Season 8 Stopwatch Time Sheet#902
This spreadsheet collects data from invite scrims (and eventually matches) in order to give anyone who is curious the information about the average capture times, with a (n assumed) normal distribution to give some sense on what times are good / bad.
As of right now, only upward is filled with “significant” data, as that is the first week of play, and the data will change overall even by next week as there will be much more data to input.
You can search by map by clicking on the tabs at the bottom of the page.
How to read this spreadsheet:
The offense team column is the team that set the time
The K column after the offense team is the kills that team got on their attack
The K:K column gives a ratio between the kills from the attacking team to the defending team. I want to see if there is a straightforward correlation between kill ratios and cap times.
The K column before the defense team is the kills the defending team got
The defense team is… the defending team.
Time is the time the offense team set. (Taken into account for set up time)
Avg time, Stddev, Slowest, Fastest should be as self explanatory as the other columns
The Map Rundown gives the setup time, as well as the fastest possible cap times for each point at x3. This should be used in order to help teams realize if they have enough time to push or not and whatever.
Assuming normal distribution column(s) give the average time, as well as the 1st-3rd standard deviations on both sides of the average to give a sense of what times are good or bad.
god damn sand hats off to u for making this, actually cool to look at and im looking forward to seeing more as the season progresses
This is so cool. Love that you made this.
good work, also lets go i got the slowest time so far last night
I’m not a statistician, so I know nothing about it – is it normal to drop outlier values? What kind of “impossible times” would be produced?
Interesting sheet. I’d be really curious to see it for other divs and see the averages between different skill levels
@scaredy-bat No, generally it is not a good idea to drop outlier values. I did so only so that the chart that tells what times are good/bad would make sense. For example, the current pl_vigil tab has a negative 2 minute time for “very fast”. Similar things like that happened when the very long rounds were input into the upward tab as well, even with that many data points. I guess I could add them but that table on the right would be totally off
Vigil times are updated, use the link in OP and navigate through the maps using the tabs at the bottom of the window
Also, I kept the outliers in the data this week, to show what I meant when the normal distribution chart isn’t accurate
Grazie! Very weird. I wonder how statisticians deal with this kind of thing when analyzing other kinds of things.