Hi! So you guys might have seen my other thread that called Scouting Help, that has 1.2k views, which kind of blows my mind. But, I’ve looked into it and someone said something about it on my thread and it’s simbucks. It’s a fake currency used by another robotics team that is gambeling and betting on the outcome of a match. I was wondering if anyone used the system or something like that, and how it works, does it work well or not, and if there are any specifics I’m not seeings.
Thanks!
Thanks! I’ve seen this before but haven’t watched the part on Simbucks. I was wondering if anyone had first hand experience with simbucks or other.
On the team that I am on, we have done something a little similar to using Simbucks for the past 2 years. Before each match, each scout is allowed to choose which alliance they think will win the match. Then, at the end of the tournament, whoever guessed the correct outcome for the highest percent of matches wins candy from one of our mentors. This is not exactly like Simbucks, but it still works really well.
If your team is doing “bets” on each match, there’s quite a lot of data in the collective knowledge of your team (or maybe just the good betters!) An interesting parallel to this is the data journalism website fivethirtyeight has been letting readers compete against its algorithm this year for NFL games. On average, the very simple ELO model has been better than the average reader, all who should be considered quite qualified observers. Some people have been beating the model pretty consistently. Some of this comes from noise – in any random distribution, some darts will land on the higher side of the curve. But some of this is real signal, and comes from knowledge of things the model does not – injured players, or teams resting their starters. And perhaps there are some great football minds out there. That said, imagine an ELO model with information about major injuries. I think it would be pretty hard for even the best player to beat!
I’d be interested in how the power of simbucks could be used to create an “informed OPR” that is more accurate than the standard statistic.
I think it would be very interesting to see if it works, I’m thinking of implementing it for our second competition because we are putting in a new system for scouting in general so I think if we were going to add in a new addition into our scouting systems I would like to make sure our system works first.