After a short break away from football, numbers and banging my head against the keyboard I am back. My work here at StatsBomb has mainly comprised of all things Premier League forwards and their stats from 2008-13.

Think of this article (and maybe one other) as a wrap-up of all the information I have on Premier league Forwards spanning from 2008 to 2013.

Right now I want to look specifically at the relationships, if there are any, between some of the numbers I have previously looked at. Do shots and shots on target begin to decay as the ToP% increases? How about scoring%? Goals, even?

Let’s find out. This is all about decay as time (players minutes on the pitch) increases.

 

Shots And Shots On Target

 

X axis=time (ToP%) Y axis=Statistic

 

Decay_shots_medium

This chart is shows us the relationship between time (x) and shots and shots on target per90 (y). This is the full sample of players in my database with no outliers removed.

The correlations for shots and ToP% and SoT and ToP% are super weak, almost non-existent. But what we can see is a slight angling of the trend line: Shots increases from ~2.75 to 3.1 as we move from left to right. Shots on target increases from ~1 per90 to ~1.2 per 90 left to right.

As we move upwards in the units of x (Time) the units of y increases slightly. If I had cherry picked the sample and discarded all players who played less than a league average ToP% (44.29%) then the trend lines would be much steeper. Alas, I wanted to use the entire sample.

Reasons for Increase in Shots per90 as ToP% increases?

It’s probably to do with survivor bias. The players that play the most minutes tend to be the best players, the best players tend to be the one’s who generate the most shots and shots on target, hence the slight upward slope of the trend line.

The more minutes a player plays may be a rough proxy for talent, manager trust and an ability to stay healthy. The trend line indicates -ever so slightly in this full sample of players – that the more a player plays (talent?) the more shots and shots on target he registers.

Scoring%

 

Decay_sc__medium

 

Now we move onto Scoring% (goals/shots on target) with ToP%. From left to right we see the trend line is decreasing ever so slightly from 35% to 31%.

Reasons why Scoring% decreases?

I’d love to hear some reader comments on this. I’d probably need some more time to think about it, but a rough guess would probably look like this: The more minutes (ToP%) a player plays, the more raw shots on target he records. The more shots on target a player has the more likely it is that variance will wash out and his scoring% will regress toward the mean.

Random Thoughts

* Colin Trainor posted some excellent articles here on StatsBomb which looked at shot locations and shot placement maps (where on the goals frame the shot would have crossed the goal line) which questioned, if I understood it correctly, whether we need to sort shots on target by quality. As I was making this chart today some interesting information cropped up: Why does a player post such different scoring% numbers each year?

Now, some players, like Messi and RvP are pretty consistent in terms of scoring%, this may be due to their shot locations and shot placements. But they are the exceptions, nearly every other player has their scoring% vary somewhat. This could well be down to shot location and placement as Colin stated.

But what if a players location/placement varies year to year? Does this mean that the popular train of thought that a strikers main skill, that of shot location/placement, is non-repeatable and that there are other factors involved that influence a strikers shot location?

If a players shots location/placement is stable year to year then why does the player suffer the dips and spikes in scoring%. If player X shoots from the same location, why doesn’t he score as much? Does variance, non-skill factors, defensive pressure, goalkeeper position play a bigger role in a players season scoring% than just static shot location? If it does, it would go a long way in helping explain the variance in season-to-season scoring% and level of regression involved in scoring%.

I have highlighted a couple of names on the chart above: Adebayor and Berbatov.

Adebayor posted consecutive scoring% seasons of ~13%, 35% and 58%.

Berbatov posted scoring% seasons of 35%, 72% (tiny sample), 47% and 35%.

Are these numbers due to the lack of repeatability of locations/placements or are these two players shooting from the same locations and merely suffering through variance/bad or good luck? Or is there something we are not currently capturing?

I guess what is part of the fun and debate, which is always friendly and aimed at trying to figure out what the hell is going on, is to discover just what drives stats like scoring%. What is the constituent make-up of scoring%, it’s repeatability et cetera. This is why myself and Ted created this site.

Any thoughts, comment away.

 

Goals Per90

 

Decay_goals_medium

 

This is goals per90 with ToP%.

Again we see a weak correlation, but a slight decline in the trend line which indicates that as x increases y decreases ever so slightly. I highlighted some of the best goal scoring performances of the last years in the top right hand side of this chart. Familiar names.

I think it is pretty clear why goals per90 decreases over time, it is scoring% driven.

The bottom left side of this chart is really cool. It shows the groupings of below league average ToP% players and the rate at which they score goals per90. Seems to be six or seven different bands of players featured in the circled area and each group has it’s own talent level curve for goals per90.

I checked the data before posting and it seems sound, but my those curves are mighty intriguing.

 

  • Toshack

    Ben,
    Thanks for that! There’s been a discussion based on Colin’s piece(s) where Chris from Portland has suggested we need to look at the other 10 players in the striker’s team and even the opposing 11 players (my interpretation).
    Let’s assume that the striker’s skill is the same from year to year (which it isn’t of course, but the shot placement ability shouldn’t vary too much one would assume). Then would Adebayor’s up’s and downs’ in part depend on the overall performance (top table, mid table or bottom table) of the team he played for that year, the service he got, the system his team played that year etc?
    I have no idea, but something else that his own basic skills could affect the outcome – at least that is what Chris is advocating (my interpretation)
    I’m sure he will comment “in person” soon 🙂

    • http://BenPugsley Ben Pugsley

      Yeah, that is a good point….basically QualCompetition and Quality of team-mate. Tricky to factor in tho, and a huge task, I imagine.

      Adebayor, for example had different minutes played in each season….but in those seasons he played at City (3rd) Spurs (4th) and Spurs (5th) I think, may have to go back and check. He played in good teams, who did well, and his minutes varied across each season.

      I think the debate on how strikers score will be a debate that goes on for some time. The luck, non-skill, location, placement was solved in hockey, but it took time.

      • Toshack

        Cheers Ben,
        And yes, ”huge task” and ”take time” seems to an appropriate assumption… 🙂
        //Peter

      • Toshack

        Btw Ben,

        I have to say what Ted and you have accomplished in a short while with this site is just amazing. As much as I really like the TTT site, it sometimes feel a bit Liverpool fixated (naturally, I guess).

        On this site you still get a lot of PL (and Liverpool), but so much more which I as a general sports fan like. And the quality, the quality is simply excellent.

        Keep it coming :-).

        • http://BenPugsley Ben Pugsley

          Peter, thank you for the kind words. We both arrived at a certain point whereby we wanted to write about a wide range of subjects and teams and our then current sites kinda prevented it.

          Expect a lot of fun stuff once the season starts. The Summer is usually the quiet time for this type of analysis!

    • http://blogs.columbian.com/portland-timbers/ Chris Gluck

      Hehee — just read the article 🙂 Aye…

      Ben, your closing speaks to me like Great Gig in the Sky by Pink Floyd! 😉 Completely and utterly and nonviolently agree that the concept about the players who surround the strikers directly influences the outcome of not only the goals scored by the striker but the overall results in the league table. – That is, after all, my basic premise going into my initial research this year 🙂

      I’m really chuffed to have found this site! I have some thoughts to offer but will defer to others for now…

  • mike

    Players with low ToP% more likely to be a frequent sub and so might play a higher % of their minutes at game states with a higher conversion %.

    • http://BenPugsley Ben Pugsley

      possible, but a hideous amount of work involved to test it over 1/2 million minutes played.

  • http://blogs.columbian.com/portland-timbers/ Chris Gluck

    For me the shots and shots on target will increase as the game goes on given a score-line that is not nil-nil, one-one, ect… as it represents the intent of all teams to try and get an equalizer at least… I would also offer – you may have already done this – the removal of all ‘cup games’ from this as the pretext for winning those versus a draw is different. Another relevant variable might be the score-line – from what I have seen ‘quantity increases as the scoreline gets worse’ – but that does not mean ‘quality increases’ as the scoreline gets worse… Perhaps? another consideration is total minutes played versus per 90 minutes… I used that approach awhile ago to debunk the Castrol Index 😉

    • http://BenPugsley Ben Pugsley

      Hey Chris, cheers for the comments and glad you liked it. As for your Q’s I’ll run ’em down!

      This data is league only.
      Every game is rated as 94mins, all player #’s are reformatted per90 mins.
      I found a link and I cannot find it now, but it had shots broken down per 10 minute section, biggest spike was 60-70 iirc, after that it cooled as teams settled, on average, for their current game position. Winning teams tend to play in a certain way toward the end of the game that restricts shot volume both for and against.
      That restriction may well reduce quality which has a slight effect on SoT/Total shots but as seen in Chart 1, the big ToP% players see shots rate and SoT rates increase as their ToP increases.

      In short, I love reader feedback…..I love to hear other ideas and theories. It helps everyone. Should of seen it when I first floated the Game State idea……….silence!

  • http://blogs.columbian.com/portland-timbers/ Chris Gluck

    Ben,
    I won’t have time to do stats on the EPL this year with my involvement in the Timbers but I will get the chance to watch every single EPL game on telly in the States – so am looking forward to what you guys offer.

    In considering the above topic – did you consider weaving-in the number of ‘offside’ calls those strikers have had called against them (an individual statistic) to see what (positive/negative) influence that may have on the overall numbers?

    The reason I ask is that, for me, an ‘offside’ call stops play and possession changes – thereby eliminating a ‘potential future shot taken’ associated with that possession…

    Anyhow – appreciate you running down my questions – for me in what I have seen here, in the short time i’ve researched MLS, the number of penetrations into the red-zone (attacking third), creation of goal scoring opportunities, (failed and successful assists) (Those are my two separately collected statistics not tracked by anyone that I know of and I refuse to use OPTA for personal reasons) and shot taken rate significantly increases in the final 15 minutes for most teams who have been trailing Portland – the timbers have just 2 losses to go with 8 wins and 10 draws.

    I too have seen a spike between the 45 and 60 minute mark (I track by 15 minute increments as opposed to 10 minutes but understand the pace of the game is much higher in EPL than MLS)… On average, it appears to me, in the MLS, the first 15 minutes are the least productive and I put that down to teams trying to get a feel for each other.

    I’d greatly appreciate you emailing me separately chrisgluck303@gmail.com where we could talk off-line…
    All the best Ben,
    Chris

  • Aliet
    • http://BenPugsley Ben Pugsley

      You lost me at the slideshow!

  • P

    Fatigue? More time spent on the pitch the more tired a player is, less accurate they are, less powerful their shots are, etc…

  • marlon

    This is obviously a bit late, but I figured out what the curves are. Each curve represents a different number of goals scored. Presumably the lowest curve is full of players who only scored 1 goal and the next 2 goals etc.

    Seems like you get these curves when the values in each axis are linked – in this case time.

    • http://blogs.columbian.com/portland-timbers/ Chris Gluck

      To further the discussion on this one… As mentioned above I have been working on the ‘team’ aspect as opposed to individual aspect of the game and here’s some interesting info for consideration…

      I have been tracking six separate categories…
      1) Possession with Purpose (Entire Pitch)
      2) Possession with Purpose (Final Third)
      3) Dispossession with Purpose (Entire Pitch) Defending
      4) Dispossession with Purpose (Final Third)
      5) Goals For
      6) Goals Against

      Out of those six team statistics nine out of 19 teams in MLS have “Goals For” as having the highest correlation to Points in the League Table… in other words 10 others teams show correlation where their points in the league table have more relevance to one of the other 6 categories… It is interesting that the team with the highest correlation of Goals For to Points is Chivas USA, one of the worst teams in MLS; followed closely by Houston and Chicago (two other teams out of the ‘playoff’ picture at this time. Seattle, Vancouver, Columbus, New England, San Jose, New York and Colorado round out the remaining nine.

      Note that Real Salt Lake, Montreal, Sporting KC, LA Galaxy and Portland (other playoff ‘contenders’) have one of the other six as having a higher correlation to points in the league table…

      Real Salt Lake, the leader this year in points and pretty much favorite to take the Cup as well as the Supporters Shield and most probably the league championship have “Goals Against” as having the highest correlation to points in the league table… in other words it’s not who is scoring that is getting them the points as much as who they are preventing from scoring…

      LA Galaxy, another front runner this year as Dispossession within the Final Third as having the highest correlation to points in the league table. In other words when the LA Galaxy do a great job of preventing the opponent from penetrating and taking shots they usually get points…

      Portland Timbers – a known possession based team – have Possession with Purpose (Entire Pitch) as having the highest correlation to points in the league table… in other words when Portland possess the ball (with purpose) across the entire pitch, more than their opponent, they are more likely to get points in the league table…

      So for me at least it is VERY clear that just having goal scorers who score goals is NOT the answer to success for every team.

      In going back to the top strikers in MLS at this point it should be noted that Di Vaio (Montreal) plays on a team where Possession with Purpose (Final Third) has the highest correlation to points in the league table… Sanvezzo is next up and PWPFT is third highest in Correlation, Magee has PWPFT as second highest correlation, LA (3rd highest), Saborio (3rd highest)

      bottom line here is that 8 out of the top ten strikers in MLS play for teams where PWP Final Third has at least the third highest team correlation to points in the league table.

      in closing – here’s what i would offer; if DiVaio plays for Chivas he would score fewer goals than he would playing with Montreal…

      And the two strikers in the top 10 that aren’t playing for a possession based team are playing with Philadelphia ( a team noted for playing direct attacking football) a team that is 14th out of 19th in passing completion accuracy across the entire pitch…

      I will be offering up an article a bit later on this when the season ends but wanted to throw this out their to generate some thoughts/feedback…

      As always – love this site and appreciate you guys allowing me to contribute thoughts to your well written and researched topics…