At the events, teams are randomly paired with other teams to create alliances and score as many points as they can. This means that some teams will get put with other teams multiple times, and other teams will never see that team.
This puts some teams at a disadvantage. If they never get matched with the best robot, there score will probably never be that good. So for the teams that were paired multiple times with that robot, their scores will be so much better, and if they are continuously paired with robots better than them, their ranking will actually be better than they deserve.
What I am proposing is to make the competitions so that each team gets paired with each of the other teams once No more, no less. Everyone is on the same alliance with all of the other teams at one point or another.
This would show the true value of the robot of the team instead of the possibility of a robot being carried into a high seed simply because of their alliance partners in Qualifications.
I realize this would result in longer competitions and scheduling would be more difficult, but that would be a true and fair representation of the robot instead of the robot’s alliance partners.
Currently, there is an algorithm that decides match scheduling, at least for regionals, and it tries to do just that. However, minimizing repeated alliance partners / opponents is only second order sort behind maximizing time between matches. Also, I worry that for the larger events, it may be unreasonable to do so many matches, and scheduling would be difficult without a significant number of surrogates. Unsure how this works at districts, though, but I presume the algorithm is the same.
At District events, where the standard is 40 teams, we would need to play 20 matches per team to ensure that every team gets to play with every other team. That would add 67% to the qualifying schedule, requiring an additional day.
While I would have loved to play the required 32 qualifications to make this possible at the Lake Superior Regional, we only had time to play 9 in our normal 3 day event. A week of qualification matches would sure be fun, but I doubt many schools would like how many extra missed days this would add up to
At Bayou, we had 59 teams, so each team would have to play 29 matches, which would be a 222% increase in the qualifying schedule, requiring at least two additional (and longer) days, more likely three.
The same scheduling algorithm is used in Districts and Regionals.
I don’t think your description of the algorithm is correct. The cost function at the core of the optimization procedure prioritizes minimizing repeated alliance partners over repeated opponents. Time between matches is not part of the cost function at all, but the algorithm only considers solutions that satisfy a minimum match separation.
After generating the schedule the FMS provides overall statistics, which in my experience at District sized events does typically show the maximum number of distinct partners for most teams.
The algorithm begins by seeding the match schedule with the simplest possible schedule: the teams are dumped in the schedule sequentially in the exact same order for every round. Thereafter, teams are only rearranged within rounds. This guarantees the round uniformity requirement: no schedule that breaks the round uniformity requirement is ever even generated.
When running the algorithm, the minimum match separation is specified. The algorithm ensures that no team is forced to play two matches with less than the minimum match separation. This is also handled up front by the way teams are permuted within rounds: no permutation that would violate the minimum match separation is allowed. No schedules violating the requirement are ever considered as candidates. No other consideration is given to match separation, so one team might have the average separation between each pair of appearances and another might have half at the minimum and the other half widely separated.
The most interesting part of the puzzle is pairing uniformity. This is handled by the simulated annealing. There is a “current” schedule, which is initially the simple schedule described above. In each iteration of the algorithm, the current schedule is slightly modified by permuting some teams around as described above.
Each schedule generated, which is guaranteed to satisfy the first two criteria, is assigned a score based on the amount of partner and opponent duplication. For each team, we count the number of times that team (in a non-surrogate match) sees each other team as a partner, as an opponent, or in either role. Penalty points are added for each duplication, doubled by each additional time a given team is seen in any category. The weighting for duplication in partners is slightly heavier than for opponents, since there are only two partners, but three opponents, per round.
If the newly generated schedule has a better score than the “current” schedule from which it was derived, it becomes the current schedule. If this were the only way in which the current schedule changed, it would be possible to get into a “local valley” where we get stuck with a poor solution which is structured so that it’s just a little better than any “nearby” schedule which can be obtained by the permutation procedure. To solve this problem, simulated annealing allows for a small chance of replacing the current schedule with a worse schedule, with the probably decreasing exponentially with how much worse the new schedule is. This will cause the algorithm to jump out of a local valley where no forward progress is being made over many iterations.
In addition to the “current” schedule, there’s also a “best” schedule which is updated any time we find a new schedule better than the previous best. This is to make sure that we used the best schedule encountered even if the algorithm happens to randomly climb uphill from the best solution while trying to find a deeper valley.
The final step is to analyze the red/blue balancing and to swap sides on the matches in the final “best” schedule to even out the balancing as much as possible. Notice that this swapping doesn’t alter any of the other criteria, since no team moves to a different match or changes partners.
In my experience, the algorithm has done a pretty good job of making sure all teams have the same numbers of partners and the same number of opponents (which is the metric FMS reports), even at smaller district events.
At WVROX, we played just about every single iteration of the 24 teams on the field. Granted, running 24 hours will do that for you. We had a long cycle time, but still ran so that every team played against and with every team, multiple times.
As far as my experience, at most events, you will not see repeats. I think the only repeats we have seen on our team that I can think of were due to surrogate matches. At most events, we don’t even get to see every team on the field (whether for or against), so we actually see no repeats.
At the five events I worked at I can’t recall any repeats.
In fact the last time I recall something like that happening was 2007 and I believe it caused FIRST to fix the scheduling algorithm so that wouldn’t happen anymore.
Good memory, Ed. 2007 brought us the Match Schedule Algorithm of Death. Paul and John were very quick to bring the issue to my attention as a Week 1 FTA that year. It caused quite a stir, and everyone I have talked with was very glad to see FIRST HQ correct it.
This is generally true. However, better alliances are formed when the strongest teams seed highest. Scheduling algorithms were improved several years ago to help with this. The District-era trend toward 40-team fields and 12 match schedules helps even more.
Jim Zondag will gladly say more about this, if asked. He has a lot of data.
I think the event I remember the most glaring was Florida. Pink was scheduled four different times against Shark Attack who that year was a Pink killer and practically drove them into last place with their relentless defense.
While I generally agree with the new algorithm and wistfully consider the possibility of playing against every team and with being allied with every team, I have seen personally a number of times when it appears the current algorithm breaks.
Last year we had a schedule where we were paired against the same team 3 times and never with them in our alliance.
This year it happened again with the two highest seeded teams (by unlucky coincidence), we were only paired with one of the top two teams once, but played against them multiple times.
I understand the algorithm and the concept of the optimization methods. However in this case it appears that the cost function must have really been skewed to generate these schedules. I need to build an analytic model of the cost function and see what exactly happened. Maybe when I get some time to breath again
Some teams get an “easy” match schedule…some teams get a “tough” match schedule. It’s been like that for a long time. There really isn’t any any way to “fix” this, and I don’t see any reason to try. The teams that are really good will end up at the top of the rankings after enough matches have been played, likewise the teams that just aren’t doing very well will end up lower.
As mentioned, if you are relying on your alliance partners during qualifying matches, you’re probably not going to do very well. We learned a long time ago that we have to be able to hold our own in every qualifying match, if we expect to rank high and pick our own alliance.
Also this year the coopertition thing moves up some of the better (but not best) robots a bit higher than they might ought to be. So…if you want to move yourself up in the rankings, and your robot is decent but not the best, concentrate on getting the coop bonus as often as you can.
But don’t be surprised if you drop out in the quarterfinals.
As a whole, I really like the current scheduling. It seems pretty fair and easy to follow. My only gripe with the system is that we have been consistently against the same team at multiple events in the last two years.
In 2014, at Oregon City we were against 2471 3 times but never with them
In 2015, at Wilsonville we were against 2471 3 times and with them once.
At Philomath, we were against 1983 4 times but never with them.
Now I don’t particularly mind that we get the schedule we do (especially this year), but it would be fun and beneficial to play with teams occasionally instead of always against them. This isn’t to say the system is broken, it isn’t, just that we haven’t had the best luck with match scheduling.
The biggest disappointment for me is arriving to competition. Seeing all the cool robots and planning out in my head “Oh man we will work so well with that team and that team and that team.” Only to get the schedule and end up with no “fun” matches.
This isn’t to say we didn’t have matches with good teams, it just felt like we had matches with teams where roles overlapped so we didn’t get to play to our full potential.
At Purdue we went against 234 three times and were with them zero times. It was funny because the strategist for 234 kept coming to our pits to organize coop and he was over enough times for it to seem odd when he wasn’t.