After reading much discussion about matches "decided by fouls" in the 2014 game, I wondered how the overall percentage of such games compared with past years. I found one early season report of "about 10%", and a few more detailed analyses. While I'm sure the latter contain the information, I wasn't up to going through the trees to find the forest I was looking for, so I wrote the attached program, with the results below. I defined a "decisive" scoring component (autonomous, teleoperated, endgame, or foul points) as one which would have changed the match outcome (won/lost/tied) had it been zero. Percentages are the percentage of matches for which each scoring component met this criterion. Matches where the individual components failed to add up to the total for either team were ignored.
Qualification matches:
Code:
> java -Dtype=Q CSVStats *csv
type Q
file 2012_Twitter_weeks_1_thru_8.csv
matches 5738 (6 ignored)
foul 385 7%
hybrid 1831 32%
teleop 1721 30%
end 1299 23%
file 2013_Twitter.csv
matches 6617 (5 ignored)
foul 359 5%
hybrid 2249 34%
teleop 2790 42%
end 1904 29%
file 2014_twitter.csv
matches 8300 (11 ignored)
foul 1057 13%
hybrid 3004 36%
teleop 4980 60%
end 0 0%
Eliminations:
Code:
> java -Dtype=E CSVStats *csv
type E
file 2012_Twitter_weeks_1_thru_8.csv
matches 1065 (13 ignored)
foul 63 6%
hybrid 449 42%
teleop 460 43%
end 449 42%
file 2013_Twitter.csv
matches 1236 (10 ignored)
foul 69 6%
hybrid 654 53%
teleop 821 66%
end 466 38%
file 2014_twitter.csv
matches 1533 (10 ignored)
foul 181 12%
hybrid 749 49%
teleop 1243 81%
end 0 0%
Both:
Code:
> java CSVStats *csv
type QE
file 2012_Twitter_weeks_1_thru_8.csv
matches 6803 (19 ignored)
foul 448 7%
hybrid 2280 34%
teleop 2181 32%
end 1748 26%
file 2013_Twitter.csv
matches 7853 (15 ignored)
foul 428 5%
hybrid 2903 37%
teleop 3611 46%
end 2370 30%
file 2014_twitter.csv
matches 9833 (21 ignored)
foul 1238 13%
hybrid 3753 38%
teleop 6223 63%
end 0 0%