Quote:
Originally Posted by Raul
Back to the topic - I did not even look at the algorithm. But if it is using Jim's algorithm used at IRI, then I think it is golden.
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Using the parameters from IRI, it appears that this algorithm produces similar if not better results.
First, here is the explanation from the Saxton algorithm for the aggregated statistics he collects:
Code:
Schedule Statistics
-------------------
#: number of matches played, a '+' after the number
indicates one additional round as a surrogate
d: minimum delta between matches (e.g. '1' means back-to-back)
part: number of distinct partners followed by most frequent repeat count
opp: number of distinct opponents followed by most frequent repeat count
both: number of distinct teams seen as partner or opponent
followed by most frequent combined repeat count
r/b: balance between red and blue alliance appearances
eg, 3b means team appeared as blue 3 times more than as red
4+ repeats: any teams seen four or more times as partners or opponents
team # d part opp both r/b 4+ repeats
---- -- -- ----- ----- ----- --- ------------
And here is the results from Jim's algorithm at IRI (I had to guess a few places because of the inadequacies of FIRST's match lists, and I didn't have the original, but it should be very close, and the only difference would be in the deltas)
Code:
best: 8 11 | 16 1 | 24 1 | 40 1 | 0
worst: 9 6 | 16 1 | 24 1 | 35 2 | 8 (2)
Here is Tom's algorithm at best, default match delta
Code:
best: 8 12 | 16 1 | 24 1 | 39 2 | 0
worst: 8 10 | 16 1 | 20 3 | 28 3 | 2 (28)
Here is Tom's algorithm at best, with 6 minimum match delta, same as Jim's algorithm produced
Code:
best: 8 10 | 16 1 | 24 1 | 40 1 | 0
worst: 8 6 | 16 1 | 24 1 | 38 2 | 2 (32)
With the 6 match min delta, Tom's algorithm allows the worst case team to see 3 more total teams then Jim's algorithm, with everything else being similar or the same. It also eliminates the need for any surrogates with the IRI data set and minimizes it for other data sets.