Interesting Stats shit (updated) (1 Viewer)

[Fergusons_Beard]

If you into this (and it DOES tell a story of our season so far) this set of graphs really quite an interesting read from https://experimental361.com/2019/02/04/scatter-graphics-league-1-4-feb-2019/

Shot dominance
First of all, here is how the number of shots taken by each club compares with those they face in return. The average number of shots taken per match is on the horizontal and the average number faced is on the vertical, so bottom right (take plenty, allow few in return) is good while top left (take few, allow plenty) is bad. The stripes are like contours: the greener the stripe, the better the performance (and vice versa for red).

Attacking effectiveness
Now let’s look at attacking alone. The horizontal axis stays the same as in the graphic above, but now the vertical shows the average number of shots needed to score each league goal. Therefore bottom right is good (taking lots of shots and needing fewer efforts to convert) and top left is bad:

Defensive effectiveness
Next let’s look at the defensive situation – basically take the above chart and replace the word “taken” for “faced” on both axes. Now top left is good – facing fewer shots and able to soak up more per goal conceded – and bottom right is bad:

Expected goals
Finally here’s an attempt at correcting the first graphic for the quality of chances created and allowed, using the same “expected goals” values that power my shot timelines (explained here). The reason for doing this is that the results tend to correlate more strongly with performance than when we treat all shots equally:

Opinions?


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[Nick]

I really dont get the expected goals thing.

The other week it said Bright had more expected goals than Chaplin in a game where Chaplin missed a couple of sitters and Bright didn't get any chances.

 

[Fergusons_Beard]

This is Burge’s saving stats too.
Based on GAA-goals saved above average which in essence is difference between xG (Expected Goals on target) faced and goals conceded.

Naturally the better the difference from xG faced to actual goals conceded the more potential "goals" a GK is stopping from going in.


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[rob9872]

Ha - didn't know anyone else saw these. My mate who I used to play poker with does this stuff for a living and he posted these on Twitter over the weekend. I commented that it just shows we're massively under-achieving.

 

[Fergusons_Beard]

A simple way to think about the Expected Goals value is as the number of goals a team “deserved” to score, if we lived in a world where all players were equally skilful and we had perfect information about the shot.

These are obviously both massive over-simplifications. While skill doesn’t vary massively between players in the same division (particularly in lower league where the better players are likely to be promoted or poached) there isn’t any data on defensive positioning or how the ball was delivered at this level. However I have to work with what I can get and to me this still feels intuitively superior to merely counting shots.

The differences between the actual and expected goals scored and conceded by a club in a given match can be explained by three non-exclusive reasons:

They were lucky (or unlucky)
They were playing against an unusually weak (or strong) opponent
They genuinely performed more (or less) effectively than the average club.


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[Fergusons_Beard]

Ha - didn't know anyone else saw these. My mate who I used to play poker with does this stuff for a living and he posted these on Twitter over the weekend. I commented that it just shows we're massively under-achieving.

Your mate a talented bloke Rob. His website genius and where football is growing massively.


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[Fergusons_Beard]

I really dont get the expected goals thing.

The other week it said Bright had more expected goals than Chaplin in a game where Chaplin missed a couple of sitters and Bright didn't get any chances.

See posted explanation Nick.

Fuller explanation here https://experimental361.com/explanations/match-timelines/

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[ajsccfc]

I can't remember if it's the same guy who does these charts, but there are individual match graphics after each game that show the likelihood of a team scoring throughout and our line is nearly always above the team that ends up beating us or taking points. Energetically wasteful is a lovely summary of our season so far.

 

[Fergusons_Beard]

Look at where Rochdale are in the defensive chart -‘Pushovers’!

Here comes City for the first clean sheet of the season....


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[Ashdown]

If you into this (and it DOES tell a story of our season so far) this set of graphs really quite an interesting read from https://experimental361.com/2019/02/04/scatter-graphics-league-1-4-feb-2019/

Shot dominance
First of all, here is how the number of shots taken by each club compares with those they face in return. The average number of shots taken per match is on the horizontal and the average number faced is on the vertical, so bottom right (take plenty, allow few in return) is good while top left (take few, allow plenty) is bad. The stripes are like contours: the greener the stripe, the better the performance (and vice versa for red).

Attacking effectiveness
Now let’s look at attacking alone. The horizontal axis stays the same as in the graphic above, but now the vertical shows the average number of shots needed to score each league goal. Therefore bottom right is good (taking lots of shots and needing fewer efforts to convert) and top left is bad:

Defensive effectiveness
Next let’s look at the defensive situation – basically take the above chart and replace the word “taken” for “faced” on both axes. Now top left is good – facing fewer shots and able to soak up more per goal conceded – and bottom right is bad:

Expected goals
Finally here’s an attempt at correcting the first graphic for the quality of chances created and allowed, using the same “expected goals” values that power my shot timelines (explained here). The reason for doing this is that the results tend to correlate more strongly with performance than when we treat all shots equally:

Opinions?


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Is it half term in Sheffield ?

 

[rob9872]

Your mate a talented bloke Rob. His website genius and where football is growing massively.


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Decent footballer too, had dodgy knees and so started playing in goal (made it to decent Non league level at Bury St Edmunds). James Scowcroft's cousin too if you remember him from his stint with us (ex Ipswich)

 

[Fergusons_Beard]

Is it half term in Sheffield ?

Nah nowhere near! Btw coming to the conclusion you a jinx-you been to too many shite City games this year!


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[shmmeee]

Love this shit. With Nick on not fully understanding xG (even after reading the explanation - in fact I thought I did understand it until I read the explanation )

Keep it up.

 

[Nick]

A simple way to think about the Expected Goals value is as the number of goals a team “deserved” to score, if we lived in a world where all players were equally skilful and we had perfect information about the shot.

These are obviously both massive over-simplifications. While skill doesn’t vary massively between players in the same division (particularly in lower league where the better players are likely to be promoted or poached) there isn’t any data on defensive positioning or how the ball was delivered at this level. However I have to work with what I can get and to me this still feels intuitively superior to merely counting shots.

The differences between the actual and expected goals scored and conceded by a club in a given match can be explained by three non-exclusive reasons:

They were lucky (or unlucky)
They were playing against an unusually weak (or strong) opponent
They genuinely performed more (or less) effectively than the average club.


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Yeah but in reality what is it based on?

For example in a match why would Bright have a higher expected goal than Chaplin after Chaplin had a couple of chances one on one with the keeper? What about if our most skillfull player only got 10 minutes and had no chances but a less skillfull player missed 10 sitters over 90 minutes. Would that mean the more skillfull player has a higher expected goals?

I can understand guessing before the game but afterwards when it has actually happened surely it's easier to be more accurate?

 

[fernandopartridge]

Yeah but in reality what is it based on?

For example in a match why would Bright have a higher expected goal than Chaplin after Chaplin had a couple of chances one on one with the keeper? What about if our most skillfull player only got 10 minutes and had no chances but a less skillfull player missed 10 sitters over 90 minutes. Would that mean the more skillfull player has a higher expected goals?

I can understand guessing before the game but afterwards when it has actually happened surely it's easier to be more accurate?

xG seems to me like a statisical basis for assertions like "We were all over them"

 

[Fergusons_Beard]

Yeah but in reality what is it based on?

For example in a match why would Bright have a higher expected goal than Chaplin after Chaplin had a couple of chances one on one with the keeper? What about if our most skillfull player only got 10 minutes and had no chances but a less skillfull player missed 10 sitters over 90 minutes. Would that mean the more skillfull player has a higher expected goals?

I can understand guessing before the game but afterwards when it has actually happened surely it's easier to be more accurate?

In general before a player takes a shot, the situation is analysed and compared to hundreds of other situations in the past of football played at similar level. So if a tap in with no one nearby is scored 99.3% of the time so the xG for that chance is 0.993. A difficult 1-on-1 with a defender putting pressure may be converted 70% of the time, so the xG for that situation is 0.7. A long range attempt from a particular spot maybe works 5% of the time, so the xG is 0.05

So in theory Chaplin has scored from harder chances so therefore his expected goals will be higher.

Clear as mud?


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[GaryJones]

If you into this (and it DOES tell a story of our season so far) this set of graphs really quite an interesting read from https://experimental361.com/2019/02/04/scatter-graphics-league-1-4-feb-2019/

Shot dominance
First of all, here is how the number of shots taken by each club compares with those they face in return. The average number of shots taken per match is on the horizontal and the average number faced is on the vertical, so bottom right (take plenty, allow few in return) is good while top left (take few, allow plenty) is bad. The stripes are like contours: the greener the stripe, the better the performance (and vice versa for red).

Attacking effectiveness
Now let’s look at attacking alone. The horizontal axis stays the same as in the graphic above, but now the vertical shows the average number of shots needed to score each league goal. Therefore bottom right is good (taking lots of shots and needing fewer efforts to convert) and top left is bad:

Defensive effectiveness
Next let’s look at the defensive situation – basically take the above chart and replace the word “taken” for “faced” on both axes. Now top left is good – facing fewer shots and able to soak up more per goal conceded – and bottom right is bad:

Expected goals
Finally here’s an attempt at correcting the first graphic for the quality of chances created and allowed, using the same “expected goals” values that power my shot timelines (explained here). The reason for doing this is that the results tend to correlate more strongly with performance than when we treat all shots equally:

Opinions?


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FOOKING HELL its like a really shit Spot the Ball Competition entry!

 

[Johhny Blue]

We will win if we score more goals than Rochdale

 

[Nick]

In general before a player takes a shot, the situation is analysed and compared to hundreds of other situations in the past of football played at similar level. So if a tap in with no one nearby is scored 99.3% of the time so the xG for that chance is 0.993. A difficult 1-on-1 with a defender putting pressure may be converted 70% of the time, so the xG for that situation is 0.7. A long range attempt from a particular spot maybe works 5% of the time, so the xG is 0.05

So in theory Chaplin has scored from harder chances so therefore his expected goals will be higher.

Clear as mud?


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Yeah but the Plymouth match. Chaplin missed easy chances and Bright didn't even get a chance let alone a tap in.

How was Chaplin's expected goals lower?

I can only comment because I watched the game, does somebody doing the stats watch every game to see how good the chances were?

 

[Sky_Blue_Dreamer]

I agree with Nick.

I can understand how before a game xG could be useful in a bookies type situation but after a game it's irrelvant - the expected number of goals in that game after the match is how many you ended up scoring.

For me, xG is only useful if you plot it against actual goals - because then it shows how many you SHOULD be scoring and how many you ARE scoring. Looking at the xG graph that just emphasises the point of how poor we are at converting chances because our actual goal tally is much, much lower than expected.

Overall, it looks like we've got an average defence and a wasteful attack. Which is how I think most people on here would describe us.

 

[Londonccfcfan]

Attacking effectiveness is interesting.

Clearly see the correlation shots taken per goal/shots per match. The top 8/9 teams ie the teams with most effective/clinical strikers are.

Interesting how Fleetwood who don’t take many shots per match on average score highly.
Not surprising with Madden and Evans.

 

[Calista]

I love the terminology. Our attack is stuck about half way between "Ineffectual" and "Energetically wasteful" - sounds spot on to me!

If Hiwula was supposed to be part of a front 3 on Saturday, he must really be dreading the day he's asked to play up front on his own.

 

[Brighton Sky Blue]

Made a CCFC version:

 

[Johhny Blue]

I agree with Nick.

I can understand how before a game xG could be useful in a bookies type situation but after a game it's irrelvant - the expected number of goals in that game after the match is how many you ended up scoring.

For me, xG is only useful if you plot it against actual goals - because then it shows how many you SHOULD be scoring and how many you ARE scoring. Looking at the xG graph that just emphasises the point of how poor we are at converting chances because our actual goal tally is much, much lower than expected.

Overall, it looks like we've got an average defence and a wasteful attack. Which is how I think most people on here would describe us.

So it works?

 

[Philosoraptor]

So it works?

N'ah, I would assume it's like measuring how far your car has travelled by the amount of petrol you have put in the tank and waiting for the gauge to get near empty knowing that the last few times you have done this the mileometer has said you have travelled this far.

Rather then just looking at the mileometer for your distance.

Still waiting on people to get out there protractors and rulers and do this properly.

It's just not accurate enough.

What I would assume people are after is something not a million miles away from this.

 

[Gazolba]

It's no surprise that the top few teams are doing well in every category and the bottom few teams are doing poorly.
Makes you wonder why we do well against the top teams and poorly against the bottom teams.
I always believe in the old investing adage: Past performance is no guarantee of future results.
But it's about all you have to go on other than rumour, innuendo and pure guesswork.

 

[Sky Blue Harry H]

Duncan Alexander

Aymeric Laporte now has as many PL goals as Vincenzo Montella and Youssef Chippo


20:37 - 6 Feb 2019
Twitter Ads information and privacy
See Duncan Alexander's other Tweets

From twitter - Man City game - loved Chippo and Hadji !!!

 

[Sky_Blue_Dreamer]

So it works?

Some of those graphs do, because they use actual not expected data.

The last one using expected goals for and expected goals against has us performing much better than we actually are. It only has any worth if you then compare it against actual goals for/against.

1.19 actual goals against per game (1.38ish xGA)
1.03 actual goals for per game (1.53ish xG)

Which shows that the defence is actually performing slightly better than expected, but the attack is way short of what it should be doing.

 

[shmmeee]

Some of those graphs do, because they use actual not expected data.

The last one using expected goals for and expected goals against has us performing much better than we actually are. It only has any worth if you then compare it against actual goals for/against.

1.19 actual goals against per game (1.38ish xGA)
1.03 actual goals for per game (1.53ish xG)

Which shows that the defence is actually performing slightly better than expected, but the attack is way short of what it should be doing.

What’s the average error? Is everyone skewed the same way?

 

[djr8369]

So does this indicate whether we are not clinical enough or if it’s that we’re not creating enough clear cut chances? (If that makes sense) Or is it a bit of both?

What I’m asking is does the data tell us where we’re going wrong.


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[SkyBlueJord]

So does this indicate whether we are not clinical enough or if it’s that we’re not creating enough clear cut chances? (If that makes sense) Or is it a bit of both?

What I’m asking is does the data tell us where we’re going wrong.


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It tells us exactly what we already know, creating a lot, and not scoring enough. Predicts that we should be scoring a lot more than we are (given our chances created).

 

[djr8369]

It tells us exactly what we already know, creating a lot, and not scoring enough. Predicts that we should be scoring a lot more than we are (given our chances created).

Yeah I realise that I’m just wondering if the data can provide an insight to the specifics and what could be done to remedy it (apart from shooting practice).

Regarding training I keep thinking the team need to do practice in front of an empty net just to get used to scoring. Seem to recall you sometimes hear coaches talk about doing things as basic as that to get over the mental issues and stop players trying to create the perfect opening.


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[Sky_Blue_Dreamer]

What’s the average error? Is everyone skewed the same way?

Put together these tables (sorry for the alignment - no idea how to do tables on here)

Goals against (teams at top of list concede less than expected i.e. are doing better than expected defensively)

Team aGA xGA Diff
Sunderland 0.93 1.40 0.47
Blackpool 0.93 1.28 0.35
Charlton 1.03 1.38 0.35
Accrington 1.29 1.59 0.30
Peterboro 1.32 1.58 0.26
Luton 0.87 1.09 0.22
Gillingham 1.63 1.83 0.20
Coventry 1.19 1.39 0.20
Fleetwood 1.10 1.28 0.18
Portsmouth 1.03 1.19 0.16
Barnsley 0.87 1.01 0.14
Plymouth 1.68 1.81 0.13
Walsall 1.57 1.69 0.12
Bradford 1.65 1.76 0.11
Burton 1.30 1.40 0.10
Doncaster 1.31 1.39 0.08
Bristol R 1.10 1.16 0.06
Wycombe 1.35 1.39 0.04
Southend 1.23 1.24 0.01
Scunthorpe 1.81 1.77 -0.04
Shrewsbury 1.40 1.20 -0.20
Wimbledon 1.53 1.25 -0.28
Rochdale 2.00 1.61 -0.39
Oxford 1.53 1.12 -0.41

Average difference 0.09

Goals for (Teams at top of list scoring more than expected i.e. doing better than expected offensively)
Team aG xG Diff
Sunderland 1.75 1.31 0.44
Luton 1.97 1.71 0.26
Doncaster 1.79 1.54 0.25
Peterboro 1.58 1.37 0.21
Fleetwood 1.35 1.16 0.19
Southend 1.30 1.21 0.09
Barnsley 1.77 1.71 0.06
Wycombe 1.32 1.29 0.03
Scunthorpe 1.23 1.20 0.03
Portsmouth 1.67 1.65 0.02
Gillingham 1.33 1.35 -0.02
Oxford 1.23 1.26 -0.03
Charlton 1.52 1.58 -0.06
Plymouth 1.26 1.37 -0.11
Walsall 1.13 1.32 -0.19
Blackpool 1.07 1.28 -0.21
Rochdale 1.23 1.46 -0.23
Bradford 1.16 1.42 -0.26
Shrewsbury 1.07 1.35 -0.28
Burton 1.30 1.63 -0.33
Bristol R 0.97 1.39 -0.42
Wimbledon 0.73 1.17 -0.44
Coventry 1.03 1.53 -0.50
Accrington 0.96 1.47 -0.51

Average difference -0.08

Given the average error of each, it shows that we're defending better than is expected of us 9even taking in account the average margin for error) but attacking wise we're scoring way less than can be expected (even taking into account average margin for error).

In terms of scoring only Accrington are on a similar level of underperformance.

 

[Mucca Mad Boys]

So does this indicate whether we are not clinical enough or if it’s that we’re not creating enough clear cut chances? (If that makes sense) Or is it a bit of both?

What I’m asking is does the data tell us where we’re going wrong.


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I’d say a bit of both. We’ve certainly had the chances to have better results than we’ve got. Tactically, however, I would say we are generally quite cautious and mainly concede from mistakes.

 

[djr8369]

I’d say a bit of both. We’ve certainly had the chances to have better results than we’ve got. Tactically, however, I would say we are generally quite cautious and mainly concede from mistakes.

It does feel like every mistake we make were punished for and costs points (partly because of how few we score).


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