The goal is to set up my next league (which starts tonight) so that each foursome is actually two teams battling it out, and comparing combined scores. (Overall league standings (for WPPRs) will still be based on individual results, but your team record, which comes from the handicapped matchups, will be used for end of the season goodies/benefits).
I’ve been doing some math with my results from last season. To come up with a handicap, I took each score for each player for each game, and compared it to the average score for all players for that game (for the same night only, some games were repeated on later nights).
So, each player got a “% of average score” handicap number. These ranged from 216% down to 45%. So, the 216% means: “that player, on average, is expected to score 216% of the league average score for a given game”, ie - a little more than double the average score. The 45% means that player scored roughly half of the average.
I spent a lot of time worrying about things like: What about when someone really blows up a game? Does that artificially inflate their handicap? Does it screw up all the numbers? Why did the best player have 201% but the second best player had 216%? Etc.
I looked at a few things (like removing the 2 best scores), didn’t find anything conclusive, and then finally just gave up and created some what if scenarios from last season. I’d create matchups where the combined “% of average score” was roughly even between the two teams.
Long story short, this created remarkably even matches. It worked when high players were paired with low players. It worked when medium players were paired with medium players. It worked with the best and worst, against the 3rd and 4th. And by worked, I mean: every matchup was either dead even (like 15 wins for one team, and 15 for the other team), or off by one (17 wins for one team, and 18 wins for the other team). I was simulating it as if those same two teams faced off every week of the season.
Even doing Canadian doubles, one player against two, worked pretty well. I tested 216% (best player) vs 123% (3rd ranked) & 96% (7th ranked). That matchup ended up 18-22.
1st vs 4th and 5th, actually was 17-13 in favor of the top player.
(I thought everything was suspiciously close, so I tested several uneven pairings also, and did indeed find the expected landslide victories).
These simulations were just for ease of coding. In the real league, you’d have a different teammate each week…but an even matchup vs the other team, regardless of who is in the foursome. (Foursomes would be sculpted a bit to ensure this).
So, I’m going to move forward with this (league starts tonight). I’m pretty confident that even with uneven numbers of players, I can create relatively even matchups.
Will post again here with updates.