The setup

I ran a backtest across three CBB seasons comparing closing totals to a simple pace + efficiency model. The goal wasn't to find a magic number — it was to see where the market is systematically slow to adjust.

What the data showed

• Early-season totals (first ~6 games) are the softest lines of the year. Books haven't seen enough possessions to calibrate pace for new rotations, transfers, and freshman minutes. Efficiency ratings are still mostly preseason priors.

• Totals move slower than pace does. When a team's actual per-game possessions run meaningfully above or below their preseason pace projection for 3+ straight games, the total often lags the adjustment by 1-2 games. That lag is where a backtested, rules-based approach can find repeatable edges — not because you're smarter than the market, but because you're checking pace deltas every single day and the line-setters are triaging hundreds of games at once.

• Conference-only stretches distort efficiency numbers. Teams that played a soft or brutal non-conference schedule get mispriced for the first 2-3 conference games until results catch the model up.

The mistake most bettors make

Betting totals off "gut feel" for pace ("this team plays fast") instead of tracking actual possessions-per-40 over a rolling window. Vibes-based pace reads are wrong more often than people think — a team can feel fast because of a few highlight possessions while their actual tempo is middle-of-the-pack.

Takeaway

If you're serious about totals, build a simple rolling-average pace tracker per team (last 5 games weighted higher than season average) and diff it against the market's implied pace from the total itself. The gap is your signal — not a certainty, but a real, repeatable edge worth tracking systematically instead of picking games one at a time.

Happy to answer questions on methodology in the comments.