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Closing total

As explained in Statistics Slam Dunk

A closing total is the predicted combined score of the participating teams after wagers have been placed and the betting line has closed.

A closing total is the predicted combined score for both teams after wagers have been placed and the betting line has closed. Also called the closing over/under, it is the number bettors use to choose whether the actual combined score will finish over or under the line; the winner and margin do not matter. section 17.0 section 17.3

The total can move from its opening value as betting arrives. A move upward is intended to encourage under wagers, while a move downward is intended to encourage over wagers. For Memphis–Indiana, the total moved from 209 to 204.5, indicating heavier betting on the under. section 17.0

To compare a closing total with the opening total and the game result, create these game-level measures:

  • Add road and home points to produce the actual combined score, ptsT. section 17.4.2
  • Compute each line’s absolute error: abs(ptsT - opentotal) and abs(ptsT - closetotal). section 17.4.2
  • Classify movement as up, down, or same, then label which total has the smaller error. section 17.4.2

2018–19 NBA comparison

Across the 2018–19 regular season, closing totals were closer to combined points more often than opening totals, by about 10% in the count comparison. Their average variance from combined points was about 2% lower, and the count advantage held whether the total had moved up or down. section 17.5.1 section 17.5

oddsdf3 %>%
 mutate(versusPTS = 
          case_when(diff_ptsT_opentotal > 
                    diff_ptsT_closetotal ~ "closetotal",
                    diff_ptsT_closetotal > 
                    diff_ptsT_opentotal ~ "opentotal",
                    diff_ptsT_opentotal == 
                    diff_ptsT_closetotal ~ "same")) -> oddsdf3

oddsdf3$versusPTS <- factor(oddsdf3$versusPTS)

This R transformation assigns each game to closetotal, opentotal, or same according to which line is nearer the final combined score. section 17.4.2

These comparisons support a collective-intelligence interpretation: bettors collectively added information beyond the opening odds. The finding is limited to the examined NBA regular season, rather than establishing that every closing total will be more accurate. section 17.5 section 17.6

How Statistics Slam Dunk covers it

How deep it goes
Defines the line, derives absolute-error measures, and compares opening and closing accuracy by movement and month.
Examples
Uses the Memphis–Indiana game and 2018–19 NBA regular-season totals, bar charts, and R data transformations.
What it assumes
Introduces over/under and closing-total meanings before applying R data wrangling and plotting.
What you can do after
Evaluate/understand whether closing or opening totals more closely match combined game scores using absolute differences.
How it connects
Connects over/under betting, opening total, point spread, exploratory data analysis, and collective intelligence.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Statistics Slam Dunk. The section links point to the parts of the book it draws on.