReport.


This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.


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