Re: Rank vs. blue banner chance
 

Thanks for the chairman's rankings. I guess it seems that the top teams on the field are the top teams off the field as well. I would have expected more winners outside the top 8. But very interesting. I think answered my question. Very interesting results.

Just a programmer's 2 cents, try using the D3.js library to visualize data from TBA. It's very extensible and slick.

Re: Rank vs. blue banner chance
 

Disclaimer: When I say throwing a match would be helpful I don't mean that you should do it, I just wanted to know if statistically there are times where you would be in a better position if you threw the match.

Now back to the thread.

Thanks inkling! That's exactly what I was looking for. You can make some interesting observations from those graphs, for instance, I didn't realize how much more likely a #1 seed is to win than a #2 seed. I also think that the graph does show that there is really no situation where throwing a match would be helpful.* And even if it would be, most good teams would see that you threw the match and wouldn't pick you anyway.


*(unless maybe you are #15 and you can drop exactly 2 spots.)

Re: Rank vs. blue banner chance
 

For completeness, here are all blue banner recipients with their seeding position. The data are averaged from 2011-2014. Thanks to team 1114 for use of their scouting database.

There is a nice correlation between ranking high and number of Chairman's or EI wins. The data for RAS are much more scattered. I'm not sure that the RAS graph actually says much of anything. Looking at this graph without fully understanding it might imply that it is better for rookies to seed lower at an event if they want to win RAS. However, that would be a false conclusion since rookies are generally not uniformly distributed throughout the seeds at an event.

EDIT: mislabeled axes, see next post

Re: Rank vs. blue banner chance
 

I mislabeled the axes on the spreadsheet from my last post.

This one makes more sense.

Re: Rank vs. blue banner chance
 

I see that differently, looks like teams that win Chairman's may or may not have a good robot. Which makes sense, since the award is more about community, outreach, spreading STEM vs robot on the field. Top teams have gotten into the swing of "We build great Robots and now that we got that, we can look at our real mission". Some teams are the other way.

Chairman's teams are amazing. I listen to the regional awards and it's amazing the things they do. Homeless, elderly, cancer, disabled, learning, other countries ....

Roboteers Rock!

Re: Rank vs. blue banner chance
 

I took your data and divided the number of position winners by total winners/3 to get an idea of the probability of being on the winning alliance based off of ranking position. An interesting (though not unexpected) finding was that typically, #1 position was above 60% likelihood of winning. This makes sense because the #1 ranking spot means you are likely either the best or can pick the best.
I think you can judge the 3 team engagement and/or ranking system by how high the #1 position is. For instance, 2011 (0.66) and 2012 (0.61) were games that could usually be won by 2 really good bots. I am not saying the 3rd did nothing, they were just a significantly lower contributor, and weren't as required to do well (ignoring World champions which had an incredibly influential 3rd partner). For the 2013 (0.56) game, a powerful 3 could overcome a very strong 2 which shows a dip in that probability of the #1 spot as well as the #2 spot. 2014 was even lower with the #1 dipping below 50% (0.49). This is likely the first time since 3v3 that this has occurred. This also makes sense as for 2014, at most regionals, you needed a decent third partner could help overcome a 2 strong team alliance.

For me personally, games like 2013 hit the balance just right for a serpentine style draft. I almost felt that 2014 shifted the balance a bit too much. If I had time, I would love to see difference between events with more than 40 teams and events with 40 and under to see if there is a significant trend difference there.