Are Premier League referees getting worse? It sure seems that way when I watch games.  And despite the opinion of Sir Alex Ferguson, the decisions do not even out.

What makes it even tougher is when the players dive all over the place with no intent other than to con the referee.  Is anyone with me on starting a campaign for retroactive suspensions for diving?  That would stop all of the diving immediately!  Guaranteed!

Ashley Young has been near criminal in two recent matches.  He’s even been mentioned for a position on Great Britain's Olympic diving team.  Refer to the video of Man U vs. Villa and Man U vs. QPR for some of the finest acting in years.  He really ought to be ashamed of himself.

But it’s not only the PKs that are called; it’s those that are not called as well.  Refer to the highlights, if you can find them, of the Man U vs. Fulham game on 26 March 2012.  The game was at Old Trafford, it was late in the game, there was a CLEAR penalty against Man U and, of course, it wasn’t called.

I’m not saying there’s a bias towards the “bigger clubs”, but looking at penalty kick data sure leans me in that direction.  All you need to do is filter the viz below to only include teams that finished 1-4 and you’ll see what I mean.

The top four teams get way more PKs called in their favor than the rest of the clubs AND they significantly more PKs called at home.  I simply can’t believe that referees are NOT intimidated by Fergie and Old Trafford?

Click on the Manchester United logo to focus on them.  Look at those startling trends that appear at the bottom.  Intimidation at its finest!

If you want to see the details behind the charts, go to the Team PK Stats tab. 

• Look at how many PKs the top four teams have gotten over the year, both overall and at home
• Now compare that to the relegated teams (18-20)

Maybe it’s because the top teams have the ball more and create more situations where a PK could be called. But still, should the numbers be so overwhelming?

The Soccer by the Numbers blog continues to provide me great inspiration. After Manchester City destroyed Manchester United 6-1 on October 23rd (at ManU), they blogged about the results and provided a bit of statistical analysis.  City has long been the “noisy neighbors” to United, but they now are doing their best to buy a title, rather than grow their own talent.  Soccer by the Numbers posed this fundamental question:

We now know that the outcome of the match was truly unusual. But how unusual?

They created the table below, which is a frequency distribution of scored lines since 1907 of matches at Manchester United.  To use the chart you simply identify the score line by going across City’s scores then down ManU’s scores.  So the 6-1 scoreline has occurred 2.99% of the time since 1907.  Clearly this was an unusual result.

But I think this table could be improved.  I made these changes:

1. Changed the numbers to percentages and rounded to one decimal.  Two decimals is unnecessary precision.
2. Removed most of the gridlines so that the lines separate the data from the categories
3. Formatted the results as a heat map.  I chose a red-white two-color scheme since Red is ManU’s color.  This makes the largest percentage of result very obvious.  For example, you can now easily see, without having to scan across all of the data points, that 1-1 is the most common score line…boring result!
4. Formatted the totals as a second heat map.  I chose a brown-white scheme for these.  The totals show you the % of the total goals scored for each time.  ManU has scored one or two goals 64.2% of the time while City has scored one or two goals 58.2% of the time.

 

Which format do you like best?  Does one make the story easier to interpret than the other?

On Football has quickly become one of my favorite blogs to follow (Twitter) and one of the most interesting posts of late was an analysis of “finishing” in Major League Soccer.  OnFooty analyzed conversation rate vs. the number of shots for each team over the total season.  Typically conversion rate is calculated as goals/shots on target, but OnFooty has a terrific case for using shots in lieu of shots on target.

In conclusion, Sarah said “The upper right quadrant (teams that are above average at both creating and finishing) contains the MLS Cup Finalists and the number one seeds for each conference.

This quickly led me to the Premier League and interestingly enough, the same analysis holds true through 30 rounds (29 for some teams) this season.  The top four teams are all in the upper-right quadrant. 

If you follow English football, you might note these things as well:

1. Tottenham needs to improve their finishing if they want to secure a returns spot into the Champions League qualification round (for the 4th place finisher)
2. Blackpool (one of the most exciting teams to watch) score at a terrific rate, but since they’re in 15th place in the table, they obviously need to work on their defense (their philosophy is to outscore their opponents since they know they can’t stop them
3. Wigan has the worst conversion rate and sits last in the table…enough said

Play with the view below.  Choose your vertical and horizontal axis, check out the different tabs.  What do you see?

I’m compelled to look historically to see if this theory holds true season after season…maybe one day when I have more time on my hands (I’m busy tallying stats for my daughter’s soccer team).

Let me start by saying I am a HUGE Arsenal fan. I catch every game that’s on TV here in the States. 

If you’re living under a rock and don’t watch football, the knockout stages of the UEFA Champions League begin Tuesday with Arsenal hosting Barcelona on Wednesday in the biggest tie of the round.  Catch the game on Fox Soccer Channel at 2:30pm ET.  If you want to see the game played at its absolute highest level, this is the game to watch.  It will be a beautiful sight.

Annually Deloitte publishes a list of the top 20 football clubs in the world based on revenue.  As always, the Guardian Datablog published a viz to go along with its article.  They published this absolutely hideous stacked bar chart.  Seriously, this is what they published.  How do you even know which team is which?  There is a fancy mouse-over feature.  This stuff kills me!

With Tableau, there are so many better ways to make this data interesting.  Here’s my take:

Interacting with the viz you can quickly see that:

1. The Barclays Premier League dwarfs the other leagues in all revenue types
2. The Barclays Premier League has seven of the top 20 teams (click on any of the league logos to filter the list of teams)
3. Real Madrid is a MUCH bigger club than its city neighbor Atletico de Madrid (350% bigger)
4. Manchester United is also a MUCH bigger club than its city neighbor Manchester City (229% bigger).  I hate them both, but Manchester City even more since they think they can buy themselves a title.  No chance with an Italian manager; the football is way too negative!
5. Arsenal dominates matchday revenue, thanks in large part to the spanking new Emirates Stadium (I can’t wait to see it some day).  I heard on TV today that they generate $3M every game
6. The top three clubs in terms of broadcasting revenue are all in Italy.  According to the NY Times, “Italian teams negotiate their own television contracts, with the top clubs like Inter Milan, A.C. Milan and Juventus garnering huge deals”, whereas it’s a shared revenue pool in the other leagues.  Heck, Real Madrid’s rank in broadcast revenue puts them at 17th, but their overall revenue has them at #1.
7. German clubs lead the way in commercial revenue.  I know virtually nothing about the Bundesliga other than their games are fun to watch and the chanting by the fan is endless

Does anything else stand out to you?

Go you Gooners!

According to the Guardian Data Blog on December 1st “The freezing weather, which fell to -20C in parts of Scotland, continues to severely disrupt travel across the country.  The problem is the ground temperature is lower than the air temperature [which] makes thawing difficult.” 

This impacted me since the Manchester United vs. Blackpool match was not shown on Fox Soccer Channel.  Apparently Blackpool doesn’t have an underground heating system to keep the pitch from freezing.  It stinks when you set your DVR and get some other crappy game instead.

The Guardian presented the data via a Google map, which is not surprising since this is such a simple way to present the information.  The problem with presenting the data this way is that you can’t determine how cold it really was nor how much the weather changed; the data is represented merely as points on a map.  If you look at this map, it could mean just about anything: vacation spots, lighthouses, you name it.

I wanted to understand how the temperature changed day to day from December 1-3.  I wish they posted the data for more days so that I could see what happened over the weekend as well (to justify the game getting canceled).  I loaded the data into Tableau and changed the measurement to be the change from day to day.  This means that December 1 doesn’t have anything to compare to. 

It’s incredibly clear that there was a bit of a warm up in many places in the UK with the exception of the northwest.  However, the temperature dropped dramatically on December 3, but with a warming occurring in the northwest.  Scroll through the days to see it for yourself.