So how about a different Pinburgh topic… the point spread.
Pinburgh is a match play tournament… which I assume is the origin of the 3-2-1-0 scoring format. Simply put… it’s how many people you beat. Coincidence, or design? @bkerins?
But as we’ve seen year after year… the scoring results in incredibly TIGHT bands between players and division cutoffs. Where B division is a 3 point spread entirely (ignoring those dragged up by restrictions)… and the difference between a C qualifier and an A qualifier is only 4 points… 4 places out of a possible 60… or another way… 1-2 games out of 20 played can be the difference between almost 200 places in the rank. So in practice, just 4 out of 60 points (~6%) is the difference between A and C. Or another way… just 10 points (~17%) is the difference between 58% of the field (467 players).
The question I propose is… is this ‘massing at the middle’ the best outcome?
When you look at the point total distribution… it’s largely as you would expect for an ‘average’ minus the top 10 or so of players pulling away. (half points were rounded down here for better viewing)
Would it be better… to create more separation in the player totals by making scoring less linear? Without easier access to the match data, this is not worth the manual effort to simulate… but I assume the math geeks may have done this already?
Would scoring matches something like 0-1-3-5 or 0-1-2-4 significantly change the spreads… and would it be a meaningful change resulting spreading out the player outcomes?
Edit: note this analysis was done initially based on the open qualifying. It may be more interesting to compare results once you are in the divisions too… but computing those match totals is less convenient with the data on-hand.
Edit Note 2: This is done with almost zero checking of the data for errors… so be gentle if I screwed up