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With apologies to Gil Scott-Heron, the data revolution that is currently happening in football will
not be televised. Instead, it is taking place in the cramped back offices of clubs where scouts are
now as likely to be hunched over a computer to check a player's performance indicators as they are
to be swapping stories of watching a young Algerian striker on a rainy night in Copenhagen.
I have uploaded the spreadsheets that I use to calculate the CONCACAF club and league coefficients
to the public FTP site of my company, Soccermetrics Research & Consulting. I am using this site to
host my publicly-available software projects, and while the the spreadsheets aren't software per
se, they do represent one of my early projects when I was getting started in statistical analysis
in soccer and they do attract interest from fans and other analysts.
I wanted to develop a spreadsheet that would accept match results in the group stages of the
Champions League and calculate an updated table. It took a while to get the cell and array formulas
right, but I finally have that spreadsheet which is linked below. The table generator is
straightforward to use and the four groups are in separate sheets.
While some goals are certainly more beautiful than others, do some actually matter more than
others? I've been trying get a bead on this question in part by comparing the relative value of
goals created in different ways. My earlier analysis of Guardian Chalkboard/Opta data for the
Premier League from the 2010/11 season suggested that open play goals had a stronger statistical
connection with points or wins than set piece goals did (The Guardian defined set piece goals as
resulting from penalties, free kicks, and corners).
If you've been reading this blog these last few weeks, you know that I've been spending way too
much time digging through data on shot creation in the Premier League with the help of the
Opta/Guardian chalkboards. But I can't quite help myself, so here's yet another installment; this
time it's on the (relative) uselessness of free kicks.
A few days ago, I took a look at the origins of goals in the first half of this year's Premier
League season to see what we can learn about the connection between different match situations
(defined as open play, corners, fast breaks, penalties, and free kicks) and goal creation.
In case you didn't have the time or inclination to read the details, here's the upshot: Keeping in
mind that teams scored on average 1.
Goals don't just happen - they are made. Both on offense and defense, teams control how they deploy
their resources (speak: players) on the pitch, and they make tactical choices about how to attack
and defend. Some rely more on fast breaks, while others try to create or avoid chances from open
play. So this means that goals are created and allowed.
When Hernandez scored for Manchester United in the first minute of play against Chelsea today on a
fast break after a beautiful pass from Park, it reminded me of the high value such shots have for
teams. Mind you, these kinds of opportunities don't come along all that much in the average match:
I have previously noted that teams actually create relatively few shots from fast breaks.
Here's another analysis of shot creation in the Premier League. This time, I'm looking into the
creation of accurate shots from one specific kind of situation: open play.
From the earlier analyses, we already know the following basic facts from the first half of this
year's EPL season, based on data from the Opta/Guardian chalkboards.
Here's another analysis of shot creation in the Premier League. This time, I'm looking into the
creation of accurate shots from one specific kind of situation: open play.
From the earlier analyses, we already know the following basic facts from the first half of this
year's EPL season, based on data from the Opta/Guardian chalkboards.
I've been spending a few posts looking at shot creation in the Premiership. One of the things I
haven't spent much time on is differences across teams in in terms of who has been creating the
most and least shots from different kinds of situations. These situations are open play, corners,
free kicks, fast breaks, and penalties.
I've been spending a few posts looking at shot creation in the Premiership. One of the things I
haven't spent much time on is differences across teams in in terms of who has been creating the
most and least shots from different kinds of situations. These situations are open play, corners,
free kicks, fast breaks, and penalties.
Last week I posted an attendance summary for all of the CONCACAF Champions League matches this
season except for the two finals matches. Now it's time to extend that summary with team-by-team
attendance figures, both raw numbers and attendance relative to stadium capacity. First, here are
the attendance figures over all of the stages of the competition, with separate columns for group
matches in the Champions League: Preliminary Group A Group B Group C Group D Knockout 18891 16862
900 12042 2632 4665 763 10626 5745 1990 3500 14062 6783 501 4700 22513 2050 11236 725 3400 2498
2899 7463.
In an earlier post, I took a closer look at shot creation in the Premier League to see what number
and proportion of shots are created from different match situations. The numbers, courtesy of the
Opta/Guardian chalkboards and covering the first half of this year's EPL season, showed that most
shots were generated from open play (11 on average per team/match).
In an earlier post, I examined shot creation in the Premier League to see what number and
proportion of shots are created from different match situations. The numbers, courtesy of the
Opta/Guardian chalkboards and covering the first half of this year's EPL season, showed that most
shots were generated from open play (11 on average per team/match).
Co-authored With Danny Pugsley, Editor of the fabulous Bitter and Blue blog.It is difficult to know how much success a club's spending on squad and coaching can guarantee, but
that has seldom prevented owners and managers from trying. And occasionally analysts have done a
terrific job getting good statistical results correlating transfer fees or wages with club's league
points, for example – witness Tomkins et al.
I received a couple of questions on my Twitter feed about the attendance figures for the CONCACAF
Champions League, so I decided to compile a table of the attendance for all the matches. I used
separate columns for the preliminary stage, the group matches, and the knockout stage. I did not
compile the attendance per team; that will come later.
Here's a different way of looking at positive leverage. In the spirit of analyses that have looked
at teams' ability to generate and take advantage of chances in a match, it's a way to identify
teams that both generate positive leverage situations and manage to, well, leverage them for a
win.
Here's what the graphs show.
Here's a different way of looking at positive leverage. In the spirit of analyses that have looked
at teams' ability to generate and take advantage of chances in a match, it's a way to identify
teams that both generate positive leverage situations and manage to, well, leverage them for a
win.
Here's what the graphs show.
Soccer's relatively low scores compared to other team sports make the game exciting and agonizing
at the same time. After all, any one score, any one action or mistake on the field can make or
break a team's day. Soccer's high stakes and the rare beauty of goals have a downside for analysts,
however.
The fact that soccer scores are low compared to other team sports actually makes the game more
exciting. After all, any one score, any one action or mistake on the field can make or break a
team's day. Soccer's high stakes and the rare beauty of goals has a downside for analysts, however.
In particular, the trouble with goals from an analysis perspective is that they are infrequent.
In earlier posts, I have discussed the idea of positive and negative leverage - the idea that being
up or down a goal (or two or three) changes the dynamics and the psychology of a match.
Statistically, I defined it as the odds of a team winning the match, given the particular score at
the time and the time remaining in the match.
In earlier posts, I have discussed the idea of positive and negative leverage - the idea that being
up or down a goal (or two or three) changes the dynamics and the psychology of a match.
Statistically, I defined it as the odds of a team winning the match, given the particular score at
the time and the time remaining in the match.
I've gotten lots and many different kinds of reactions to my guest post on the New York
Times Goal soccer blog. So I thought I'd say a few things about the issues raised by people who
care enough to comment.
First of all, thanks to everyone for reading and going to the trouble to write in, either on the
Times comments section or to me personally.
I've gotten lots and many different kinds of reactions to my guest post on the New York
Times Goal soccer blog. So I thought I'd say a few things about the issues raised by people who
care enough to comment.
First of all, thanks to everyone for reading and going to the trouble to write in, either on the
Times comments section or to me personally.
Check out my post on the New York Times Goal blog here. Enjoy!
Check out my post on the New York Times Goal blog here. Enjoy!
A quick follow up on how good Barcelona are this year; in a few days, I'll do a more involved post
on where the leagues stand at this point in the season, but I thought I'd share this little tidbit
for the Barca aficionados out there - and those of you who love to hate on Barca. Whether you're a
fan or a hater, you have to be impressed with how good they have been this year.
With the new MLS season about to get under way, I thought it'd be interesting to take a quick look
back at the last season to generate some baseline information for putting the league and teams in a
little bit of a soccermetric perspective. Without too much ado, here are some basic stats on the
league from last season to put you in the mood for soccer made in the U.
Most people would say that CD Saprissa's artificial turf gives them a significant home advantage.
But Saprissa's stadium has always been intimidating to visiting teams in the days when it still had
a grass surface. Assuming everything else equal, how significant is the difference in match results
from the grass pitch and artificial pitch eras?
Most people would say that CD Saprissa's artificial turf gives them a significant home advantage.
But Saprissa's stadium has always been intimidating to visiting teams in the days when it still had
a grass surface. Assuming everything else equal, how significant is the difference in match results
from the grass pitch and artificial pitch eras?
I am liveblogging the Soccer Analytics session at this year's MIT Sloan Sports Analytics
Conference. If you're interested, please follow along at my Soccermetrics site.
Here's another installment of "what is the point value of goals?" It's one thing to see how many
points are associated with different numbers of goals, or to see if first or second half goals
generate more points (they don't). But these analyses leave open the question of whether goals
produce different amounts of points, depending on when the situation the team finds itself in -
whether it is behind, tied, or ahead.
If you want to know how amazing yesterday's comeback by Newcastle against Arsenal was, consider the
expected point value of first and second half goals.
One way to compare the point value of goals it so calculate their values depending on
when
they were scored. To keep the analysis simple (after today's match), I was wondering simply whether
first half goals are more valuable than second half goals?
If soccer had a Super Bowl, who would win it? Since this year's Super Bowl - the final for the U.S.
National Football League (NFL) championship - is happening on Sunday between the Green Bay Packers
and the Pittsburgh Steelers, I thought it'd be fun to treat soccer as a version of American
football - only for a laugh, of course, lest you think I'm trying to blaspheme the best game in the
world.
Since my last report about conversion and shot records for various teams in the EPL, I've been
wondering how things were looking so far this season on the shot frequency/conversion front. But
instead of analyzing one league at a time, I thought it'd be interesting to compare several leagues
together.
Following up on my post about shot creation versus shot conversion as measures of offensive
production (see also the
On Football post), here's a quick and dirty analysis of Premier
League teams' ability to degrade opponents' shot
frequency (measured by shots allowed) and
shot
accuracy (the ratio of shots on target to shots allowed).
Ever since I started calculating shot to goal ratios as well as conversion and accuracy ratios of
teams' offensive (and defensive) production, I've been concerned that these ratios do not tell the
full story of what happens on the field.
Conversion, you may remember, is the ratio of goals
to shots on target - that is, how many of the high quality chances teams generated actually
resulted in goals: how good teams are at finishing.
The news at the beginning of the week was that CONCACAF officials would lobby FIFA for a fourth
direct qualifying place into the 2014 FIFA World Cup. The argument that the officials made was that
CONCACAF deserved an extra place on the basis of their performance in international competition
(i.e. World Cup finals).
The news at the beginning of the week was that CONCACAF officials would lobby FIFA for a fourth
direct qualifying place into the 2014 FIFA World Cup. The argument that the officials made was that
CONCACAF deserved an extra place on the basis of their performance in international competition
(i.e. World Cup finals).
