Dont think of me as a perverted spreadsheet user, I like visualizations in any form or shape. There is so much data even about human relationships like love and sex. This article shows 10 of the most visually beautiful and insightful of the infographics on sex and love.
Click on the titles above images to see the detailed site. The links are mostly safe for work, so enjoy the Friday 🙂
1. Charting the Dating Data – Dizzia’s Dates
What happens when you take all your dating data and plot it on a calendar by using icons for what happened during each relationship? Dizzia got curious and did just that. This is an awesome visualization with lot of wit and simplicity. You can quickly tell how long each relationship lasted and what they have done.
2. How does Love look like?
Ever wondered how the emotion Love actually looks? What happens when you try to plot love? Emotionally Vague has conducted surveys on people to find out the color, words, body parts associated with love and plotted this information in the above seen beautiful info-graphic. Very pretty and insightful.
3. Personal sex data goes web2.0 – Bed Posted
Have you ever wondered how your sex life is progressing? Not in an emotional way, but in the way like tracking monthly budget? BedPosted promises to give you insights into your sex life. Whenever you log in just feed little data about your intimate activities to this site and leave it to come up visualizations like one seen above. Another fun way to look at your data.
4. What to say during sex – Flow chart of things to say
This is a funny flow chart of things to say during xxx. Easy to understand and fun to read.
5. What do we search for – Love or Sex? – Google Search Insights
I like the google search insights because they work like a dashboard by providing all critical info in one place. This one works the same way. Looks like the S word beats L word here. The google search insights shows us that when it comes to love western part of the world is searching more for it where as for sex, it is the eastern part which is searching more. Also, the S searches outnumber L searches thrice.
6. What are people loving right now – Twitter tweets on Love
Twistori is more like a social experiment, a window through which you see how humanity (the tweeting kind) is feeling. The above shows a snapshot of what people love. It is a simple text visualization that is pretty to watch.
7. What is the right size?
The above is a very good example of partition chart in which spatial trends are meaningful. It shows preferences of several women plotted to reveal where the pleasure is. Okay, enough detail, I leave it to you to interpret.
8. [NSFW] Who does it most? – Durex sexual well being survey 2007
[NSFW] Durex sexual well being survey is an annual affair in which they reveal trends across the globe. I believe it is part of their business continuity plans. The above shown is a map visualization of sexual frequency across globe. You can see who is busy.
9. [NSFW] Fleshmap – Touching Preferences
Fleshmap [NSFW], which is featured here earlier, is an incredibly cool way to plot intimate data. They have gathered data about touching, looking and listening and plotted it in several creative ways. The site is full of insights. But do not browse from work as some of the charts are pretty graphic.
10. [NSFW] Playboy Centerfold Images – How they have looked from 1960 to 1990
This is clever visualization and art work. Jason Salavon took centerfold images from all the playboy magazines between 1960 and 1990 and scanned these images. Then he normalized the data to create the above images. Even though it doesn’t mean anything on the outset, when you know how the image is generated you would marvel at the thought of it.
Bonus: Viagra sales cartoon
This is as funny as graphs can get.
Like these visualizations? Why don’t you browse some of the coolest visualizations featured here earlier.
Have a great weekend 🙂
19 Responses to “How to Distribute Players Between Teams – Evenly”
An excellent solution, especially for large data sets.
Another solution without using solver would be to assign the player with the highest score to Team 1, the 2nd to team 2, 3rd to team 3, 4th to team 3, 5th to team 2, 6th to team 1, 7th to team 1 and it continues. This method would end up with a Std Dev of 0.001247219. This works best with a distribution with lower Std Dev for the dataset.
Full Disclosure: this is not my idea, remember reading something a few years ago. Think it may have been Ozgrid
thinking back I now remember why I read about it. About 10 years back I had to distribute around 300 team members into 25-30 odd teams. Used this method based on their performance scores. I used the method I described to do this and the distribution was pretty fair.
Solver would have saved me a ton of time though 🙂
I think the issue with you first Solver approach was that you took the absolute value of the sum of team deviations (which should always be zero except for rounding) instead of the sum of the absolute values (which is a reasonable measure of how unbalanced the teams are).
Here's another simple algorithm you could use: you start from the top (with players sorted from high to low), and at each step allocate the next player to whichever team has the smallest total so far. You can implement it dynamically with some formulas so it will update automatically when the data changes.
If the scores were more widely distributed (so that this might end up with not all teams the same size), you could add a constraint to only pick among the teams which currently have fewest players at each step, or just stop adding to any team when it hits its quota.
When I tried it on the sample, I got the three teams below, with a STDEV of 0.000942809 (i.e. about half of what Solver got to).
Team 1: John, Hugo, Tom, Josh, Eric, Zane, Charles, Andrew
Team 2: Barry, Michael, Kenny, Joe, Xavier, Patrick, Oliver, William
Team 3: Henry, Steven, Ben, Frank, Kyle, Edward, Cameron, Lachlan
Thanks for sharing!
Hi,
I was looking at all the solutions and this is closest to what I intended to do. I am dividing a bunch of players into 3 soccer teams. Players availability is also a factor while deciding the teams.
So the steps the excel needs to do is as follows:
1) In availability column if "yes" go to next
2) Equally divide 'Goalkeepers', 'Strikers', 'Defenders' basis their quality
So the end result gives each 3 teams a balance of players playing at different positions.
Can this be done on Google spreadsheet with only availability as an input from the user and rest calculates by itself.
Sorry for asking such a pointed question, but I have been struggling to find a solution for it for sometime now!
Hi Ishaan,
I am working on a similar problem at the moment, so I am wondering if you ever found a solution and if you are willing to share what you did.
Hi everyone, this is a variation of the famous Knapsack Problem https://en.wikipedia.org/wiki/Knapsack_problem.
I had to use a VBA implementation recently as part of a problem, where we ar trying to allocate teams of an organization into different locations (we are a large company with many different team). The goal was to optimally allocate teams to individual buildings without putting too many teams into one building and not splitting teams apart.
As we had around 400 teams of different sizes, solver couldn't handle it anymore. Luckily there is a Knapsack algorithm implementation in VBA readily available on the internet :).
I also went with a heuristic approach first!
An interesting mathematical solution but what if Eric and Xavier can't stand each other or Patrick is best friends with Steven - the real life problems that effect "even" teams.
@Joe
You can add more criteria like
If Eric and Xavier can't stand each other
=OR(AND(E15=1,E16=1),AND(F15=1,F16=1),AND(G15=1,G16=1))
It must be False
If Patrick is best friends with Steven
=OR(AND(E5=1,E17=1),AND(F5=1,F17=1),AND(G5=1,G17=1))
It must be True
Note that the 2 formulas above are exactly the same
except for the ranges
One must be True = Friends
One must be False = Not Friends
Nice Post!
Just one question What if number of players are not even or equally divisible.
Nice post Hui!
I download your workbook and just try to change in options the Precision Restriction from 10E-6 to 10-8 and the Convergence from 10E-4 to 10E-10. The process take almost the same time, but the results was great.
The standard deviation I got was 0,000471.
Team 1: John, Tom, Kenny, Frank, Eric, Xavier, Edward, Zane
Team 2: Steven, Hugo, Ben, Joe, Josh, Oliver, Cameron, William
Team 3: Barry, Henry, Michael, Kyle, Patrick, Charles, Andrew, Lachlan
Great application of Solver! Thanks for the link!
Great explanation. Well done... However, I tried with 6 teams of 4 players and solver never did finish.
How about vba code for the same data set.
I have 3 column A B C wherein A has text and B has number Wherein C is blank. And in C1 been the header C2 where I want the name to come evenly distributed the number which is in Column B.
My Lastcolumn is 1000.
Sorry if I'm being slow here, but how is 'Team Score' calculated? I've gone through the explanation several times but it seems to just appear.
@Hrmft
This process uses the Solver Excel addin
Solver is effectively taking the model and trying different solutions until it gets a solution that meets all the criteria
Then solver puts the solution into the cell and moves to the next cell
So yes it appears to "just appear"
Hi ! Thank you so much ! Works great 🙂
I cannot get the fourth Equation to work in my excel spreadsheet
You have =($E$2:$G$25=0)+($E$2:$G$25=1)=1 as a SUMIF solution, I have, =($F$2:$H$13=0)+($F$2:$H$13=1)=1 as my solution but it does not work. The only thing I changed is the ranges. Any suggestions?
Thank you.
Jim
I cannot get the fourth Equation of TURE or FALSE statements to work in my excel spreadsheet You have =($E$2:$G$25=0)+($E$2:$G$25=1)=1 as a SUMIF solution, I have, =($F$2:$H$13=0)+($F$2:$H$13=1)=1 as my solution but it does not work. The only thing I changed is the ranges. Any suggestions?
Sorry I left some of it out in the previous question,
Thank you. Jim