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Old 05-08-2017, 09:36   #1
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Join Date: Feb 2011
Location: North Pole
Fav. Players: Baresi, Maldini, Albertini, Weah, Nesta, Rino, Kaka, Sheva, Pippo, De Sciglio, El Shaarawy
Default Cool Radar Plots for Visualizing Football Stats

I find this is a very interesting way to look at players' stats

Radar boundaries represent the top 5% and bottom 5% of all statistical production by players in that position across 5 leagues (EPL, Bundesliga, La Liga, Serie A, and Ligue 1) and 5 seasons of data. In stat-y terms, the cut-offs are at two standard deviations of statistical production.

  • The only thing these represent is statistical output.
  • If you put players in different systems, it may change their output.
  • If you put them in different positions, it almost certainly WILL change their output.
  • Age will also change statistical output.
  • In short, these are a tool to help evaluate players. Like any tool, they have strengths and weaknesses. In general, I have found it much easier to evaluate players WITH this information than without it.

Explaining Bits and Bobs

All unit in per 90

This means that all the non-percentage stats in this are normalized for 90 minutes played. The reason you do this is to correct for the fact that some players don’t always play 90 minutes. Players that frequently get subbed on or off will inherently look worse if you look at per game stats than per 90 minutes played.

Non-Penalty Goals

Why use non-penalty goals? Because penalties are converted at a 75-78% rate almost regardless of who takes them. They are a different skill to scoring goals that are not penalties (some teams have even had goalkeepers as their lead penalty takers), and so we strip them out of the scoring numbers.

DRAWING penalties is a great skill (and will be added to assist stats over time). Converting penalties is a very common one.

How many shots were on target out of ALL shots that a player has taken. This includes those that were blocked.

Key Passes
Passes that set up a teammate to take a shot. These are highly correlated with assists, which are passes to teammates who score a goal quickly after.

(Note: This is the same stat as Chances Created. Somewhere along the way Opta made Key Passes only mean passes that lead to shots that are NOT goals and CC is all. Which is weird.)

Through Balls
Opta definition: a pass splitting the defence for a team-mate to run on to. Why do we care? These types of passes are generally considered the single type of passes most likely to score a goal.

Scoring Contribution
Combined non-penalty goals and assists per 90 minutes.

PAdj Tackles
PAdj stands for “possession adjusted” stats. The reason why we do this is because it normalizes defensive stats for opportunity. Think about it this way: If your teammates always have the ball, then you can’t make any defensive actions, and you would look worse in this statistic compared to a Tony Pulis-style team that sits deep and constantly defends.

When adjusted for possession, tackles and interception output becomes moderately correlated with shots conceded and goals against, as opposed to having no correlation without the adjustment.

In short, it’s an imperfect adjustment, but much better than not having the adjustment at all.

In the bottom left of every radar is the actual statistical output in numbers for each spoke of the radar. Numbers in green are in the Top 5% of output in that stat for the player population and numbers in red are the Bottom 5%.

Examples for our CFs and targeted CFs


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