Just like millions of viewers around the world, I too have been spending hours watching FIFA world cup football matches on TV. I don’t like spending hours watching TV. But when its FIFA world cup time (which is once every 4 years), I am glued to the idiot box. Blame it on PaWaRa, my school teacher in 8th grade who instilled this passion.
So while watching the match day before yesterday (it was Holland vs. Chile), the commentator said, “This has been a world cup of late goals” as both teams maintained 0-0 until 77 minute mark when Leroy Fer scored a goal for Holland.
That got me thinking,
Is this really a world cup of late goals?
But I quickly brushed away the thought to focus on the match.
Later yesterday, I went looking and downloaded all the goal data for 2006, 2010 & 2014 FIFA world cup matches (2014 data for first 36 matches).
Lets examine the hypothesis “2014 has been a world cup of late goals”.
Attempt 1: Distribution of goals on 90 minute timeline
There have been 147 goals in 2006, 145 goals in 2010 and 117 goals in 2014 (as of 24th June, 2014). Out of all these goals, only 5 goals were scored after the 90 minute mark. So I ignored these 5 goals for our analysis.
Also, I assumed that any goals scored in injury time are part of the 45th minute or 90th minute mark (for simplicity).
One more: I have included data only up to 23rd of June, 2014 – so only first 108 goals of this edition are considered. This reflects accurately the moment commentator made that remark.
Lets see the chart.
Each dot depicts a goal. The dots are filled with semi-transparent color, so we can see the density of goals at each point of the 90 minute timeline.
As you can see, there is no clear pattern of late goals in 2014.
While we could see higher density of dots in first half of 2006 & 2010 editions, that can be attributed to having full data vs. partial data (for 2014).
Attempt 2: % of goals scored in each 15 minute block
May be if we look at % of goals scored in each 15 minute block, we can conclude something.
This gives an indication that 2014 world cup indeed has slow first half. But then you also see conflicting proof with more goals scored in last 30 minutes in 2006 & 2010 editions.
Attempt 3: What if we consider only first 100 goals in each world cup
Lets remove some noise. The commentator said this has been a world cup of late goals. If we consider only first 100 goals (ie first 30 odd matches) in each world cup may be we can see how 2014 fares compared to 2010 & 2006 editions.
Here too the chart does not reveal much. If anything, we can conclude that 2006 has clear pattern of high number of goals in first & last 30 mins.
While 2014 has high density in the last 30 mins, it has good distribution throughout the 90 minutes.
Attempt 4: Lets consider only the first goal of each match
I guess the impression of slowness is created if you have to wait a lot of time to see the first goal in any match. After that usually things pick-up.
So what if we consider only the first goal times in each match.
This is what we get.
Now this is clear. You can see that 2014 has high density in first half. Remember, for 2014 only 36 matches data is considered where as 2010 & 2006 have 64 matches data.
But we can also see the high density of goals in first half for 2006.
If you look at the average wait time for first goal, 2006 is the least with 30 mins and 2014 is in second place.
So if any, we could say 2010 was the world cup of late goals.
Attempt 5: Cumulative % of goals by minute
If a particular world cup has many late goals, then it will show thru when we plot cumulative goal distribution (as a %).
Here is what we get.
From this you can see that 2014 line lags behind 2006 & 2010 for first 60 minutes, before climbing to top place.
This does indicate that 2014 has a lot of late goals.
But the difference is negligible, so we cannot really say much.
What do you think?
I do feel that some of the matches are slow to watch. But this is purely because I have been looking forward to the world cup and could not wait for the action.
What do you think? Do you think this has been a world cup of late goals?
Also, tell me what you think about this analysis? Wow or meh?
About the data
Thanks to Soccer Worldcups & Wikipedia from where I obtained this data.
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13 Responses to “Using pivot tables to find out non performing customers”
To avoid the helper column and the macro, I would transpose the data into the format shown above (Name, Year, Sales). Now I can show more than one year, I can summarize - I can do many more things with it. ASAP Utilities (http://www.asap-utilities.com) has a new experimental feature that can easily transpose the table into the correct format. Much easier in my opinion.
David
Of course with alternative data structure, we can easily setup a slicer based solution so that everything works like clockwork with even less work.
David, I was just about to post the same!
In Contextures site, I remember there's a post on how to do that. Clearly, the way data is layed out on the very beginning is critical to get the best results, and even you may thinkg the original layout is the best way, it is clearly not. And that kind of mistakes are the ones I love ! because it teaches and trains you to avoid them, and how to think on the data structure the next time.
Eventually, you get to that place when you "see" the structure on the moment the client tells you the request, and then, you realized you had an ephiphany, that glorious moment when data is no longer a mistery to you!!!
Rgds,
Chandoo,
If the goal is to see the list of customers who have not business from yearX, I would change the helper column formula to :
=IF(selYear="all",sum(C4:M4),sum(offset(C4:M4,,selyear-2002,1,columns(C4:M4)-selyear+2002)))This formula will sum the sales from Selected Year to 2012.
JMarc
If you are already using a helper column and the combox box runs a macro after it changes, why not just adjust the macro and filter the source data?
Regards
I gotta say, it seems like you are giving 10 answers to 10 questions when your client REALLY wants to know is: "What is the last year "this" customer row had a non-zero Sales QTY?... You're missing the forest for the trees...
Change the helper column to:
=IFERROR(INDEX(tblSales[[#Headers],[Customer name]:[Sales 2012]],0,MATCH(9.99999999999999E+307,tblSales[[#This Row],[Customer name]:[Sales 2012]],1)),"NO SALES")
And yes, since I'm matching off of them for value, I would change the headers to straight "2002" instead of "Sales 2002" but you sort the table on the helper column and then and there you can answer all of your questions.
Hi thanks for this. Just can't figure out how you get the combo box to control the pivot table. Can you please advise?
Cheers
@Kevin.. You are welcome. To insert a combo box, go to Developer ribbon > Insert > form controls > combo box.
For more on various form controls and how to use them, please read this: http://chandoo.org/wp/2011/03/30/form-controls/
Thanks Chandoo. But I know how to insert a combobox, I was more referring to how does in control the year in the pivot table? Or is this obvious? I note that if I select the Selected Year from the PivotTable Field List it says "the field has no itens" whereas this would normally allow you to change the year??
Thanks again
worked it out thanks...
when =data!Q2 changes it changes the value in column N:N and then when you do a refreshall the pivottable vlaues get updated
Still not sure why PivotTable Field List says “the field has no itens"?? I created my own pivot table and could not repeat that.
Hi, I put the sales data in range(F5:P19) and added a column D with the title 'Last sales in year'. After that, in column D for each customer, the simple formula
=2000+MATCH(1000000,E5:P5)
will provide the last year in which that particular customer had any sales, which can than easily be managed by autofilter.
Somewhat longer but perhaps a bit more solid (with the column titles in row 4):
=RIGHT(INDEX($F$4:$P$19,1,MATCH(1000000,F5:P5)),4)
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