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Predicting Goal Scoring Performance – A Discussion

Over the past couple of weeks, Fantasy Football Scout (or at least, the geeky corner of it in which I reside) has been busy discussing the relative merits of chance conversion rate, and other predictive measures of goalscoring performance.

The first article I wrote on this topic highlighted a number of teams who had underperformed last season in terms of goals scored based on their number of chances, in particular Southampton and Manchester United.

These teams generated chance-conversion (CC) rates that were more than one standard deviation below the league mean – yet both had performed at or above the league average in previous seasons.

In looking at how repeatable chance conversion rate is from year-to-year, I found that CC rate in 2015/16 was wholly uncorrelated (R2=0.002) with CC rate in 2016/17.

But this was a small sample size from which to work.

As noted by Deulofail (the first of many members I would like to thank for their input in advancing this discussion), using a running-three year tally of team chance conversion rate, should in theory enable yield better results.

This hypothesis was proven true – over longer periods of time, team level chance conversion rate is somewhat more predictive of future performance. For example, cumulative chance conversion rate from 2013/14 – 2015/16 (a three-season sample) had a correlation coefficient of 0.37 vs data from the 2016/17 season. Whilst far from an absolutely predictive signal, this number is important for people to note in future discussions on this topic moving forward.

The impact of chance quality

One side-conversation that grew from these datasets (thanks here to Green Windmill, Giggs Boson, and Doosra, among others, for their input) related to the types of shots teams were taking. For example, were some sides tactically disposed to take longer-range shots and, if so, did this affect their chance conversion rate on a team level?

To test this, I ran a series of linear regressions and Spearman’s rho calculations to assess whether teams who took the most shots from outside of the box also had lower chance conversion rates as a result. To prevent against single season biases, I collected data across the past four seasons, which are presented below:

Season Correlation coefficient (R2) Spearman’s Rho (ρ)
2016/17 0.1 0.34 (two-tailed p=0.18)
2015/16 0.27 0.63 (p=0.01)
2014/15 0.17 0.25 (p=0.38)
2013/14 0.12 0.23 (p=0.42)

As demonstrated, shot distance on the team-level appears to have a consistent, but relatively small negative relationship on chance conversation rate: as a greater percentage of shots are taken from long-range, chance conversion rate declines, and vice versa.

However, this impact is significantly less than I had initially expected to find – in only one season (2015/16) was the relationship between distance-shooting percentage and chance conversion rate statistically significant to even a conservative p<0.1 threshold. There’s clearly more to this equation than simply shot location alone.

The ‘Big Six’ Effect

A second conversation related to overall team quality. Specifically, did top Premier League sides convert chances at a better rate than others – due either to their generating better-quality chances, or possessing strikers who were more clinical finishers?

To test this, I divided my four-year PL sample into two groups: the “Big Six” (Arsenal, Chelsea, Liverpool, Manchester City, Manchester United, Tottenham) and the eight other sides who have featured in the PL across each of the last 4 years (Crystal Palace, Everton, Southampton, Stoke, Sunderland, Swansea, West Brom, West Ham).

Here are their relative chance conversion rates over the past four seasons:

Season “Big Six” Other sides “Big Six” effect
2016/17 12.5% 10.7% +1.8%
2015/16 11% 10.4% +0.6%
2014/15 11.5% 9.7% +1.8%
2013/14 9.9% 9.5% +0.4%

In each of the past four seasons, the so-called “Big Six” sides have converted chances at a higher level than the rest of the league. However, the extent of this difference has been variable: in 13/14 and 15/16, the two groups were much closer in terms of performance than last season.

This demonstrates that we should recalibrate our expectations for a side’s chance conversion rate, to some degree, based on the quality of the team’s players.

To me, this finding provides yet further evidence in favour of a Manchester United bounceback heading into next season – their 9.1% chance conversion rate looks especially poor in light of these numbers.

Chance conversion rate on the individual level

One significant problem with using team-level data to assess chance conversion rate is the ratio of signal to noise (thanks to Twisted Saltergater in particular for insightful comments on this issue, and interesting data on baseball analytics).

So many potentially obfuscating factors impact upon the ability of a team to create, and eventually to convert, goalscoring chances. Moreover, year-to-year changes are more significant on the level of the team than on the level of an individual player – making future performance more difficult to predict from past results.

There is less statistical noise – though obviously still a significant degree of inexactitude – when analysing the performance of single players over multiple seasons.

First and foremost, how predictable is single-player chance conversion rate from one season to the next? The good news would seem to be that this number is stronger than on a team-level. Considering all FPL players who took attempted at least 50 shots in the Premier League last season, the correlation coefficient between their 2016/17 and 2015/16 performance levels is 0.21 (much more convincing than the 0.002 on the team-level).

If we also include data from the 2014/15 season – i.e. using the average of a player’s preceding two seasons to predict his chance conversion rate in the third – that coefficient increases to 0.31.

In practical terms, this dataset can also help us to identify outliers in terms of player performance. For example, let’s use these numbers to highlight some of the Premier League’s most proficient finishers over the past three seasons. Listed below are the five players whose three-year average plotted more than one standard deviation above the mean performance of the 35 most prolific players over this timeframe.

Player Average shots Average goals Mean CC rate (%)
Diego Costa 85 17 20.6
Harry Kane 127 25 20.3
Jamie Vardy 72 14 18.6
Sadio Mané 68 11 17.4
Sergio Aguero 135 23 17.4

This dataset seems to do a pretty good job of identifying players whom the eye-test would also mark out as being clinical finishers.

The presence of Sadio Mané on that list is very interesting – with a three-year chance conversion rate to match Sergio Aguero, the Senegalese international has shown both consistency and quality in front of goal over an extended period of time. That could be tempting for fantasy managers looking for a goalscoring midfield option heading into next season.

And what about the players who shoot a lot, but whose individual CC rates are more than 1 standard deviation below the mean? Note – Dimitri Payet initially qualified for this list (8.3%), but as he is no longer in the Premier League I have removed him and inserted the next-worst player in his place.

Player Average shots Average goals Mean CC rate (%)
Ross Barkley 78 5 5
Christian Eriksen 110 8 7.4
Phillip Coutinho 107 9 8.1
Dusan Tadic 58 5 8.2
Marko Arnautovic 58 6 9.3

Again, I would argue, these numbers do a good job in highlighting players whose style of play is centered upon low-percentage, long-range efforts on goal.

In fact, one player who was invoked time-and-time again during discussions on this matter was Christian Eriksen – whose chance conversion rate was among the worst of all high-usage players last season. In his enlightening article, Spreadsheet made the point that Eriksen’s chance-conversion rate was due to regress towards the mean this time around. While distinctly possible, I would argue that the numbers suggest otherwise: we now have three successive seasons of data which demonstrate that Eriksen is a low-percentage chance converter. In other words, a low chance conversion rate is already his baseline projected performance.

What Does It All Mean?

One elusive point which I think often gets lost within conversations on statistical projection – whether here or elsewhere – is the practical application of these numbers in the process of decision making. I will be the first to admit that statistical projections are a loose, vague, and imprecise measure of a player’s footballing (and more importantly, to us at least, fantasy) ability. There will always be players who come from left field to impress; just as there will always be players whose sexy underlying numbers will forever flatter to deceive (here’s to you, Dusan Tadic – I’ll see you in my team come Gameweek 1).

Yet there are equally cases where statistical underperformance has enabled fantasy managers to jump early upon some emerging stars: who could forget our statistical crushes on Riyad Mahrez and Sadio Mané heading into 2015/16?

Scepticism of anybody spouting off endless reams of statistical analysis to support or defend a player is healthy.

As Individual and I have often joked, numbers are a very flexible concept. To illustrate this point, and to round out this article, I’d like to offer you a choice:

Player A had an incredible year last season: finishing in the top-10 midfielders in terms of assists and BPS. Furthermore, he almost doubled his goal output from the previous year, a product of generating more goal attempts and big chances than any other season in his career. Still only 21 years of age, and having risen in price by a full 1.0 this time around, this prospect could prove to be a generational cornerstone for both club and country.

For Player B, meanwhile, things aren’t looking so bright. Despite playing in an advanced midfield role, his number of assists and total chances created both fell relative to 2015/16. He averaged fewer touches per minute than any previous year. Worse still, other midfielders around him seem to have picked up the slack: two of his teammates finished in the top 10 midfielders for fantasy points last year. His potential for explosive returns, particularly early in the season, may be muted: despite a high opening price of 8.5 last season, he produced only 1 double-digit return across the first 17 gameweeks. Nor did he end the season well – producing three blanks and only a single bonus point across the last six games.

Player A, as you might have guessed, is rising superstar Dele Alli.

As for Player B? Also Dele Alli.

Numbers can be misleading.

The choice of how much you choose to believe in the power of statistical measures as a means of projecting player performance is ultimately each manager’s personal choice.

There will be many, no doubt, whose minds jump upon reading such analyses to the words of Mark Twain: “there are lies, damn lies, and statistics”. In many cases, such people are probably right. Yet I prefer a different mantra, courtesy of statistician George Box: “all models are wrong – but some models are useful.”

Thank you once again to everybody who has engaged with these discussions over the past couple of weeks. Though I’ve tried to pull together the questions and conversation points that have been most prominently discussed of late, this list is by no means exhaustive or definitive. I’ve enjoyed the discussions immensely – and hope to find myself sifting through tables of data for many months to come!

61 Comments Post a Comment
  1. Jonty
    • Fantasy Football Scout Member
    • Has Moderation Rights
    4 months, 10 days ago

    Thanks for this- another fascinating insight.

    Also we are delighted to say that Prokoptas is joining our team of writers, to pen more detailed statistical analysis - starting with a number crunching review of the Community Shield.

    1. FPL Poker Player
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Brilliant stuff! As someone who's taught themselves how to measure correlation only recently, I loved this article. I might have to rethink my Eriksen selection now though! 🙁

      1. Prokoptas
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Thank you! Eriksen is such an interesting player to me, that I think he and Coutinho are really the poster boys of the chances created vs expected goals argument. The two of them take so many shots that, at first glance, they seem as if they should be unstoppable goalscoring machines - after all, we know that shot number is a critical determinant of goal scoring count. Yet, as we dig into their data further, we can see that they also take some of the lowest-percentage shots (in terms of goalscoring likelihood) of any players.

        I think their example really underscores the importance of analysing player performance data on multiple levels. In the case of Eriksen in particular, I think that this second layer of analysis really confirms a lot of thoughts we would have based on the eye test of his game - that so many of his shots are coming in from long range, and are more speculative punts than gilt-edged chances.

        That said, of course, the primary appeal of Eriksen should never be his goalscoring acumen but the volume of chances he creates for others. With 20 assists last season, there's plenty of reason to fancy Eriksen as a prospect this year - terrible finishing or not!

    2. FC Lackless [BALEGIUM]
      • Fantasy Football Scout Member
      4 months, 10 days ago

      lol, was just about to ask if you'd signed him up yet?!

      1. Prokoptas
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Couldn't be happier to be on board!

        1. FC Lackless [BALEGIUM]
          • Fantasy Football Scout Member
          4 months, 10 days ago

          Lots more great insight judging by your output so far...good luck!

    3. LangerznMash
      4 months, 10 days ago

      Awesome article great work!
      ...how it traslates to our team selections is a bit iffy. Makes me more confident of selecting Mane over Coutinho.

    4. wheredabudat
      4 months, 10 days ago

      Wow, great read

    5. Giggs Boson
      • Fantasy Football Scout Member
      4 months, 7 days ago

      Terrific! Well deserved.

      His articles are incredible.

  2. bojack
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Great article.

  3. QPRUTD - BLINDIAN
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Nice Article. Congrats Prokoptas for becoming a part of FFS Team. Good luck 🙂

  4. André94PT
    • Fantasy Football Scout Member
    4 months, 10 days ago

    What a great article! Congratulations for this amazing work Prokoptas 🙂

  5. versatile
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Great read. I'm interested to know if there are any methods of judging a player's goal scoring performance if they have joined a new team OR are new to the league?

    1. Prokoptas
      • Fantasy Football Scout Member
      4 months, 10 days ago

      That's a really interesting question, and something that I've been toying around with already when building statistical profiles for players like Morata (who has an added degree of difficulty, due to having played so many garbage-time minutes at the end of games). I'd be happy to talk about this in more detail with you if you're interested, but for now here's the tl;dr version -

      1) The number of shots a player takes per game is probably the best first approximation factor of goalscoring potential. It's a simple notion, but you've got to buy a ticket to win.
      2) For players who are moving into new systems, I then look at the statistical profile of the player they were replacing. Where have they been shooting from? Do they have a high proportion of "big chances" within their shot profile? This gives us something of a baseline of their role.
      3) If the data is available (and hopefully, this dataset will continue to grow), a player's xG profile is invaluable. This tells you so much about the nature of chances they are on the end of, and can be used to back out so much interesting data from preferred shot locations to weak foot/aerial ability.

      1. versatile
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Yeah I would be happy to discuss this further. I am just intrigued because someone like Lacazette, who (I think) recorded the highest goal to chance ratio last season, could prove to be an excellent buy this season

        KDB is also an interesting one, particularly as we don't know if he will be playing deeper or further forward.

      2. versatile
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Sorry, to add to this. Is there further difficulty analysing players who are newly promoted to the league?

        1. Prokoptas
          • Fantasy Football Scout Member
          4 months, 10 days ago

          Lacazette is a very interesting case, I think. You're right to note that his chance conversion rate was stellar last year - I had him at 33%, which was higher than any PL striker (Jesus was at 29%). The three previous years, he's been between 18% and 28%, so he's clearly shown an ability to put away chances on a regular basis.

          Obviously, there are three big factors to account for off the bat. The first of these is the quality of the sides he was playing against - I don't have the full defensive metrics for Ligue 1 on hand, but I think we can qualitatively say that he was playing the majority of his games against poorer opposition than he'll face in the PL. That's our regression factor #1.

          Then we look at the team on a macro level. Arsenal had 566 goal attempts last season, which put them sixth in the league. That's pretty good. As a team, they converted 13.6% of these chances - as I wrote in this article, the baseline for the big six last year was 12.5%, so Arsenal's performance was well within our expected range of sustainable outcomes. So that's promising.

          Next, the players who fulfilled the central striking role. Both Sanchez and Giroud were pretty prolific (18.6% and 30.8%, respectively) in front of goal last year (take that Giroud number with a grain of salt, though - there's maybe a Morata effect going on here, in which he has a tendency to play during times when we would naturally expect the most goals to be scored). The role of 'Arsenal striker' therefore has evidence to support its ability to sustain high-volume shot attempts (sixth in the league) with reasonably good efficiency.

          I think he could do well. However, I'd be pretty assured that he's not going to convert 30%+ of his chances next time out. If he can settle into the 15-20% range though, and take enough shots (which our numbers suggest he will, as he's shown form as a high-volume shooter and Arsenal produce a good number of shots) then he could easily finish with 15-20 goals. Interestingly, in-house FFS projections have him around this number too - 21 goals over a 38 game season.

          1. versatile
            • Fantasy Football Scout Member
            4 months, 10 days ago

            Fascinating - on both fronts. The numbers do speak volumes, although I suppose it's near impossible for stats to take form into account. For an example Josh King last year, I don't think many people would have predicted his huge rise in value and stake.

            15-20 goals at 10.5m, I'm not sure that does enough for me. I'm not sure Gayle will even hit 15, if I am honest.

            I am stuck with around 6m for a striker and at the minute am punting on JRod. But with what you're saying, I am tempted to try to find a .5 somewhere to get Gayle in his place, despite rather horrid opening fixtures.

            I'm also not entirely sure that Alli, will have quite the season he had last year, but I hope he proves me wrong.

            1. Prokoptas
              • Fantasy Football Scout Member
              4 months, 10 days ago

              I don't know if such a performance would constitute a disappointment - as a point of reference, here is the full list of players who scored more than 20 goals last season:

              Kane, Lukaku, Sanchez.

              If Lacazette could get somewhere up in the 18-20 range, that would put him up with Costa, Aguero and Alli - the only additional players to even score more than 16. Those guys were invaluable for long periods last season. That being said, Lacazette isn't in my draft right now. But a strong showing this weekend could certainly see him garnering strong consideration.

              As for Gayle - there are some concerns. He may not even be immune to rotation, with rumours swirling about Newcastle adding a new striker. I probably wouldn't recommend him heading into week 1, but rather as a player to keep an eye on and potentially deploy opportunistically. For example, if he starts brightly, his fixtures from weeks 3-6 are WHU, swa, STO, bri. Pretty tempting!

              Mid-priced strikers are a market inefficiency if they run hot - but in the case of most of these players, they are mid-priced for a reason.

              1. versatile
                • Fantasy Football Scout Member
                4 months, 10 days ago

                I think I am going to gamble on JRod, but I will see how the charity shield pans out. Still currently going for Lacazette over Jesus, mainly because I am yet to be convinced by Pep's rotation tactics. Although I have got KDB.

        2. Prokoptas
          • Fantasy Football Scout Member
          4 months, 10 days ago

          And to answer your second question - yes, I think there's definitely an added layer of complexity when dealing with newly-promoted players (or more broadly speaking, any players whose previous experience is not at a top-level club). I always try to bake in both a decline in efficiency and volume when a player makes such a leap. Dwight Gayle, for example, got 23 goals in 32 games last year. I think even the most ardent Newcastle fan would expect that number to come down this year. But even if we subtract 40% of that output, could he be situationally useful for a 6.5 price tag? I'd argue yes.

  6. Taking the Mkhitaryan
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Awesome article. Picked Dele as player A a mile off, genuinely surprised he was player B

    1. Jonty
      • Fantasy Football Scout Member
      • Has Moderation Rights
      4 months, 10 days ago

      I love that drumroll....Ali again! part. 🙂

    2. Prokoptas
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Thank you! It's amazing how numbers can be used to support any argument - and I think that's a point that I really wanted to try and hammer home. We do need to be selective, and sceptical, in order to derive the most value from our analyses. I'm hoping this is a service I'll be able to provide during the Member's articles moving forward!

  7. Hungry Singh
    • Fantasy Football Scout Member
    4 months, 10 days ago

    I enjoyed this very much. Cracking work old chap!

  8. Slindoffer
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Thanks for this Prokoptas. Very insightful and to the point. Setting a high bar for yourself in future articles!

  9. Prokoptas
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Thanks, everybody, for your kind comments! As I mentioned throughout the article, there are a huge number of FFS community members to whom I am grateful for their help and insightful comments - and I hope that these are discussions we can all continue to have moving forward! To piggyback on Jonty's point, I'll be producing a weekly stats column during the season analysing player performance and hoping to identify players who are under- and over- performing their statistical profiles, as well as using the new data (like player heatmaps) that we have available in the Member's Area!

    If anybody has specific questions regarding this article, or our plans going forward, feel free to ask!

    1. versatile
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Great work mate, and good luck!

    2. Boris- Salahmon Islands FTW
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Great read, many thanks

    3. Individual
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Great work 🙂 looking forward to the column 😀

      "30% of the time, it works every time"

  10. Clump
    4 months, 10 days ago

    What a great read. Cheers!

  11. Huddy
    • Fantasy Football Scout Member
    4 months, 10 days ago

    An excellent article. Nice one!

  12. The Architect of Anarchy
    4 months, 10 days ago

    Makes me rethink eriksen's selection

    Thank you for this.

  13. Respect My Authoritah
    • Fantasy Football Scout Member
    4 months, 10 days ago

    The final point there is excellently made. Props 🙂

  14. Rodney
    4 months, 10 days ago

    Great analysis mate

  15. thes7s
    4 months, 10 days ago

    You must be a damn good poker player.

    1. Prokoptas
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Ha, that's an interesting comment! I actually used to play a lot of online poker (it helped to get me through University) - not so much these days though, I'm afraid.

      1. Mozanniepique VC
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Loads of poker pros play FPL

        1. electrue - fashanu zealand
          • Fantasy Football Scout Member
          4 months, 10 days ago

          Too bad we can only speculate on that. Would be interesting to know the number of people playing poker that also play FPL. I think there is a s stronger link between poker and chess and also some strategy based PC games.

          1. RedLightning - January to M…
            • Fantasy Football Scout Member
            • Has Moderation Rights
            4 months, 10 days ago

            There are a number of FPL mini-leagues for chess-players, but I have not yet come across any for poker players.
            Perhaps they prefer to play in cash leagues rather than against other poker pros.

            Chess at normal rates of play, and the old postal chess, are both slower games than poker (although blitz chess isn't), so chess players who like to have plenty of time to consider each move in depth are quite likely to also be attracted to FPL.

            1. electrue - fashanu zealand
              • Fantasy Football Scout Member
              4 months, 10 days ago

              Live poker can be pretty slow but I get your point.
              I guess what makes these games so popular is their accessibility and the notion that everyone can win.

  16. greghammer95 - Matagascar
    4 months, 10 days ago

    Fantastic article and I love your points on trying to relate it back to decision making. Really really good stuff and I stopped eating my lunch as it had me gripped. Probably shows my sadness. To the above points I think FPL players tend to be Poker players and in analytical/mathematical jobs/studies. You could definitely draw the profile of an FPL geek.

    Anyways, here's my feedback besides the fact I think the content is brilliant.

    - The top 5 converters, as you said the eye test pretty much confirms this, would like to see what the top 20 are though as I reckon there'll be some interesting stuff in there!
    - Would be interesting to see how close they're going, so KDB/Pogba in particular despite having a low conversion rate might have quite a high "nearly a goal" rate, so come up with something that combines shots on targets/woodwork hits. Not sure if it'll just be statistical nonsense but might be something in it.
    - Intrigued as to what the data looks like that sits behind this, is it all coming from the members area? If so it'd be great to start using a nice data visualiser tool (For personal use) to start being able to drill into this
    - Question for Jonty if it is coming from the members area (Although I'm not a member currently), is it possible to take raw data from there at all?

    1. Prokoptas
      • Fantasy Football Scout Member
      4 months, 10 days ago

      Hey, there's nothing sad about enjoying a good set of footballing statistics (or at least, this is what I tell myself...)

      To get to each of your points:
      1) If you're interested, I can definitely expand upon this list in one of my future articles. As Jonty said up top, I'll be writing regular features for FFS now, as part of our Technical Area series. Unfortunately, the articles are going to be members-only (but I'll be diving into the good stuff, like our new heatmap feature).
      2) There are a lot of different weighting methods that it is possible to use for analyzing how close a player came to scoring (one popular method of calculating xG, for example, uses the average conversion rate of other players taking similar shots). Accounting for things like woodwork rate sounds like a good idea in theory, but it opens so many other potential problems - for example, what about shots that only just miss the woodwork? What about those two inches further wide again? In general, I'm not a fan of boolean data - I like continuous scales that apply a sliding value of quality to the process, rather than a definitive GOOD/BAD outcome to the result. But it's something I could dig out for you if you're keen.
      3) Yep, all the raw data behind this is available through the Member's Area to the FFS community. However, the final numbers presented here (and obviously, the subsequent statistical tests run upon them) were done externally.
      4) If I can deign to speak on Jonty's behalf - yes, you can export data to the statistical software of your choosing. This is what I do!

      Finally, and most importantly - thank you so much for your generous feedback! Given that I'm going to be writing a lot more for the team going forward, it's good to know that there's an audience out there for these pieces!

      1. greghammer95 - Matagascar
        4 months, 10 days ago

        1) For sure, I'll be becoming a member in due course anyways! So I look forward to them.

        2) Of course there's a million ways you can show/interpret data, for me that seemed like a good way for measuring projected conversion rates, are they hitting the post more than normal? But to your point there though how likely is the shot to go either side of the post rather than hit it.

        As an analyst by trade continuous data is better for any form of analysis BUT only where applicable, with a stat's background (kind of) It's always nicer to have a continuous data set

        Thanks for the other answers! One last question, why have you chosen to use one standard deviation away from the mean and not say 1.5 or 0.5? Obviously depends on how the data is distributed but intrigued as to why? (Not a criticism as it helps make the point! 🙂 )

  17. Doosra - ☭Bolivia Giroud…
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Very good article, Prokoptas. Thank you. 🙂

    One thing missing from this, though, is the player's learning curve. The other thing is the player's innate accuracy. Some are blessed, others are not.

    With this in mind, two players I have marked for advancement this Season, are Coutinho and the aforesaid Eriksen. The reason I have not mentioned All, is because I don't believe that he has the innate accuracy. His results appear to be achieved by means of good positioning.

    Anyway, that's my take on it, before I rush off to the dentist. Let us hope that his innate accuracy is good! 😀

    1. Prokoptas
      • Fantasy Football Scout Member
      4 months, 10 days ago

      I'm rooting for you to be blessed with the Harry Kane of dental surgeons!

      The learning curve point is an interesting one - we certainly would assume that a player's clincality would improve with additional years of experience, but I don't know if I've ever seen a large dataset on it. It would be interesting to look at this, and to quantify what kind of relationship exists between these factors - it's unlikely to be linear, as there's a clear plateau that players approach towards which you would expect to see a diminishing scale of improvement. Sounds like a great idea for a project, Doos...

      Regarding Cout, I'm not sure how much he has to gain from last season. That was (by far) his most efficient shooting season: he actually converted 12% of his chances last year, up from 7% the previous year and 5% before that. If he can hold onto that rate, though, I'd be delighted as he's been in the vast majority of my drafts thus far (and still is right now, actually).

      1. Doosra - ☭Bolivia Giroud…
        • Fantasy Football Scout Member
        4 months, 10 days ago

        Ha! Was a simple cleanup. 😀

        Well, Coutinho had an awful lot of blocked shots, so I can see two lines of improvement: shooting from better positions, and shooting at more fruitful areas - he has the accuracy.

      2. Hot Fuzz *Bolivia Giroud*
        • Fantasy Football Scout Member
        4 months, 10 days ago

        "Prokoptas"........................interesting name.......so your suppose to be a GIANT......murderer, slaughter....make people suffer keep them hostage....... not a nice guy by any stretch...just try to figure out how does it fit with being an amazing annalist for football statistics and create in the same time one of my favorite articles on this page??? well ..... i might not be able to find that out, but wanted to thank you for this incredible piece of yours its amazing.....

  18. jesperdalagersuri
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Great read, thank you very much!

  19. ponsio22
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Wow, brilliant article!! For someone like myself who lacks the flair to make sense of the stats - this is a massive help. Easy to understand, and a gripping read. I'm looking forward to more posts!

  20. Pork Pie Sausage Roll
    • Fantasy Football Scout Member
    4 months, 10 days ago

    This genuinely is one of the best articles ever posted on this site in my approx 10 years of frequenting it. Bravo

  21. KMonst
    4 months, 10 days ago

    For anyone wanting to do a "Dugout FC Fantasy Draft", and wants to play all year (no leaving after 2 games and leaving dead teams) I have created a league.
    Live draft takes place Sunday 6th August at 8pm UK time

    Copy the link and join lets have some drafting fun this year!

    https://dugoutfc.app.link/CwzDJbTnlF

  22. Syntese
    • Fantasy Football Scout Member
    4 months, 10 days ago

    Last year I did some minor work along this line. What I did, was that I looked at how team strength (as measured by ClubElo at the start of the season) was related to the conversion rate of shots inside the box (excluding penalties). In total I looked at 7 seasons, from 09/10 to 15/16, making the number of observations in total 140. Team strength was highly significantly related to conversion rate (t=6.04, p

    1. Syntese
      • Fantasy Football Scout Member
      4 months, 10 days ago

      And I'm sorry to say the rest of what I wrote didn't make it, so I'll try again. Elo was correlated with shots in the box conversion to a moderate degree (r=0.45). On average 13,2 % of these shots were converted, with a 100 Elo increase estimated to increase the conversion rate by 0.9 % (95 % CI, 0.3 %). As an example Chelsea is rated 200 Elo above the league average, and would be expected to roughly convert 15 % of non-penalty shots inside the box.

      Estimated model: Shots inside conversion rate = .0000924*ClubElo -.0269393

  23. FPL Chess
    • Fantasy Football Scout Member
    4 months, 10 days ago

    FPL Chess - { mini-League code 7741-3334 } : 300+ players. Everyone welcome.

    Brilliant article by-the-way. I think I need to do some tweaking...

  24. BOWIE - DZ LEAGUE 97-594
    • Fantasy Football Scout Member
    4 months, 7 days ago

    Great article, It got me thinking about players who do take ranged efforts. Back in the early 2000's Steven Gerrard hit several long range efforts quite frequently, I would say there were several more players who 'had a pop' on a regular basis. Now, as a football lover of fine long range efforts, I did notice the decline in ranged efforts over the past 15 years.

    I put it down to many factors, one being the changing of the ball from a Mitre Ultimax to the newer, Nike Geo design. If you've kicked these balls before you'd know how they travel in the air, In my experience it was far easier to hit a long range effort with a mitre ball or even an adidas ball. I was curious about the Nike ball, so in 2009 I bought the new Nike Geo Merlin, the standardised PL match ball at the time. The ball is very light, probably safer for those concerned with head injuries. Upon striking the ball, the way it reacted was very different. Just trying 'to smash it' resulted in more shots over the bar than normal.

    The second factor I no believe is the most likely regression of long range goals is the modern evolution of the game. It's quite clear players follow similar patterns of play practiced in training, trying to make a likely goalscoring opportunity. The penchant to 'have a go' rests in the player himself, probably breaking protocol by potentially wasting a foray into the final third.

    In conclusion I'd say it's harder to score from range than ever before partially due to the ball, part due to the modern game (where statistics are killing aloof, unpredictability). Players such as Coutinho and Eriksen like having a go, any player that does and is allowed to frequently by their coach is worth considering. If you fail, try again! 🙂