College Basketball Predictions

Selection Sunday for the 2019 NCAA men's basketball tournament is finally here.

In just a few hours, the selection committee will let us know the 68 teams in the tournament field.

It's a joyous occasion for some, and doomsday for others.

Our projected No. 1 seeds for the 2019 men's NCAA basketball tournament are Virginia, North Carolina, Duke and Gonzaga, and that will not change based on Sunday's results. A lot of people have been saying that Tennessee or Michigan State might jump to the No. 1 line if either wins its conference title game, but the selection committee has a tendency to ignore the results of the SEC and Big Ten championships, and we'll be doing the same.

If Kentucky had beaten Tennessee in the SEC semifinals, the Wildcats would have supplanted North Carolina on the top line. However, Tennessee's resume isn't quite as strong as Kentucky's—in spite of two wins over the Wildcats. UNC has nine Quadrant 1A wins and a 10th one-NET-spot-outside-Q1A home win over Florida State (the Volunteers have seven), played a much more difficult schedule and went 11-1 in road games.

At the other end of the spectrum, Oregon was a late bid thief Saturday night, blowing out Washington in the Pac-12 championship game to shrink the bubble by one spot.

The selection show starts at 6 p.m. ET Sunday, and it will be streamed live on March Madness Live and broadcast on CBS.

Up until that time, our live bracket projection will help you try to make sense of the constant chaos.

After the projected bracket for each region, we'll dive into a bubble watch, hitting on the current last four in, first four out and perhaps a few others. For each bubble team, the three best wins and three worst losses are highlighted to add some context to why they're on the bubble. Those best/worst results are a little subjective but are primarily based on NET and KenPom rankings.

FINAL UPDATE: 4:10 p.m. ET on Sunday.

        

First Four Games

No. 16 seed in South Region: North Carolina Central vs. Prairie View A&M
No. 16 seed in West Region: Iona vs. Fairleigh Dickinson
No. 11 seed in East Region: Indiana vs. Texas
No. 11 seed in South Region: Belmont vs. Ohio State

        

Fourth-to-Last In: Texas Longhorns (16-16)
Three Best Wins: North Carolina (neutral), at Kansas State, vs. Purdue
Three Worst Losses: vs. Radford, at Georgia, at Oklahoma State

We are in uncharted waters here. Could a team seriously get an at-large bid with a .500 record? Well, based on the metrics—Texas is top 40 in the NET and top 30 on KenPom—it seems that way. Texas played one of the toughest schedules in the nation and put together a nice collection of quality wins. Still, 16 losses might be a bridge too far.

One major development from Thursday night's loss to Kansas to keep an eye on: Projected lottery pick Jaxson Hayes went down with a knee injury with two minutes left and did not return. I don't want to speculate on the severity of the injury, but if there is any doubt that he'll be able to play in the NCAA tournament, that may be the last straw that pushes the Longhorns out in the eyes of the selection committee.

        

Third-to-Last In: Indiana Hoosiers (17-15)
Three Best Wins: at Michigan State, vs. Michigan State, vs. Wisconsin
Three Worst Losses: at Rutgers, at Northwestern, vs. Ohio State

By now, you know the deal with Indiana: six Quadrant 1 wins, no Quadrant 3 or Quadrant 4 losses, but 15 total losses. In addition to the three wins listed above, the Hoosiers also won home games against Louisville and Marquette during nonconference play. That should be enough. Vanderbilt earned a No. 9 seed two years ago with 15 losses—one of which was a terrible misstep against a team outside the RPI Top 250. And this year's bubble is even weaker than that year's was.

        

Second-to-Last In: Ohio State Buckeyes (19-14)
Three Best Wins: at Cincinnati, at Nebraska, at Indiana
Three Worst Losses: vs. Illinois, at Rutgers, at Northwestern

Ohio State defeated Indiana in the second round of the Big Ten tournament, which might serve as a tiebreaker between the two Big Ten schools. Neither is safe, though. Since the season-opening win at Cincinnati, Ohio State is 0-9 against the NET top 40. The Buckeyes got a bunch of low-Q1 and high-Q2 wins simply by not going winless in Big Ten play, but it's been a long time since their last impressive victory. Factor in the home loss to Illinois, and they'll be sweating out the weekend in Columbus.

                  

Last Team In: Belmont Bruins (26-5)
Three Best Wins: at Murray State, at Lipscomb, vs. Lipscomb
Three Worst Losses: at Green Bay, vs. Jacksonville State, at Jacksonville State

Playing without primary big man Nick Muszynski (injured in the OVC semifinal), Belmont lost to Murray State in the conference championship game. If the selection committee is serious about taking injuries into consideration in its evaluation of teams, that's a key one to keep in mind. Either way, this is a borderline top-50 team both on KenPom and in the NET. The season sweep of Lipscomb arguably makes Belmont the best of the many mid-major at-large candidates.

One thing to keep in mind if my projection is close to what the committee is actually considering: Belmont's nonconference SOS ranks 75th in the nation. If the committee is comparing Belmont and NC State head-to-head at any point, that's a nice advantage for the Bruins.

             

First Team Out: North Carolina State Wolfpack (22-11)
Three Best Wins: vs. Auburn, vs. Syracuse, Clemson (neutral)
Three Worst Losses: at Wake Forest, vs. Georgia Tech, vs. Virginia Tech

North Carolina State played a laughably weak nonconference schedule, and those chickens may be coming home to roost. Even though the Wolfpack defeated all of those terrible opponents and suffered only two remotely bad losses in ACC play, their lack of quality wins is a major issue. Beating Clemson in the ACC tournament's No. 8 vs. No. 9 game was crucial, but we'll see if that's enough.

                    

Second Team Out: Arizona State Sun Devils (22-10)
Three Best Wins: Mississippi State (neutral), vs. Kansas, Utah State (neutral)
Three Worst Losses: vs. Washington State, vs. Princeton, at Vanderbilt

The No. 2 seed in the Pac-12 tournament is normally a lock for the NCAA tournament. However, the second-best team in the Pac-12 doesn't normally suffer nine losses to teams that aren't headed to the Big Dance, either. Thus, here we are. The Sun Devils took care of business against UCLA in the Pac-12 quarterfinals, but losing to Oregon in the semifinals might have been the last straw.

Truthfully, I don't know what to make of this resume. Arizona State is ranked outside the top 60 on both NET and KenPom. It went 4-1 against teams in the projected field, yet it has 10 total losses. Between this team, 16-loss Texas and worst-NCSOS-in-the-nation NC State, it has been a most bizarre year for the bubble.

            

Third Team Out: Temple Owls (23-9)
Three Best Wins: vs. Houston, vs. UCF, at Missouri
Three Worst Losses: vs. Penn, at Tulsa, Wichita State (neutral)

Temple was a last-four-in team for a lot of bracketologists at the beginning of the week, but I already had the Owls out before they lost their AAC opener to Wichita State. Hard to imagine they'll get in at this point.

The main grievance against Temple is that the metrics never much cared for this team. The Owls spent the entire season outside the KenPom top 65, and they weren't even in the NET top 50 prior to the loss to the Shockers. They battled well in losses to VCU, Villanova, UCF, Cincinnati and Houston, but it's a shame they were unable to turn one of those close defeats into a pivotal win.

               

Fourth Team Out: St. John's Red Storm (21-12)
Three Best Wins: at Marquette, vs. Villanova, vs. Marquette
Three Worst Losses: vs. DePaul, vs. Georgetown, vs. Providence

You'll notice that all six of the most noteworthy results for St. John's were in conference play. That's because its nonconference schedule was dreadful outside an overtime win over VCU and a 30-point loss to Duke. In spite of that, the Red Storm were in great shape after they knocked off Villanova in mid-February. Since then, though, they went 2-5, which included four losses to teams outside the field and Thursday night's 86-54 shellacking against Marquette. I already had the Johnnies projected as the first team out before that game, and they didn't help themselves at all with that performance. Time to sweat.

            

Fifth Team Out: Lipscomb Bisons (25-7)
Three Best Wins: at TCU, at Liberty, at SMU
Three Worst Losses: at Florida Gulf Coast, vs. Liberty, vs. Liberty

For the time being, there's still a strong case to be made for Lipscomb. The Bisons played seven nonconference games against KenPom top 125 teams and won three of them. They had only one truly bad loss all season. And the proverbial eye test bodes well. But they'll need a lot of help to remain in the hunt for an at-large bid, both from major-conference bubble teams losing early and from teams like Nevada and Buffalo winning their leagues and preventing bid thieves from surfacing.

          

Sixth Team Out: Creighton Bluejays (18-14)
Three Best Wins: at Marquette, Clemson (neutral), at Providence
Three Worst Losses: vs. St. John's, vs. Ohio State, Xavier (neutral)

Creighton doesn't have any terrible losses. However, 14 "good" losses is still bad when you've won only one game against a guaranteed NCAA tournament team. Indiana and Texas have more losses, but those squads also have quite the collection of quality wins to make up for it. Had they beaten Xavier in the Big East quarterfinals, the Jays might have jumped into the field. But a terrible final possession doomed them to a two-point loss, and probably the NIT.

                    

Seventh Team Out: Clemson Tigers (19-13)
Three Best Wins: vs. Virginia Tech, vs. Syracuse, vs. Lipscomb
Three Worst Losses: at Miami, vs. Nebraska, Creighton (neutral)

Clemson has this year's easy-to-hate resume. The Tigers went only 1-10 against Quadrant 1, and the lone win was a home game against Virginia Tech playing without its starting point guard. But strong metrics and a lack of bad losses have kept Clemson hanging around the bubble. If (and when) the Tigers get left out, they'll only have themselves to blame. Blowing that huge first-half lead against NC State in the second round of the ACC tournament Wednesday is going to sting for months.

Others considered (in no particular order): Alabama, Furman, UNC Greensboro, Memphis, Xavier

                      

Advanced stats courtesy of KenPom.com. NET rankings and quadrant data courtesy of WarrenNolan.com. NET rankings updated daily.

Kerry Miller covers men's college basketball and college football for Bleacher Report. You can follow him on Twitter: @kerrancejames.

In case you've missed the memo for the past few years, predictive analytics have taken over college basketball.

Many rely on KenPom.com, which former meteorologist Ken Pomeroy has up and running with stats dating back to 2002. But Pomeroy certainly isn't alone. There's also Sagarin, KPI, ESPN's BPI, Haslametrics, T-Rank and, doubtlessly, dozens of other efficiency-based and tempo-based rating systems.

Just in the past few months, these metrics have become much more important. Several states have legalized sports betting since last summer, and more could be on the way. Moreover, the NCAA switched from the RPI to the NET (NCAA Evaluation Tool), which has added a major scoring margin and efficiency component to the selection committee's team-sorting tool.

So, how good are these predictive analytics at actually forecasting what's going to happen in a given game, and can they be used to find an edge for bracket pools and/or betting throughout the upcoming 2019 NCAA tournament?

To answer that question, I looked back through the 638 games played in the second half of February, comparing KenPom predictions to gambling lines and the outcomes of those contests. Ideally, we would have used the full season, or even multiple seasons, to get a more complete data set. But two weeks—roughly 10 percent of the campaign—is a good sample size.

The conclusion: Using KenPom to pick games is only marginally more effective than flipping a coin.

Before we go any further, be sure to note I make that statement as an avid consumer of KenPom. I spend more time perusing that site on a daily basis than most people spend on social media or email. It has fantastic elements for evaluating both players and teams, and I do believe you can find a gambling/bracket edge by digging into the numbers for each matchup.

One recent example was New Mexico State at UMKC on Feb. 28.

Both KenPom (seven points) and Vegas (eight) had New Mexico State as a single-digit favorite on the road. But one look at team rebounding percentages on KenPom—where NMSU is among the best on both ends while UMKC is one of the worst—and it becomes obvious the Aggies should be able to cover by winning in a blowout.

They won by 20.

But in an exceedingly random sport which just seems to grow more unpredictable by the week, it's not surprising that the KenPom score projections are far from perfect.

KenPom did correctly project the winner 70.4 percent of the time during the final two weeks of February, but you don't need to spend upward of 16 years perfecting a predictive metric to know Gonzaga should beat Pacific and Pepperdine, or that Belmont is probably going to blow out SIU-Edwardsville.

In games where the Vegas spread was seven points or fewer, KenPom got the winner correct 250 of 413 times (60.5 percent). With spreads of three points or fewer, KenPom only went 98-of-186 (52.7 percent).

And with the exception of the top four seeds in the opening round, most NCAA tournament games will have lines in those point ranges. Of the other 51 games in last year's Big Dance, 43 had a Vegas spread of 7.5 points or fewer, and 19 had a spread under four points.

One interesting discovery from this research project is that it might be a good idea to bet on the underdog when KenPom and Vegas disagree on the spread by two or more points. That only applies to about 30 percent of games, but the underdog either pushed, covered or won outright 64 percent of the time when KenPom's projected spread differed (in either direction) from the final Vegas line by at least two points.

Those differences can often be attributed to injuries. For instance, KenPom had Duke projected to beat Syracuse by 10*, but the Vegas line had Duke as just a five-point favorite with Zion Williamson out. It's next to impossible for predictive analytics to properly account for player absences, and given how often the underdog covers in those situations, it seems gamblers aren't any better at accounting for them.

*Oddly enough, that ended up being one of KenPom's most accurate projections during this two-week span. Duke won 75-65, which just barely missed the 77-67 projection.

For nearly half of all games (311 of 638), KenPom's projected margin was five points or fewer. It had the correct winner in 58.2 percent of those games. And in last year's NCAA tournament, KenPom went 20-17 (54.1 percent) in games where its projected margin was five points or fewer.

To reiterate: better than flipping a coin, but not by much.

And if you consider that KenPom had both Loyola-Chicago and Kansas State projected to lose in the first round last year (not to mention UMBC), you would've immediately lost two Elite Eight teams and a Final Four team by just using its projections to fill out your bracket.

One last note on how KenPom fares at forecasting the scoring divide between two teams: Its projected scoring margin was exactly right 23 times (3.6 percent) and within five points in either direction 233 times (36.5 percent). But it also missed by at least 10 points for 248 games (38.9 percent) and missed the mark by at least 20 points on 52 occasions (8.2 percent).

What about over/unders, though? Surely a metric grounded in scoring efficiency and adjusted tempo does a fine job of projecting how many total points will be scored in a game, right?

Not so much.

KenPom got the exact total correct 19 times (2.98 percent) and was within five points 157 times (24.6 percent). But it missed the total by at least 20 points more often (158 times) than it came within five, and it missed the total by at least 40 points more often (20 times) than it was exactly right.

And it misses wildly in both directions, so it's not as if KenPom is consistently overvaluing either offense or defense. KenPom's projected total was less than the actual total 309 times, and it was more than the actual total 310 times.

Moreover, there's no rhyme or reason as to what will happen when KenPom and Vegas disagree on the combined points, so good luck trying to profit off it. When the Vegas total was at least four points higher than KenPom's projection, the over hit 44 of 87 times (50.6 percent). When KenPom was at least four points higher than Vegas, the over hit 22 of 52 times (42.3 percent).

The moral of the story is that an intelligent man gave up a career trying to predict the weather so he could dedicate more of his life to improving a model that projects the outcome of college basketball games. And after more than a decade-and-a-half, the score predictions still might as well include a shrug emoji.

That's no slight against Ken. Even with my degree in applied mathematics, I couldn't do any better. There's just no way to know what's going to happen in this chaotic sport, and we wouldn't have it any other way.

               

Spread and over/under data courtesy of VegasInsider.com.

Kerry Miller covers men's college basketball and college football for Bleacher Report. You can follow him on Twitter, @kerrancejames.