Each season brings unending debate over player contributions (or detractions.) I have all boxscore data for the season for our team in a massivespreadsheet filled with multiple nested calculations. I came up with some new stats you might like to see. For example, I compute percentage of game time versus percentage of points, which reveals who can fill it up the fastest. (Hint: It's not always the leading team scorer.)
In this post I'd like to present my new stat "Impact". I created it, but you can help make it a useful stat.
Typical boxscore data: Min FGm FGA 3PM 3PA FTM FTA OR DR TR AST TO STL BLK PF and PTS.
Combinable data: date, location, game prominence (regular season versus conference play versus big dance, et al.), team and opponent RPI & ranking,
To measure a player's impact more comprehensively, I combined all the above data into one calculated stat. Whichever team has the higher PTS wins, right? So I use PTS as the baseline.
Other stats affect PTS. For example, a BLK prevents PTS for the other team, right? We can just add that to our stat: Impact=PTS+BLK
Some BLKs may not have stopped a score, and those that do vary between 2 or 3 point shots which might, or might not, have gone in. So apply some common sense factoring for that. Most shots are 2s (except in Louisville) and most don't go in. So intead of a BLK being equal to 2 or 3, it's really more like 0.4 PTS on average.
Whether it should be .4, .24, 1.1 or whatever; that decision can be debated or refined later. I'd be happy (and easily able to) to improve this stat with discussion and tweaking. So here is the starting list of calculations included in 'Impact' version 1.0.
BLK add .4 of a point; this leads to probable PTS
OR add .3 of a point; this leads to probable PTS
DR add .5 of a point; reduces possible OPP PTS leads to possible PTS
ASTadd .6 of a point, because these lead to PTS
TO minus 1 point, because this reduces possible PTS and leads to possible OPP PTS
STL add .6 of a point, because this leads to possible PTS
PF minus .3 of a point
If the player's game impact is significant (to be defined), add:
1 for conference win
1.5 for conference road win
2.2 for conference tourn win earlier than semi
2.4 for conference tourn semi
2.8 for conference tourn final win
3.1 for NCAA round 1 win
3.3 for NCAA round 2 win
3.4 for NCAA round 3 win
3.6 for NCAA round 4 win
3.8 for NCAA round 5 win (FF)
4.4 for NCAA round 6 win
5 for NCAA round 7 (Title)
Increase 10% if it was a ranked opponent
Increase 10% if it was a road game
Increase 10% if it was a conference game
Increase 10% if it was a conference road game
if player shot less than 30 FG%, minus .5 PTS per miss
If a player had more TO than AST, minus 10%
Yeah, this could go on and on.
But you can't always tell the wisdom in using (or not) each calc. It's best to look at the results, and then start tweaking where it makes sense based on the results. Here are the results:
Relative to each game, do you agree these are the top impactful performances among our team this season?
Here's what the bottom looks like: (And no, I didn't connive to ensure Marra got the worst score; that's all on him.)