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Showing posts with label English Premier League. Show all posts

July 21, 2019

#MakeoverMonday: Arsenal Player Stats 2018-19

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This week for #MakeoverMonday, Eva was ever so kind to pick a topic that I really enjoy...Arsenal! She did this to coincide with my 800th Tableau Public viz. More about that in a future blog post.

Here's the original viz:

SOURCE: transfermarkt.co.uk

WHAT WORKS WELL?
  • A table is a simple way to display stats that serve the purpose of looking up values. That seems to be what the designer had in mind here. This viz isn't for comparing players.
  • Being able to sort by the headers
  • Including an image of the player; this helps those that are already familiar with them.
  • Including links to the player's profile

WHAT COULD BE IMPROVED?
  • Other than this being used to look up information, what purpose does it server? It merely a list of facts.
  • There's no context for the numbers. How does a player rank amongst the team?
  • It's visually unappealing.
  • I can't find definitions for some of the stats. For example, what does "In Squad" mean? No clue!

WHAT I DID
I first thoughts about creating player cards with the stats over time, big numbers, etc. But the data was only for one season, so I had to scrap that idea.

Then I thought back to a viz by Andras Szesztai that I was shown last week. His viz is about NBA basketball team spending by season, and it includes stats like the lowest, highest, and average payroll. He then has a mark on the viz for the salary cap.

I took his concept and applied it to the team and player stats. I included the minimum, maximum, and average for the team for each stat (like Andras did for each season). I then included a dot for the player selected. This allows you to see how the play compares within the team as a whole. So I got to include a player card of sorts after all!

Lastly, I made it mobile friendly because it seemed to make more sense to scroll down the viz vs. laying them out in a grid.

Check it out!

May 16, 2019

The History of English Football Champions: 1888-2018

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Last week I saw this really cool viz from Squawka Football on Twitter and wanted to see if I could rebuild it.

Given that this requires animation, I knew I needed a tool that supported this and I turned to Flourish. The data has to be structured in a very specific way, so I downloaded the data from Wikipedia, imported it into Alteryx for a bit of a massage, and spit it back out in the format Flourish required.

And voila! An animated viz of the history of English football champions from 1888-2018. Very little effort required + great animation = win!

August 9, 2018

The Petr Cech of Chelsea was outstanding...then he moved to Arsenal

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Arsenal signed goalkeeper Bern Leno in the offseason. Rumors have been swirling about when, not if, he'll takeover as their top choice keeper. Three summers ago, Arsenal signed Petr Cech away from Chelsea, and with that signing, Arsenal had hoped to sure up their defense.

In an Arsenalesque sense of optimism, Arsene Wenger thought bringing in a great goalkeeper would solve their defensive woes. Many fans, however, knew that the real problems were in front of the goalkeeper. Without a solid defense, a goalkeeper cannot be effective.

This led me to thinking about how Cech's first three seasons compared to his first three seasons with Chelsea, when he was widely considered one of the best goalkeepers in the World. The data shows that Arsenal more or less ruined him. Or did Chelsea's stellar defense make him better than he really is?

History of the Premier League Table

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The 2018-19 Premier League season kicks off tomorrow night with an enticing match between Manchester United and Leicester City. This reminded me about a viz I had created at the end of the last season as a way of practicing stepped lines in Tableau.

When I originally created this, I had to use table calcs to get the stepped lines to work, which can get complicated and is very time consuming. Now with stepped lines, it merely a matter of changing the lines type.

I decided to add in a couple of user options:

  1. Which team do you want to highlight?
  2. How do you want to compare the teams? By total points for the season of the final position in the table?
  3. Not all teams have been in the EPL for all 17 years, so I provided an option to filter down to just the teams that have been in the EPL for the user specified number of years.

And here's the viz for you to explore. Enjoy!

May 21, 2018

Makeover Monday: How well did The Guardian predict the Premier League table?

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Back to sports again this week. With the Premier League season just finishing, we're looking at how well The Guardian predicted the EPL table at the start of the season.


What works well?

  • Sorting the teams by prediction makes sense since this is an evaluation of their performance against their prediction.
  • Including the logos so people can find their favorite team
  • Including the numbers for the table position so that the reader doesn't have to count as they go
  • Shading every other row helps break up the view

What could be improved?

  • If you don't know the team logos, it can be hard to track a team across the table.
  • It's hard to see which team did better and worse than expected.
  • There's no scale for how "well" The Guardian predicted the table.

My Goals

  • Focus on the difference between the predicted and actual results
  • Try to create some sort of unit chart (I didn't have time to figure out the calcs, so I cheated with distribution bands)
  • Make it easier to see if team finished above or below the predictions
  • Finish in under an hour because we did MM live at the Data School and had to present to Eva at the end of the hour 

June 5, 2017

When Arsenal Lost the Plot...and the Significance of the Change to 3-5-2

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I've had this viz on my mind for a couple months now, basically since Arsenal crapped themselves mid-season. I wanted to understand the ebbs and flows of the season a bit better. This also gave me a good excuse to practice using Tableau's story points feature.

So I sat down last night and cranked out this viz and story about Arsenal's 2016/17 campaign, including the up, the downs and the inevitable contract extension for Arsene Wenger.

Enjoy!

December 24, 2015

Premier League: Who Has the Toughest Christmas Schedule?

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It's nearly Christmas, which means we have the best time of the year quickly approaching for any fan of English football...the Christmas fixtures. They come fast and furious, and my beloved Arsenal sits in 2nd position behind surprise leaders Leicester City. But who has the toughest run of matches?

Using the viz below, you can see that, based on the average position of their opponents, Bournemouth has the toughest run followed by Chelsea. Leicester has the 6th toughest run, while Arsenal have the 5th easiest. This provides hope that Arsenal can finish the festive season on top of the Premier League.

I've added a parameter on the upper right to allow you to view by opposition points as well. In this view, Bournemouth and Chelsea still have the two toughest schedules, but the teams with the easiest schedules shifts a bit.

On the 2nd tab, I've added a bit of an exploratory view. Pick a metric and see the team rankings.

#COYG!

April 20, 2015

Makeover Monday: Chelsea Are the Worst-Behaved Team in the Premier League When It Comes to Showing Respect to Referees

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Last week the Premier League published the first (sort of) detailed stats on their Fair Play League table. Quickly thereafter, all of the news outlets reports how Chelsea basically treats the refs like garbage. Anyone that watches the Premier League, even Chelsea fans, knows this is true. Don’t deny it folks!

As I was scouring the various reports, I didn’t see anyone actually create a viz on the subject. The best I found was this table from The Daily Mail:


A table is great for ranking and looking things up, but terrible for doing any sort of analysis. I downloaded the FPL table into Excel (here) and combined it with the BPL standings as of the same date.

In the viz below, I’m using Chelsea as the baseline for comparison, because the story that interested me was how much worse does Chelsea behave compared to the other teams. For example, if you hover over Liverpool, you will see that Chelsea is 14% worse with its respect for referees.

I then added a second tab that allows you to explore the data on your own. Pick a FPL stat, a BPL stat and you can compare and contrast. The question I wanted to answer here was “Is there a relationship between FPL and BPL stats?” I can’t find any interesting relationships, but maybe you can.

April 12, 2015

English Football Stadium Tracker

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Today is Sunday, which means it’s Sunday Long Run. Those of you that are runners know what I mean. I moved to London last Saturday and my goal for my runs is to use them as a way to explore new places. Yesterday, I went to see Leeds United play with a friend from Atlanta who grew up a Leeds fan.


Today, I set out to see some football stadiums. I mapped a route that took me from Wimbledon, past three iconic football stadiums.

Craven Cottage - home of Fulham FC
Loftus Road - home of QPR FC
Stamford Bridge - home of Chelsea FC
Shortly after I posted my run on Instagram, someone commented that I had missed a nearby stadium. Naturally I thought I needed a viz to keep track of the stadiums I have visited. I found the geocodes for more stadiums here, but it was missing a few teams. I created this csv to track the stadiums where I’ve seen games. I’m going to do my best to keep up with it. This viz includes the first four divisions in both English and Scottish football (as of the 2014-15 season).



And yes, I know I titled this post "English" and Scotland is not part of England, but UK football stadium tracker doesn't resonate as well with me.

February 16, 2015

Makeover Monday: How Does Francis Coquelin's 14/15 Season Compare to Alex Song's 11/12 Season at Arsenal?

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Ever since Alex Song left Arsenal for Barcelona in the summer following the 11/12 season, Arsenal have been in desperate need of a defensive midfielder. They've been scraping by with Arteta and Flamini, but they're both aging and not getting any better. In the 2014 summer transfer window, fans were screaming out for Arsene Wenger to sign a DM. Stubborn as he is, Wenger didn't sign one.

That decision left Arsenal very thin at the back to start the 14/15 season. Fast forward a few months and injuries, as they always do, hit Arsenal hard. They were forced to recall Francis Coquelin from a loan spell at Charlton.


As the saying goes, he's been like a new signing. In his previous spells with the first team, he failed to establish himself, but this time around, he grabbed hold of the opportunity and surely now Coquelin is the first name on the manager's team sheet.

Late last week, I ran across this article from HITC Sport. In it, Dan Coombs says "Coquelin has shown already that he is playing defensively at an equal or higher level than Song's final season at the club." Dan then provided this simple table:


This table is perfectly fine. It's a table and it provides a great way to look up the data. In the end, the point of the story is to show how effectively Coquelin is playing compared to Song. I created this infographic in Keynote with the hope that it is more interesting, more engaging and makes comparisons easier.


January 11, 2015

What If Premier League Standings Were Based on Points per Goal?

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This week on the Football Ramble podcast (listen here), they talked about a very strange stat they have been observing this Premier League season:
So far in the 2014-15 season, Aston Villa has the highest points per goal of any Premier League team in the last 10 seasons.
This was quite intriguing to me, so this morning while I was enjoying a cup of coffee at Tully's I went to ESPNFC.com and downloaded the standings for the last 10 years. I added two columns to this dataset, which you can download here.
  1. Points per Goal (PPG)
  2. PPG Position (i.e., a rank of each team based on PPG)
I turned to Tableau to do a quick analysis. My first way of looking at the data was as a scatter plot. I wanted to see just how much of an outlier Aston Villa has been this season.





From there, I wanted to understand the difference between Villa's actual place in the EPL table and their place in the fictitious points per goal table. For this view, I created a slopegraph, which I first wrote about creating in Tableau here.

If you're unfamiliar with slopegraphs, Andrew Wheeler summarizes them well in his paper "A Critique of Slopegraphs":
Slopegraphs show values for two numeric variables by line segments for each observation by connecting points on two parallel axes. They are frequently recommended for visualizing the changes in ranked data (Bertin, 2011; Tufte, 2001).
I put all of the pieces together in this simple dashboard, which you can download here. Do you notice anything else interesting or unusual?


December 17, 2014

Henry or Shearer? Who is the greatest Premier League Striker?

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December 16, 2014 will always be remembered in Arsenal lore as the day Thierry Henry officially retired from football.  He's been away from Arsenal for the most part since he left for Barcelona after the 2006-07 season. At that point in his career, he had scored 174 Premier League goals, getting one more in January 2012 in a brief return, closing his Premier League account with 175 goals.

In a tribute to The King, the Premier League created this great compilation video.

Post by Premier League.


Henry's retirement led to the inevitable debate of who is the greatest Premier League striker ever? Most people agree that Thierry Henry and Alan Shearer are in a class by themselves. The great thing about sport is that it leads to lots of opinions and great debates. There are Henry camps and there are Shearer camps.

I gathered their career data from wikipedia (here and here) and combined them into a single spreadsheet here. I built this quick viz in Tableau to allow you to answer the question for yourself. Download the workbook here.



October 29, 2014

Plot.ly - A simple interface for creating great looking charts in d3

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Yesterday I had the pleasure of meeting Matt Sundquist, Co-Founder and COO of plot.ly. Plotly is a really interesting new data viz product that allows you to quickly build charts directly in your browser. It's built on top of d3, so it has tons of styling capabilities. If you're looking to build charts with d3, but don't want to do much, if any, coding, then you should definitely check it out. They have a free version.

What is Plotly? The folks at import.io have a great summary:
Plotly is a young graphing and analytics startup, which makes it easy to analyze and visualize data together. Using Plot.ly, users can import data from anywhere, then make and share online graphs using Python, MATLAB, R, Excel, Julia, and their web app. Users can also share work and collaborate on projects.
The Plotly API enables users to analyze and visualize data in one place, and forms an important step in building the infrastructure for data science to be further democratized. Their goal is to be an awesome platform for collaboratively analyzing data and making graphs. 
From the Plotly website, in the workspace area (think of this as a worksheet in Tableau):
Easily make graphs with your data in the workspace. Import data from Google Drive or upload Excel or text files. You can apply fits, stats, and functions to your data.  
Every element of a Plotly graph is customizable. Change the colors, annotate, write LaTeX, toggle graph ticks, and much more. It's up to you!
The best way to get familiar with any new product is to start using it. Since I had just publish a parallel coordinates plot in Tableau yesterday, I thought I would use the same dataset and see how long it takes to build something similar in Plotly. I was pleasantly surprised by the simplicity and intuitiveness of the interface. It took me about 30 minutes to build this view, but a lot of that time was spent tweaking the settings to get them just right, which I'm perfectly ok with given the very detailed control I have over the final display.

Plotly doesn't currently support things like filtering and parameters yet, but for a first pass through, I really like it and will definitely be using it more often going forward. So, here's my first plot.ly viz (be sure to hover over dots to see their awesome interactivity):

October 28, 2014

My first experience with import.io and Tableau

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Remember when you first found Tableau and realized you would never use Excel to create charts again? Well, I had a similar eureka moment last Thursday when I sat in on a great webinar by import.io hosted by Alex Gimson - Build Grow Scale: Getting started with import.io. The difference here is that I will no longer need to copy/paste from webpages; import.io will do all of the work for me!!

During the webinar, Alex revealed that he was a huge Arsenal fan (as am I), and I wanted to find a simple project to become more familiar with the tool. My basic idea was:
  1. Use the import.io Extractor to download the Premier League table from ESPNFC for every season since 2002
  2. Create a visualization in Tableau
  3. Allow the people interacting with the viz to highlight their favorite team
  4. Make Alex happy!
During the webinar, Alex went through a simple Extractor example. Here's a screenshot of the extractor that I built (click on the image to make it larger):


Get the import.io dataset here. Overall, the process was super simple. All I had to do was paste the URL in the box on the left, then add a URL for each season. From there, I clicked on the Download button on the upper right to download it into Excel. I did a bit of cleanup in Excel to make it Tableau-ready.  Download the Excel data here.

Before import.io, this would be a painful process of navigating to each webpage, copying the table, pasting it in Excel and repeating for each season. Using import.io, I completed the whole process, including cleaning up the data, in under 5 minutes.  The import.io portion of the process took about 2 minutes.

From there, I built this simple viz in Tableau. It took about 30 minutes to build this in Tableau, but I had already sketched out on paper what I wanted to create. I waited until match week 9 completed to publish this viz because I wanted to test how easy it is to refresh the data in the Extractor. It was super simple!

I would highly recommend using import.io. I'm going to continue to look to use it whenever I need to crawl webpages for data.

Download the Tableau workbook here.

October 13, 2014

Makeover Monday: Arsenal's Injury Crisis - A Story

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ESPNFC recently published an article providing some details about Arsenal's nearly 900 injuries since the start of the 2002-2003 English Premier League season. Last year, Arsenal crossed the 100 injury mark, suffering 111 injuries in total. This year they are picking up where they left off, with 26 so far this season. In particular, Arsenal continues to be without Theo Walcott and has suffered major, long-term injuries to key players like Aaron Ramsey, Mathieu Debuchy and, most recently, Mesut Ozil.

I found this story fascinating because it finally put numbers to Arsenal's perceived injury crisis.  They do indeed suffer way more injuries than any other EPL team. But what bothered me about the ESPN story was that they basically just listed off a few key facts (quoted from ESPN):
  1. Arsenal players have sustained 889 injuries since August 2002, according to a report by PhysioRoom.com.
  2. The Gunners' 889 injuries over the 12-year period compare to 792 for Manchester United, 620 for Chelsea and 551 for Liverpool.
  3. Abou Diaby, who has recently returned to fitness, has endured 40 separate injuries, according to the study, while Theo Walcott, who is currently recovering from a serious knee problem, features 42 times.
  4. PhysioRoom.com claims 120 of the injuries were of the hamstring variety while six anterior cruciate ligament (ACL) have been suffered.
These all seems like interesting stats, but they're missing something incredibly critical...context.

Without comparing Arsenal to their rivals, how do I know how bad their injury crisis really is? If they're suffering injuries at the same rate as their rivals, then maybe there isn't a crisis after all. But if their rate of injury is higher, then perhaps there is more to the story. Have Arsenal players always been injury-prone or have they increased since they moved to the Emirates Stadium with its rock hard surface?

I set out to understand more by downloading the injury reports from PhysioRoom.com for all teams that have participated in every year of the EPL since 2002-03 (plus a few others that are not included in my final story below). You can download the data in Excel format here.

So in a sense, today's makeover is not a makeover of a chart or dashboard; it's a makeover that takes a text-based story and adds charts and graphs to tell a more meaningful story.

Download the Tableau workbook used to create this story here.

September 13, 2013

When Arsenal stole Mesut Ozil from Real Madrid, they got a player nearly as good as Xavi and Iniesta combined

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Fact: Mesut Ozil is a Gunner
Fact: Across all competitions, Ozil is nearly as good as Xavi and Iniesta COMBINED, merely 0.01 goals + assists per game behind the combined pair.  Get your head wrapped around that.

When Arsenal surprised everyone by actually spending some money on transfer deadline day with the club-record signing of Mesut Ozil for $67M, many of the pundits (1) were in shock that Madrid sold him and (2) thought Arsenal had secured THE BEST central midfielder in the world.

Turning to the data, you can easily make such an argument.  Using the viz below, you can compare Ozil to many of the other top central midfielders in the World.

  • Despite having played fewer seasons than nearly all of the players on this list, Ozil is the leader in total assists, leader in goals + assists per game, and the runaway leader in assists per game across all competitions.
  • Xavi and Iniesta may get all of the plaudits, but they are well down the list of goals + assists per game across all competitions, coming in at 10th and 13th respectively.  They are far behind Ozil and just behind Santi Cazorla.  This has to bode well for Arsenal.
  • Ozil has been the clear leader in assists across all competitions for the past four years. meanwhile Xavi's production has steadily dropped, with a dramatic drop off in the 2009/10 season.
  • Ozil consistently performs better for country than club and on the international stage, his performance vs. his peers is even more staggering.
  • Barca need to get Cesc on the field more often.
  • Frank Lampard, despite playing for the Evil Empire in Chelsea, was astonishingly consistent and dominant from 2003/04 through 2009/10.  Frank performs better than Gerrard on the international stage when looking at averages per game, yet you would think, based on what you hear in the press, that Gerrard's performances far exceed those of Lampard.  The data shows otherwise.  I suppose that's why they call them pundits and not experts.
  • Manchester United are desperate for an attaching midfielder to complement Michael Carrick.

Play around with the viz and comment with things you see.  You can also download the workbook here.

May 8, 2013

Was Theo Walcott’s performance for Arsenal driven by motivation for a new contract?

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With two matches to go in the EPL season, Arsenal is in a battle for a Champions League spot with Chelsea and Tottenham and Theo Walcott is leading scorer.  He started out the season in great form, then suddenly tapered off immediately after he signed a new deal with the club.

In Arsenal’s last two matches, Theo has scored two great goals very early on in the game, at the 2’ mark against the champions Manchester United and 20 seconds into the most recent game against relegated QPR.  Theo is back in form.

I was interested to see how Theo has impacted Arsenal’s overall performance.  Use the viz below to see how Arsenal performs when Theo does or does not play (Arsenal have a higher winning % when he doesn’t play, though in a small sample size) and when he does or does not score (their winning % increases by 20% when he plays and scores vs. when he plays and doesn’t score).

In other words, Arsenal need Theo to play and score.

Download the data here and the Tableau workbook here.

January 16, 2013

The one chart that shows how the sale of Robin van Persie impacted the fortunes two clubs

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Super Sunday has come and passed along with yet another abject Arsenal performance.  I attended the game with about 100 of my fellow Bay Area Gooners at Maggie McGarry’s in San Francisco. This is THE place to watch Arsenal. 

We were pumped for the game, only to be let down nine minutes into a game by a stupid foul and the subsequent sending off of Laurent Koscielny.  Why wasn’t the BFG Per Mertsacker playing in the first place?  That’s another rant for another time.

Several Gooners at Maggie’s were talking about Arsenal’s lack of ability to dominate the final third of the pitch, which got me daydreaming back to the days of Robin van Persie.  Arsene Wenger sold RVP to Manchester United over the summer, literally telling Sir Alex Ferguson that he was handing him the title.  Of course, RVP has continued scoring like the 3rd best striker in the World.  I think our manager has lost the plot. 

I pulled some data down from the Barclay’s Premier League website to see how teams were performing through 21 fixtures this year compared to last.  I created this:


Tufte introduced slopegraphs in his book The Visual Display of Quantitative Information.  This type of chart is useful because is helps quickly highlight:
  • The order of the clubs
  • The specific number of points accumulated by each team in each year
  • The slope reveals the change over time and each club’s rate of change compares easily to other teams
  • There’s almost zero non-data ink.  I say almost because I used red to highlight Arsenal.
Presented this way, the data reveals a few simple observations:
  • Manchester United have opened on the rest of the league this year and that they were in 2nd place last year.
  • The gap between Man U and Arsenal is HUGE this season, which is surely directly correlated the RVP’s transfer.
  • Everton and West Brom have had much stronger starts to the season.  Don’t be shocked if Everton snatches the last Champions League spot.  It sure doesn’t look like Arsenal has the heart to do it.
  • Newcastle sucks this year!
  • Most importantly, we’re only 5 points behind Spurs, whereas we were 10 points behind at this point last year.  If we’re not going to make the Champions League, we could take a bit on consolation in finishing ahead of Spurs.
If you have an ideas on how to turn Arsenal’s season around, please feel free to let the club know.

April 16, 2012

When did Arsenal’s season really turn around?

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As we approach kickoff of the Arsenal vs. Wigan game this afternoon, I thought I’d take a quick look back at the Gunners’ season and when the data says the season may have turned around.

It’s well documented that Arsenal got off to one of the club’s worst starts ever, but gradually they have come back and are currently in third place.  With five games remaining, their magic number over Spurs and Newcastle stands at 11 and 8 over Chelsea.

“Magic number” is a phrase we use in the States, particularly with baseball, “to indicate how close a front-running team is to clinching a season title (or third place and a Champions League automatic qualifying spot in Arsenal’s case). It represents the total of additional wins by the front-running team or additional losses (or any combination thereof) by the rival team after which it is mathematically impossible for the rival team to capture the title in the remaining games.”

Many people point to the goal below by Bacary Sagna when Arsenal were down 0-2 against Spurs on 26-Feb as the turning point in the season.  (Pardon the poor quality; it’s all I could find on YouTube.)  I must say that I love the way Sagna took the goal, followed the ball into the goal, picked it up, ran it to half field and all but said “I’m sick of this!”  The entire attitude of the team seemed to shift on this one goal.  I get the chills every time I watch it.

Again, I have no doubt about the attitude shift at this single moment, particularly after back-to-back poor results against AC Milan (Champions League) and Sunderland (FA Cup).  But looking at the data for the EPL only, one particular match stands out as the turnaround point..the 7-1 thrashing of Blackburn, whom Arsenal somehow managed to lose to during their early season swoon.

Below you will see four chart, all which highlight this 7-1 game.

  1. Points Trend – the upward trend of full-point matches clearly starts with the Blackburn match
  2. Points vs. Possible – Here, you want to see a flat green line, which indicates full points are taken from the match.  Look at that long run of results that starts with the Blackburn match.
  3. Table position – What an ugly start to the season!  There was a recovery for a few weeks 1/3 of the way into the season, but another string of poor results began with the 0-1 loss to Manchester City.  But the run of results beginning with the Blackburn match, combined with a significant dip in form by Spurs, has pole vaulted the Gunners into 3rd place.
  4. Score vs. Result – This is a simple scatterplot. The darker the bubble, the more results for that score.  Excluding the 2-8 drubbing at the hands of Manchester Units, Arsenal have lost every match, bar a 0-2 defeat by only one goals.  This indicates that they have been in every match, but haven’t been able to score late to turn the result around.  But look at our wins, the scores have been tremendous with a but more than a 4-1 average score.

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Touch wood that Arsenal will hold on to third place, and please, please, please RVP, sign a new contract!

December 24, 2011

Heat Map: Manchester Derby Results Since 1907

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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.

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

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