Thanks for a great 2 years. This one is going away.
Our new website is: www.thecrunchzone.com.
Make sure to book mark us!
We have hit 5 post season games, so I am kicking out a TVT to show how this team has re-defined itself. Literally overnight they have turned their season long production averages upside down.
TVT: net positive production per minute. Add up the good stuff, subtract the bad stuff, divide by minutes played. Breaks every player down to a single number – “When you play for 1 minute, you gain the cardinals “x” net positive contributions per minute. If you had a score of 1.0, that would be 1 net positive stat per minute. that is hard to do. .40, means you contribute a net positive stat in just over 2 minutes.
The most insane change in production? Team average has sky-rocketed.
Pretty Consistant right? Look at the number below. Insane.
Comparison graph by Category + Last five games by individual
Game prediction: Cards 78, Ducks 71. Pitino challenges Dieng on the glass, he responds. Dieng goes for double digit rebounds (he has been only averaging 5 in NCAA so far).
Which conferences are hot at the right time?
I break it down round by round, and again for a total score all rounds.
Scoring: I had to change scoring. I intended it to be a “per team” value, since some conferences have 8 bids and others 2. Trying to avoid sheer volume from driving the winner. Scoring in a nutshell; add up the wins, give a bonus if an upset win, subtract points for an upset loss, and divide score by how many teams are playing in that round.
What I show
1. Raw totals: bids, wins, losses, and % of upsets (win or lose). One thing I like to look at is wins per bid. The Raw total will show ho many total wins so far int he tourney, and you can see if bids are pulling their weight. Example: A-10 has 7 wins from 5 bids. Mountain West has 2 wins from their 5 bids.
2. Conference Score Card Cumulative: A-10 was the big winner in RD64 (6-0), but in the RD 32 they went 1-5, with a pair of upset losses. Their total score will be adding both rounds point totals together. As teams advance (or disappear) the point totals change. In RD32, Pac-12 had only 2 wins, but they were both upset wins, so that is factored into their score.
3. Per Round Performance: How the selected conferences did per round. I didn’t grab all conferences. CUSA and MVC were left off, MVC did the best between those 2.
Another metric to watch: Another thing to note is “% of the field”. This helps give you an idea of how a conference is doing. They get % of the field as bids, and they either maintain, or fall behind as the tourney progresses. This will help stop the over generalized “they get all those bids, and all they do is lose” arguments. A conference cannot expect all their teams to advance to the Sweet 16, so this alongside Upset Win (UW%) / Upset Loss (UL%) help make sense of that. Upset %’s are “when they win, X% are upsets wins”, and the same goes for losses.
Raw Totals (win/loss & Upset %’s).
Conference Score Card (RD 64 + RD 32)
Round 32 Resume
Round 64 Resume
Mashup of the first 2 games for the Cards.
A-10 huge winner in the round of 64 with 5 bids-6 wins, and 50% of their wins coming by upset.
Big East big loser with 8 bids – 3 wins, and 60% of their losses were via being upset.
It is a long tourney, so we will see how conferences fair each round and overall. Does the Big East stink? Nope, they have had 3 months to prove they win basketball games, and they do, but they certainly are having a bad round of 64 this week.
Raw: RD of 64 Results
This will be the same as above this round, since only 1 round has been played. I added any “first 4” to this group (La Salle, Boise St). Next round, this table will accumulate, as the above table will only be round specific.
Add this, subtract that, and a little of this, and walaa – Big East, you dropped a bomb first round. Time to make up for that in the coming rounds. Sorted best rd of 64 to worst.
Let’s hope the Big East steps up in the Round of 32. Game on.