Always good to be near the top right of these charts.
We are 7th in the league when it comes to “shots in the box” per game (behind Oxford, Bolton, Rotherham, Sheff Wed, MKD and Plymouth) while being 2nd in the league for “average number of attackers in the box” per shot taken (behind Crewe).
Shows we are getting the ball into good areas to create opportunities and the tactics being deployed are allowing us to load the opposition’s penalty area when we do get forward.
What do they class as "attackers" ? Forwards/strikers/attacking midfielders or any player ? Such a misleading stat. But then again XG is a waste of time anyway. Above is a stat that there is only 1 other team better than us for getting "attackers" into the box and that is Crewe. Who are in the bottom 4. Says it all really.
Always good to be near the top right of these charts.
We are 7th in the league when it comes to “shots in the box” per game (behind Oxford, Bolton, Rotherham, Sheff Wed, MKD and Plymouth) while being 2nd in the league for “average number of attackers in the box” per shot taken (behind Crewe).
Shows we are getting the ball into good areas to create opportunities and the tactics being deployed are allowing us to load the opposition’s penalty area when we do get forward.
What do they class as "attackers" ? Forwards/strikers/attacking midfielders or any player ? Such a misleading stat. But then again XG is a waste of time anyway. Above is a stat that there is only 1 other team better than us for getting "attackers" into the box and that is Crewe. Who are in the bottom 4. Says it all really.
So another name for an attacker in XG terms is.....
A Player.
Any player can score a goal. I'm not sure what difference it makes.
The stat isn't even related to xG which is an entirely separate stat in it's own right... I just put it in here because there isn't another "collection of nerdy but maybe interesting CAFC-related stats" thread.
Really interesting article on how Liverpool are likely using data to inform their defensive tactics.
Spoiler: the data tells them to back off a striker who wants to shoot from outside the area. And they’re seeing success with it despite looking really a bit silly when the odd one goes in the top corner.
Really interesting article on how Liverpool are likely using data to inform their defensive tactics.
Spoiler: the data tells them to back off a striker who wants to shoot from outside the area. And they’re seeing success with it despite looking really a bit silly when the odd one goes in the top corner.
Really interesting article on how Liverpool are likely using data to inform their defensive tactics.
Spoiler: the data tells them to back off a striker who wants to shoot from outside the area. And they’re seeing success with it despite looking really a bit silly when the odd one goes in the top corner.
The scatter plot above shows that we are 7th best in the league this season for xG against and 9th best in the league for xG for.
Interestingly the top three in Wigan, Rotherham and MK are all in the top four for ‘xG against’ while two of those three actually end up below us on the ‘xG for’ scale.
Maybe highlights a correlation between a strong back line and getting promoted?
Wigan and Cambridge are the only real outliers when comparing the xG graph above to the league table
It’s all the more reason to study what they were doing more closely. What were Wigan and Cambridge doing this season that had them over performing? Is it just luck or is there something more that they’re getting out of their players?
The scatter plot above shows that we are 7th best in the league this season for xG against and 9th best in the league for xG for.
Interestingly the top three in Wigan, Rotherham and MK are all in the top four for ‘xG against’ while two of those three actually end up below us on the ‘xG for’ scale.
Maybe highlights a correlation between a strong back line and getting promoted?
Is this actual xG though or 'looking at bbc live stats' xG?
I struggle to believe any form of xG calculations below the Championship.
I would hope the source is decent like an Opta or Wyscout but the person hasn’t said where they’ve sourced the data yet, unfortunately.
Having said that, as long as you are consistent in your measurements across a 46 game season, whatever your source (even a BBC live text feed), you should come out with an accurate representation of how everyone is performing relative to each other.
I would hope the source is decent like an Opta or Wyscout but the person hasn’t said where they’ve sourced the data yet, unfortunately.
Having said that, as long as you are consistent in your measurements across a 46 game season, whatever your source (even a BBC live text feed), you should come out with an accurate representation of how everyone is performing relative to each other.
Your second paragraph is nonsense but okay. XG is a precise calculation per shot, if every shot has a huge margin for error then it's useless.
If they haven't said where they got the data from it belongs in the bin.
Why so aggressive all the time? All I was doing was sharing something I found interesting. If you want to know their sources, go ahead and ask them on Twitter.
If every shot measured is under or over estimated in a consistent manner, then it shouldn’t make much of a difference in relative team rankings across a season. The underlying numbers could be wrong but that’s not the same thing.
XG is a useful blunt tool that can't be fully accurate. Some players miss more but get more chances. There are a wide range of chances that classify simply as chances.
XG is a useful blunt tool that can't be fully accurate. Some players miss more but get more chances. There are a wide range of chances that classify simply as chances.
That partly comes down to the version of xG. If one model took into account the height, speed and direction of the ball, positioning of opponents, right/left foot or head etc it’ll be more accurate than one that perhaps only looks at where the player was shooting from.
The scatter plot above shows that we are 7th best in the league this season for xG against and 9th best in the league for xG for.
Interestingly the top three in Wigan, Rotherham and MK are all in the top four for ‘xG against’ while two of those three actually end up below us on the ‘xG for’ scale.
Maybe highlights a correlation between a strong back line and getting promoted?
This is fairly obvious to anyone who's ever followed football surely?
Premier league best defences - City and Liverpool (top 2) Championship - Forest, Bournemouth, Fulham (top 3) League 1 - Rotherham and Plymouth. Wigan and MK are 1 goal behind Plymouth (top 3 + Plymouth 6th) League 2 - Northampton, FGR, Exeter (the top 3)
You don't win anything if your defence isn't good.
Why so aggressive all the time? All I was doing was sharing something I found interesting. If you want to know their sources, go ahead and ask them on Twitter.
If every shot measured is under or over estimated in a consistent manner, then it shouldn’t make much of a difference in relative team rankings across a season. The underlying numbers could be wrong but that’s not the same thing.
How do you know it's being under or over estimated in a consistent manner unless you know the true value that the XG should be?
In data, margin for error matters, if there's a huge margin for error and he's sticking 0.6xG chances as 0.4xG, it will make a huge difference if you try to expand that error over the course of a season.
I imagine the only companies that have xG data for League One and League Two clubs are paying people to watch hundreds of games and that data is going to be behind a paywall and only available internally to clubs.
Opta xG for our matches so far this season and how many times you’d expect each result after putting these numbers into a Poisson distribution, plus the expected points associated with that calculation:
Comments
Answer to your question
A Player.
The stat isn't even related to xG which is an entirely separate stat in it's own right... I just put it in here because there isn't another "collection of nerdy but maybe interesting CAFC-related stats" thread.
Not exactly as amazing as they're trying to portray.
Spoiler: the data tells them to back off a striker who wants to shoot from outside the area. And they’re seeing success with it despite looking really a bit silly when the odd one goes in the top corner.
Article below.
https://medium.com/@chris.summersell/are-liverpool-breaking-a-sacred-defensive-code-8c5f806a4c41
Interestingly the top three in Wigan, Rotherham and MK are all in the top four for ‘xG against’ while two of those three actually end up below us on the ‘xG for’ scale.
Maybe highlights a correlation between a strong back line and getting promoted?
who would have thought it ????
I struggle to believe any form of xG calculations below the Championship.
Having said that, as long as you are consistent in your measurements across a 46 game season, whatever your source (even a BBC live text feed), you should come out with an accurate representation of how everyone is performing relative to each other.
If they haven't said where they got the data from it belongs in the bin.
Premier league best defences - City and Liverpool (top 2)
Championship - Forest, Bournemouth, Fulham (top 3)
League 1 - Rotherham and Plymouth. Wigan and MK are 1 goal behind Plymouth (top 3 + Plymouth 6th)
League 2 - Northampton, FGR, Exeter (the top 3)
You don't win anything if your defence isn't good.
In data, margin for error matters, if there's a huge margin for error and he's sticking 0.6xG chances as 0.4xG, it will make a huge difference if you try to expand that error over the course of a season.
I imagine the only companies that have xG data for League One and League Two clubs are paying people to watch hundreds of games and that data is going to be behind a paywall and only available internally to clubs.
1. Accrington 2.63 - Charlton 1.14
2. Charlton 1.60 - Derby 1.13
3. Sheff Wed 0.72 - Charlton 0.64
4. Charlton 2.68 - Plymouth 0.51
5. Charlton 1.27 - Cambridge 0.69
6. Wycombe 1.09 - Charlton 0.64
7. Bolton 1.09 - Charlton 0.76
9. Fleetwood 0.81 - Charlton 0.74
1. Accrington 2.63 - Charlton 1.14
(Home 69.17%, Draw 16.49%, Away 14.30%)
(Expected points: 0.5939)
2. Charlton 1.60 - Derby 1.13
(Home 48.26%, Draw 24.84%, Away 26.90%)
(Expected points: 1.6962)
3. Sheff Wed 0.72 - Charlton 0.64
(Home 32.97%, Draw 38.93%, Away 28.11%)
(Expected points: 1.2326)
4. Charlton 2.68 - Plymouth 0.51
(Home 83.10%, Draw 11.99%, Away 4.87%)
(Expected points: 2.6129)
5. Charlton 1.27 - Cambridge 0.69
(Home 50.36%, Draw 29.41%, Away 20.23%)
(Expected points: 1.8049)
6. Wycombe 1.09 - Charlton 0.64
(Home 46.15%, Draw 32.43%, Away 21.43%)
(Expected points: 0.9672)
7. Bolton 1.09 - Charlton 0.76
(Expected points: 1.0752)
8. Charlton 1.53 - Forest Green 0.63
(Home 59.16%, Draw 25.63%, Away 15.21%)
(Expected points: 2.0311)
9. Fleetwood 0.81 - Charlton 0.74
(Home 34.03%, Draw 35.99%, Away 29.98%)
(Expected points: 1.2593)
- total expected points so far based on expected goals tally: 13.2733