Most Bubble Teams will POP, Rather than Produce

Keep Expectations Reasonable for Borderline Dance Contenders

We’ve reached the point in the college basketball season where a lot of media coverage will be devoted to “bubble” teams for the NCAA Tournament. So many broadcasts, podcasts, selection articles, “debate” shows…and they’ve got to talk about SOMETHING!

If you’re trying make picks on a nightly basis, or just understand the reality of late-season basketball, it’s important you keep the following in mind…

*Teams that are on the bubble right now probably aren’t very good, or they would already be locked into an invitation.

*Teams who aren’t very good can’t change gears and suddenly be good on command just because everyone’s telling them they “need” to win.

*Teams who aren’t very good often wear down late in a long season. Others have weaknesses that are now fully known across their conferences. This causes some bubble teams to actually get worse just when everyone’s expecting more intensity.

Betting markets have largely wised up to all of this. Media hasn’t. It’s become somewhat of a late season tradition (the past several years anyway) for pundits in sports betting media to make selections on bubble teams because they find the point spreads attractive. ‘This bubble team is only a 3-point favorite at home and they NEED to win!” Or, “that bubble team’s getting seven points on the road from a power, with a spot to really make a statement to the selection committee.”

As we discussed last week, point spreads are based on player/team skill sets. The most important market influences know that bubble teams in general DON’T lift their game in the final weeks of the regular season. Sure, maybe one or two per season do. There are a lot more than one or two bubble teams! You’re more likely to stay in sync with reality if you IGNORE all the bubble talk rather than trying to use it as an angle across the card.

If you have your heart set on finding late-season surges from bubble teams, I’d encourage you to focus on the following.

*Look for teams that had been dealing with injuries who are now getting healthy. The market may lag any improvement that’s coming from having more talented lineups on the floor. Quant models are heavily influenced by results-to-date. Markets are influenced by quant models. Look for teams getting healthy, or benefitting from personnel adjustments that are emphatically trying to make up for lost time.

*Use “need” as a multiplier with other factors rather than an important thing by itself. You can’t multiply by ZERO. But, if the opponent is in a fatigue or letdown spot…if the bubble team has revenge in this particular game…if the opponent has a soft inside defense and the bubble team attacks the basket…THEN being on the bubble might help expand a second-half lead into blowout territory (or spring a road upset over an overrated power). I just read the Billy Walters autobiography…because I do things months or years after everybody else…he talked about how a combination of factors can have an “exponential” impact (particularly multiple injuries at the same positions in football). Think of bubble stuff a multiplier rather than a big, important thing all by itself.

*Don’t be afraid to pick AGAINST bubble teams if your key factors point to the other side. Passing a game you should have bet is just as bad as betting a game you should have passed. Be sure you’re aware of any glaring weaknesses of the most prominent bubble teams. Evaluate whether or not each opponent can take advantage of that weakness.

There will probably be some bubble references in our Big 12 coverage the next few weeks. TCU and Cincinnati have some work to do. Possible that a team or two could slump down onto the bubble. But, I won’t be talking about it NEARLY as much as everybody else. Wanted to lay all of this out for you on a day off from Big 12 action.

That’s it for this Thursday report. My personal schedule is messy this week (well, the next two weeks with exciting but time-sensitive family stuff). Next article will be some time Friday (possibly Friday night) with a catch up of our Big 12 stat studies. I’ll include the stats from Wednesday night’s Oklahoma State/Cincinnati game in that batch. To prepare for Saturday’s seven-game slate, we’ll look at margin averages, ATS records, the CROWDED HOUSE, and home court advantage numbers.

Thanks for reading. See you again soon.