Follow-up analysis: Final third passing and Goals scored per game

This is a follow up to my post regarding the strong correlation between completed in the final third and goals scored.


Is there a correlation between the final third completions & goals scored at the game level?


I investigated to see if this correlation exists at the game level using the #MCFCAnalytics data set. I plotted the completions in the final third vs. goals scored for Manchester City in all their 38 games of English Premier League.
Blue = Away
; Orange = Home

Manchester City Goals vs. Pass completions in the final 3rd on a per game basis


  • Linear regression had an R2 of 0.04  implying that there is no correlation between passes completed in the final third and goals scored at the game level.
    I did the plot for a few other teams and got similar results.
  • Arsenal – Away and Liverpool – Home. In both cases, Manchester City had very little success completing passes in the final 3rd. However, they lost 1-0 at the Emirates and won 3-0 at home vs. Liverpool.
    Against Liverpool, City had 6 shots on target and 2 off target.
    Against Arsenal, City had 0 shots on target and 3 off target.
  • QPR – Home and QPR – Away. City scored 3 goals each against QPR home and away. However, they had a season high 326 completed passes in the final 3rd at home vs. just 74 in the away fixture.
    Shots vs. QPR Away – 5 on target & 10 off target.
    Shots vs. QPR Home – 15 on target and 10 off target.

The City – QPR fixture was that crazy season finale. City fell behind and they threw everyone forward to go for the win and the Premier league title. QPR was a man down from 55th minute and they defended at the edge of their 18-yard box for most of 2nd half. This explains the unusually high number of completed passes in the final third.

The above examples underline the rarity of the “goal” event. In any given game, there could be factors like bad shooting, luck, the opponent’s goalkeeper having a great game etc., which could influence the # of goals scored. However, over a season those things seem to even out.

In the next step of analysis I will add a 2nd variable to the model and analyze.

Leave a comment


  1. Hi Ravi,
    firstly, thanks for highlighting a couple of my posts recently. I’ll return the favour, honestly 🙂
    Also excellent spot re pivot tables, I’d been using subtotals. Your solution was much quicker and much more useful !

    You may find more correlation between final 3rd passes and success if you look at final 3rd pass differential between the teams and individual match result. Based on last year’s data and from the perspective of the home team, if you made 100 more successful final 3rd passes than your opponent in the game, your chances of winning that game was around 57%.
    75 more = 54%
    50 more = 50%
    20 more = 46%
    level = 43%
    30 less = 39%
    80 less = 32%
    100 less = 29%
    130 less = 26%

    Agree with your points about the relative scarcity of goals. Also while most of the more expensively assembled teams use final 3rd pass completions as a means to impose their superiority on others, some lesser lights take a different approach. Stoke don’t really care too much about completions in the final 3rd (although that may change now that Delap is no longer a major factor), they get the ball into the area as quickly as possible and then don’t mind defending in numbers in their own last third. So playing style partly dictates final 3rd stats, Although the Stoke way is in the minority in the EPL.

    Game position’s another variable to consider. A rare occasion last year when Stoke actually out passed a team in the final third was in the home game with Newcastle. The visitors were comfortably ahead from the 12th minute, so they didn’t mind giving Stoke possession and defending deep. They out Stoked Stoke and won 3-1.

    Good stuff, keep it coming.


    • Ravi Ramineni

       /  September 13, 2012

      Thanks for the great feedback Mark. This comment got tucked away in SPAM so I didnt see it earlier.
      Your point on the differentials is spot on and a great point about Stoke! Oh and I hope I wasnt too harsh on your Stoke in the opposition analysis 🙂

  2. Martin

     /  September 5, 2012

    What result did you expect to find before you did this work?
    That r2 looks about right to me, given how much information we know is missing from the model.
    I think if we look at the significance of the cofficient in a larger sample we would find the significance you are looking for.

    • Ravi Ramineni

       /  September 6, 2012

      Thanks for the feedback Martin. Yes, I am aware that a lot of info is missing. Next post, i will try to address the sample issue. Keep the feedback coming

  3. wayneknight

     /  September 7, 2012

    Hi ravi

    I have come across quite a few of your blogs. do u use any tools to come up with the conclusions? i am interested in working on such stuff,if u don’t mind,can u tell me how do u integrate analytics into football?

  4. As the match entered the 90th minute, second-place Man United had previously held onto win their final game, and Man City was shockingly down 2-1 thanks to two second-half QPR goals. But rather of wilting, Man City scored two incredible goals in five minutes to claim the best position.

  5. I didn’t know soccer was so complicated. I thought you just kick the ball and score a grow.

  1. Final 3rd analysis – more follow ups #MCFCAnalytics « Analyse Football
  2. MCFC Analytics – summary of blog posts # 2 « Analyse Football

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