Kenny Miller is proving the doubters wrong

Kenny Miller, courtesy of SNS

written by – Rangers Report   graph by – Mike Driggs

Many supporters were surprised when Rangers re-signed 36-year old Kenny Miller for the 2015-16 season & then again for the 2016-17 season.  Miller was coming off back-to-back subpar seasons, both in his return to Ibrox & his previous stint with the Vancouver Whitecaps.

Some skeptics may still remain, but the objective data suggests that he has become one of the team’s most proficient & effective players.

Our graphics wizard, Mike Driggs, has developed a DIY tool to compare players. It’s a graph that fans of Football Manager & those of you used to seeing statistical presentations from other leagues will be very accustomed to seeing.

Below you will see how Miller’s statistics compare to Rangers’ leading scorer Martyn Waghorn.  Waghorn is the reference point, not in an attempt to indict him, but rather to use, arguably the best forward in the Championship, as a benchmark for comparison purposes.

The statistics include:

Non-penalty goals per 90 minutes:  Waghorn has eight goals from the penalty spot so it’s important not to have those skew numbers too much

Assists per 90 minutes

Expected Goals per 90 minutes:  how many goals each player is expected to score per 90 minutes based on where & how the shot is taken (or another way of looking at it is – what percent chance will a player get a goal over a 90 minute stretch)

Shooting Percentage:  what % of shots on target beat the goalie for a goal

Shooting Accuracy:  what % of shots are on target (either forcing the goalie into a save or beating him for a goal)

Scoring Chance Percentage:  scoring chances are defined as shots taken from a High Danger or Very High Danger area.  Basically the heart of the penalty area inwards towards the goal.  Then what % of High/Very High Danger shots on target beat the goalie for a goal.  In essence, we are measuring how effective of a finisher the player is when they are in ‘their office’

Expected Goals per shot:  this is a way to measure how dangerous each players’ shot is on average.  When it comes to forwards, are they getting a high rate of shots from High/Very High Danger areas or are they relying too much on shots with a lower rate of success?

Shots per 90 minutes

courtesy of Mike Driggs
courtesy of Mike Driggs


Player NPG/90 A/90 xG/90 Sh% ShAcc Scoring Chance Sh % xG per Shot Sh/90
Martyn Waghorn 0.62 0.31 0.54 0.408 0.544 0.391 0.115 4.67
Kenny Miller 0.68 0.10 0.53 0.467 0.500 0.500 0.182 2.91
  • Even though Martyn Waghorn has scored 20 goals this season & Miller has only scored seven – when you look at the results from this lens – Miller has been just as effective when narrowing the evaluation to certain elements.
  • Waghorn’s effectiveness is very much rooted in the sheer volume of pressure he puts on a defence.  He has 90 shots this season, which is 27 more then the next highest shot total from Jason Cummings.  Also, when comparing him to Kenny Miller – his rates are even more impressive given that he has played 806 more minutes this season.
  • Waghorn’s all around play has been a revelation this season & his assist per 90 support that ‘eyeball test.’
  • Regardless, the stats highlight how effective Miller has been this season.  His Expected Goal per shot of is an indicator that the vast majority of his shots are coming from areas on the pitch that create dangerous shots on goal.  Of his shots, 73% can be classified as Scoring Chances & 80% of his shots on target have come from those High/Very High Danger shots.

Full disclosure:  the impetus of this post was the fact that Mike had this really cool graphic tool to play with & we naturally gravitated towards comparing Rangers two forwards.

So, it’s request time:  What other players would you like to see compared using this style of graph?  

We have the stats for each player in the Championship – so who should we compare next?  


You can follow Rangers Report on Twitter @TheGersReport

You can follow Mike Driggs on Twitter @RSCPDX & to experience higher definition, interactive versions of these graphs make sure to visit Mike’s website.


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