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project details

Our team of interns was tasked with build­ing a data visu­al­iza­tion plat­form (now called STATS Info­graph­ics) that allowed STATS to bet­ter lever­age their rich data into prod­ucts for media clients in an auto­mat­ed way.

sec­ondary research

This ini­tial­ly entailed sec­ondary research of how oth­ers in the sports ana­lyt­ics indus­try were lever­ag­ing data visu­al­iza­tions. Through that research, we found visu­al­iza­tions fell on a spec­trum of acces­si­bil­i­ty and the poten­tial length of engage­ment.  STAT­S’s next-gen data had the poten­tial for engage­ment but was often glossed over by the casu­al fans. This helped iden­ti­fy a clear design direc­tion for the plat­form — pro­vid­ing STAT­S’s next-gen data in easy to digest info­graph­ics with a short engagement-time. 

user test­ing & insights

We made var­i­ous info­graph­ic mock-ups in Sketch that was pre­sent­ed to users. The imme­di­ate ten­sion we found was that a data visu­al­iza­tion by itself was dif­fi­cult for peo­ple to under­stand in the con­text of sports — indi­vid­u­als that deal with com­plex data on a dai­ly basis had dif­fi­cul­ty in apply­ing that same rig­or to sim­pler charts shown in the con­text of sports. 

Syn­the­siz­ing that research helped sharp­en our design direc­tion by iden­ti­fy­ing three key com­po­nents that would ease the bar­ri­er to engagement.

Scaf­fold­ing the infor­ma­tion with a nar­ra­tive was par­tic­u­lar­ly cru­cial in typ­ing the entire visu­al­iza­tion togeth­er, and it was impor­tant that nar­ra­tive was deliv­ered in a sports-appro­pri­ate lan­guage. To under­stand the con­ver­sa­tion­al struc­tur­al of sports talk we con­duct­ed inter­cept inter­views where we’d sim­ply talk to peo­ple about their favorite teams. By under­stand­ing the con­ver­sa­tion­al UI of sports nar­ra­tives, we were able to break them down into their com­po­nent forms.

devel­op­ment

Hav­ing final­ized a design direc­tion, I devel­oped a plat­form via Python that took basic user input and queried the appro­pri­ate data, c (Word­Smith Areat­ed a visu­al­iza­tion, and wrapped into an appro­pri­ate aes­thet­ic. It lever­aged an NLP toolI) to turn the queried data into the sports nar­ra­tive struc­ture researched earlier.

I went back to user test­ing to under­stand the con­ver­sa­tion­al struc­tur­al of sports water cool­er talk. By under­stand­ing the con­ver­sa­tion­al UI of sports nar­ra­tives, I was able to break them down into their com­po­nent forms that allowed me to lever­age an NLP tool and attach the final piece to the info­graph­ic platform.

Which league would you like to see: Eng­lish Pre­mier League

Which match­week: 25

Which Brand: Nike

The final tool was able to take sim­ple text input as shown above and turn it into 50+ top­i­cal sports info­graph­ics in a mat­ter of minutes.

out­come

At the end of the intern­ship, our team pitched the alpha pro­to­type we built to STATS C‑Suite.

 

The prod­uct has since tak­en on the title STATS Info­graph­ics and has moved into devel­op­ment with a slat­ed release date of mid-2017.

select­ed work

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