Editor’s Note: Since November 2018, Joe has been publishing picks here and back at All Things NIT, our former site. Overall, the results have been mixed, with an average return on investment, per pick, of -4.0% when weighting by confidence (1 for low, 2 for medium, 3 for high) across 4,009 published picks, not including pending futures, and an average return on investment, per pick, of 0.9% across 1,336 completed high and medium-confidence picks (low confidence picks, these days, are in experimental markets for us).
Use these picks at your own risk. Only you are responsible for any money you lose, and you should not bet more than you can afford to lose. If you have a gambling problem, get help.
Lines for these come from the Vegas consensus or the closest approximation available at the time picks are written, unless otherwise noted. For futures bets (in both sports and politics) and motorsports bets, odds are taken from the better option between Bovada and BetOnline as our best approximation of the Vegas consensus, which isn’t currently/accurately available online. KenPom is heavily used in making college basketball picks. FiveThirtyEight’s SPI is heavily used in making soccer futures picks. ESPN’s FPI is heavily used in making NFL futures picks.
College basketball starts today, so two picks for that, plus picks for the midterm elections. A note on the elections: We put 100 units down on these in July, and while we intended to circle back more frequently, it didn’t happen. Those are shaping today’s, and while they aren’t a huge factor, we wanted to acknowledge they’re out there. Now. The basketball:
UT-Martin @ Pitt
Pitt’s missing John Hugley and William Jeffress tonight, two of last year’s biggest contributors. Just because they were big contributors last year, though, doesn’t mean they’re important this year. Pitt should be an improved team. Maybe not improved enough to challenge the bubble, or even make the NIT, but improved. They’ve picked up three potential impact transfers. They’ve picked up Guillermo Diaz Graham, a Spanish seven-footer who projects, on EvanMiya, to be their best player. Again: Pitt shouldn’t be very good this year. But they should be good enough to win by double digits against UT-Martin at home.
Pick: Pitt -8.5 (-112). Low confidence.
VMI @ Richmond
VMI’s got a new coach this year, with Andrew Wilson coming over from the James Madison staff to lead the Keydets. Dan Earl’s shoes aren’t the biggest to fill—he only finished above .500 once in his seven years at the helm—but he took Jake Stephens and Honor Huff with him to Chattanooga, and both Trey Bonham and Kamdyn Curfman are gone as well, to Florida and Marshall, respectively. It’s a team undergoing sizeable turnover. But…
Richmond’s undergoing some turnover itself. March hero Jacob Gilyard is in the G League. Grant Golden is there as well. Tyler Burton and a few others are back, but this isn’t last year’s team, and last year’s team was a frustrating, underachieving group until they rattled off those five wins in a row across the A-10 Tournament and the NCAA Tournament’s first round. Even those mostly came by single digits, and left them 85th in KenPom to end the year.
This should be a comfortable Richmond win. But it doesn’t have the markings of an outright blowout.
Pick: VMI +22.5 (-112). Low confidence.
2022 Midterm Elections
Alright, a big batch now of these.
We’re using the FiveThirtyEight model for this, and our approach is basically as follows (this is more or less the same approach we used in July):
1. Identify plays with positive expected value.
2. Confirm value across all three iterations of FiveThirtyEight model.
3. Place enough on each side to withstand even the most extreme “red wave” or “blue wave” without losing more than 50% of our investment.
4. Place enough on plays with 90% or higher probability that if we only win those, we still profit.
5. Use the leftover units to play for maximum value.
We’re betting 500 units today—using a lot of what had been tied up in MLB futures—and our general thesis, this would imply, is that the polls aren’t going to be historically wrong. They might be wrong in areas, but they’re not going to be shockingly wrong. Markets do seem higher on Republicans than Democrats relative to the FiveThirtyEight model, but that was the case in 2020 as well, and it worked out well for us. The only real spot where we’re seeing value on a Republican is the U.S. Senate race in Alaska, and even there it’s on a Republican to beat a different Republican. Betting markets just really like Republican candidates these days, for reasons plenty of other people can discuss. We’re just trying to make money here.
- Pick: Republican Candidate to win U.S. Senate Election in Kansas -5000. Medium confidence. x41
- Pick: Republican Candidate to win U.S. Senate Election in North Dakota -5000. Medium confidence. x41
- Pick: Republican Candidate to win Regularly Scheduled U.S. Senate Election in Oklahoma -5000. Medium confidence. x41
- Pick: Kathy Hochul to win New York Gubernatorial Election -425. Medium confidence. x50
- Pick: Democratic/DFL Candidate to win Minnesota Gubernatorial Election -400. Medium confidence. x50
- Pick: Laura Kelly to win Kansas Gubernatorial Election -125. Low confidence. x10
- Pick: Gretchen Whitmer to win Michigan Gubernatorial Election -300. Low confidence. x10
- Pick: Sharice Davids to win U.S. House Election in Kansas 3rd District -190. Low confidence. x10
- Pick: Eric Sorensen to win U.S. House Election in Illinois 17th District +100. Low confidence. x10
- Pick: Hillary Scholten to win U.S. House Election in Michigan 3rd District +100. Low confidence. x10
- Pick: Lisa Murkowski to not be re-elected +400. Low confidence. x4
