Arkansas and St John's made a combined 6 of their 48 makes outside the paint, including only 1 each in the second half. They shot a combined 4/40 from 3.

St John's wasn't efficient enough in the paint to keep up and couldn't make a 3 to catch up.

#Arkansas #MarchMadness

My ML models flagged (9) Creighton from the South Region and (8) Gonzaga from the Midwest Region as sleeper teams to make a run.

Expect them to push 1 seeds Auburn and Houston today.

#MarchMadness #Creighton #Gonzaga #Auburn #Houston

My ML model didn't like UNC. They get poor center play, cant defend 3s, and don't get TOs

Center play and turnovers were positives today but it wasn't enough

UNC and Memphis, elite shooting teams, both went cold to crash out. This is why my models fade shooting reliant teams
#MarchMadness #OleMiss

Memphis' main advantage over this CSU team was their 3pt shooting

Unfortunately for them, out their 3 elite shooters, Tyrese Hunter was out injured and PJ Haggerty was was 1/8 from 3

#CSU #MarchMadness #ColoradoState

Miss St. has kept this close despite their poor first half offensive approach.

They have a huge side advantage and have shot 70% inside the arc, yet have taken 7 more 3s than shots in the paint.

Baylor's poor 3pt shooting is keeping Miss St. in it.

#Baylor #MississippiSt #MarchMadness

My data model said a Drake win was based on interior scoring and defense

Drake scored 38 paint points vs Mizzou's 20

Drake has allowed the lowest point in the country and held opponents to 31% from 3. Mizzou is a top 20 3pt team but were held to 25% and 57 points

#Drake #MarchMadness

My machine learning models said Yale's unlikely path to an upset was from a hot shooting night. While they shot the ball decently well, they couldn't stop A&M's offense

A&M continue their poor 3pt shooting but score 46 points in the paint. 25 from Payne on 10/12, got what he wanted

#MarchMadness

Dickinson scores 0 POINTS in the second half and ends the game with 4 turnovers, 4 fouls, and -8 +/-.

A wildly inefficient game from Kansas' offensive anchor.

#Arkansas

My machine learning model said Kansas could to go on a run because of Dickinson's ability to create easy offense

He has certainly got his own with 11/6/4 this first half

However, Arkansas is picking on him with 24 points in the paint. 16 from Aidoo on 8/13, playing him as well as anyone

#Arkansas

BYU dismantled this elite VCU defense on all levels. Scoring 18 more points than VCU allowed on average this season

BYU's center duo of Keita and Traore combine for 22 points/18 rebounds/4 blocks

VCU went 9/21 in the paint and only shot 6 free throws, their lowest mark of the season

#MarchMadness

My machine learning models said that High Point had a chance but needed to win the rebounding battle and take advantage of their depth by winning the non Kaufman-Renn minutes.

They got crushed on the glass by Kaufman-Renn and Heide. They won the 11 non Kaufman-Renn minutes by just 2

#MarchMadness

Using both a logistic regression model and a random forest model, I have identified the most likely first-round upsets and the lower-seeded trans with the best chances to make a deep run, from each region.

Check out the full blog posts here:
www.rohitbhagavatulaanalytics.com