Past Picks

All picks are 504-525-10, for -13.0 units of profit (assuming 1 unit risked on every pick).

Unlock Staff Picks and more...

Subscribe now to see all picks, prediction models, and articles on both BetIQ and TeamRankings.

Get access now

NCAAB Over/Under

Air Force at Utah St. Under 137.5 -110

Won: 132 points

Fri Mar 1 • 11:00pm ET

More info

How it wins: Air Force and Utah State combine for fewer than 137.5 points on Friday, March 1.

Staff notes:

  • Our top college basketball O/U model plays have hit at a 54.5% rate over the past seven seasons, on a sample over 3,000 picks.
  • This is our highest rated college basketball O/U model play for Friday.

Pick published: Mar 1 12:09pm ET, available at that time at BetMGM, Caesars.

Rot# 892

NCAAB Spread

DePaul +19.5 -110

Lost: 58-91

DePaul at Xavier

Wed Feb 28 • 7:00pm ET

More info

How it wins: DePaul wins the game or loses by fewer than 20 points on Wednesday.

Staff notes:

  • This is a playable model spread pick for Wednesday in CBB.
  • In addition, we like this play based on recent form and news.
  • Xavier coach Sean Miller has been rumored as a candidate to move to Ohio State after the Buckeyes fired Chris Holtmann on Feb. 14th. Xavier has played poorly in the last three games, and over the last 10 games, Xavier has an average power rating of only +5.7, compared to +13.4 in the first 17 games.
  • DePaul has been slightly better (by about 3 points on average) in games that point guard Chico Carter has played, though he has gone 0-10 from three-point range in the last three games since returning from a rib injury that caused him to miss 7 straight Big East games.

Pick published: Feb 27 5:04pm ET, available at that time at FanDuel.

Rot# 701

NCAAB Over/Under

Bucknell at Loyola (MD) Over 131.5 -110

Lost: 114 points

Wed Feb 28 • 7:00pm ET

More info

How it wins: Bucknell and Loyola (MD) combine for more than 131.5 points on Wednesday, February 28.

Staff notes:

  • Our top college basketball O/U model plays have hit at a 54.5% rate over the past seven seasons, on a sample over 3,000 picks.
  • This is our highest rated college basketball O/U model play for Wednesday.

Pick published: Feb 27 7:14pm ET, available at that time at DraftKings.

Rot# 306519

About Our Staff Picks

We created the Staff Betting Picks feature to address several opportunities to provide more value to our subscribers:

  • BetIQ and TeamRankings offer a LOT of predictions and data, but it’s not fast or easy to parse through it all. Some subscribers just want to see a short list of our top/favorite picks.
  • Many bettors enjoy reading the rationale behind a recommended pick, as opposed to blindly trusting “because the model said so” as the reason.
  • Our algorithmic models for NFL and college football make predictions for full-game point spread, over/under, and moneyline bets. However, there’s a lot more to bet on than that.
  • Although bet size limits tend to be lower for markets like props and futures, those types of markets sometimes offer some of the biggest edges.
  • Our model predictions often change as they digest new data such as betting line movement and new game results. That approach has a lot of benefits, because the predictions shown always reflect the most up-to-date data we have. However, some subscribers just want to see a pick that doesn’t change.
  • As we do research on teams and players, sometimes we see a situational or one-time angle on a bet that we are confident provides expected value, and that angle may not be something that our models are well trained to pick up. Models typically need a lot of historical data to work well, and deep historical data simply doesn’t exist for situations that are less common (e.g. quirky injuries or weather or another more creative angle).

Some (and potentially the majority) of our Staff Picks will be drawn from top-rated model picks, but we’ll explain the data angle(s) that our models are likely seeing. Other Staff Picks may not be even be favored by our models, but we’re making a judgment call to overrule them.

Finally, some Staff Picks will be bets like player props and futures that our game models don’t currently cover, or more market-based value opportunities that we see (e.g. an off-market line offered by a particular sportsbook).

For each pick we make, we will note the sportsbook that offered it, and the associated line/payout odds at the time when we published it.