The Super Bowl over/under prompts frequent questions about how often the game finishes below the market total. Because the market closing total is the settled number that bettors and analysts use as the benchmark, a reproducible answer depends on careful data selection and explicit grading rules. This article gives a step-by-step method to compute the Super Bowl under rate through 2026 using public, maintained datasets. It discusses key era effects, the 2024 kickoff rule, venue influences, common data pitfalls, and hands-on tasks you can run in a spreadsheet to reproduce the results.

Authoritative, year-by-year closing totals through 2026 make a reproducible under-rate calculation possible.

Segmenting by decade and by the 2024 kickoff rule helps avoid misleading conclusions from small recent samples.

Document your sources and retrieval dates for every game to make your under-rate computation auditable.

What the over under means for the Super Bowl: definition and context

Market definition and grading conventions, over under super bowl

The over under in the Super Bowl is the market closing total set by oddsmakers for combined team scoring in the game. In practice, analysts grade a game as an under only when the final combined points fall strictly below that closing total; ties and pushes are handled according to the published grading convention you choose.

That grading rule is the essential reproducibility point: use the closing total, not an opening number or a midweek line, because the closing total is what the market settled on and what historical datasets commonly record. For a concise formal definition of an over/under and the conventional grading language, see the general explanation of over/under markets on Investopedia Over/Under definition on Investopedia.

Run a reproducible under-rate check with primary closing-total datasets

Try the step-by-step method below on a single season of closing totals to see how the grading convention affects your under rate.

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When you prepare a reproducible analysis you should list the dataset used for each game, the exact closing total recorded, and the grading convention for ties or half-point totals. Public, maintained sources provide year-by-year closing totals and results through 2026; choose at least one and document the retrieval date to make your computations repeatable and auditable. See the Funded Plays blog.

Reliable public datasets that track Super Bowl closing totals and O/U results include the Action Network historical odds collection and comparable archives such as VegasInsider and SportsOddsHistory, each of which records closing numbers and game results for every Super Bowl year through 2026 Action Network Super Bowl odds history.

How to compute the Super Bowl under rate: a step-by-step method

Data collection and cross-checking

Step 1, collect the year-by-year closing totals and final combined points from at least two authoritative sources so you can resolve discrepancies. For reproducibility, record which site you used for each row and the date you retrieved the data. Primary public sources you can use are Action Network, VegasInsider, and SportsOddsHistory; cross-checking helps detect transcription errors or differences in how pushes are logged VegasInsider Super Bowl odds history.

How often does the Super Bowl finish under the market closing total?

You can compute an exact under frequency through 2026 using maintained year-by-year closing-total datasets; document the source and grading convention and segment by era, including pre- and post-2024, before interpreting any trend.

Step 2, apply the grading rules exactly: count a game as an under only if final combined points are strictly less than the closing total. If the closing total is a whole number and the combined points equal that number, record the game as a push; if the total includes a half point, the result cannot push and is either over or under. Document how you treat pushes in your notes because different repositories and analysts may report pushes differently, so this step ensures reproducible counts.

Grading rules and edge cases

Step 3, handle half-point totals and ties consistently. Many historical Super Bowl totals are whole numbers, but many recent totals include half points. If you plan to compute an under rate as a percentage of games that finished under, make clear whether you exclude pushes from the denominator or include them; both practices occur, and your choice affects the reported percentage. For the formal definition and examples that clarify pushes and grading nuances, consult an over/under primer Over/Under definition on Investopedia.

Step 4, compute raw counts and percentages: after you mark each Super Bowl as under, over, or push, sum the unders and divide by your chosen denominator (total games or total games excluding pushes). Keep a simple provenance log listing the source and retrieval date for each game so a third party can rerun your calculations and reach the same percentage.

What the historical data shows and why era breakdowns matter

Decade and era comparisons

Historical totals and O/U results vary with league-wide scoring environments, so aggregate under counts by decade to see how the phenomenon changes across eras. For example, compute separate under rates for the 1970s, 1980s, 1990s, 2000s, 2010s, and 2020s rather than reporting a single long-term average; this approach reduces the risk of masking structural changes in scoring and pace that influence totals and final points. The year-by-year datasets maintained through 2026 make these decade splits straightforward to implement SportsOddsHistory Super Bowl betting history.

When analysts segment by era they can also report uncertainty ranges and sample sizes. Decade buckets often contain only a handful of Super Bowls, so treat decade rates as descriptive rather than definitive. Use the raw counts, show the denominator explicitly, and avoid overclaiming about small-sample fluctuations.

Venue conditions matter because many modern Super Bowls occur in domes or warm-weather sites, which reduces weather-related scoring volatility compared with cold outdoor stadiums. Market previews and historical write-ups commonly note venue climate when bookmakers set totals, and documenting venue type alongside closing totals helps analysts test whether dome games show a different under frequency than open-air, cold-weather games TheLines Super Bowl odds history and totals trends.

That said, venue alone does not determine scoring: matchups, team styles, and defensive game plans can override climate expectations. Treat venue as one factor among many and, when feasible, control for matchup variables in a simple regression or stratified tabulation.

Pre- and post-2024 kickoff rule segmentation

The NFL approved a new kickoff rule for the 2024 season that could affect kickoff returns, field position, and potentially scoring in both regular-season and neutral-site games. When interpreting under frequency through 2026, segment samples into pre-2024 and post-2024 groups to test whether the rule change coincides with a measurable shift in Super Bowl scoring behavior NFL announcement on the 2024 kickoff rule.

Because the post-2024 sample will be small for Super Bowls through 2026, report the counts and avoid asserting long-term trends until more seasons accumulate. Still, documenting the split is essential: it makes clear how much inference depends on the new rule and how much is driven by other factors like matchup quality and venue.

Factors that influence a Super Bowl landing under the total

Venue and weather effects

Market previews and historical write-ups commonly note venue climate when bookmakers set totals, and documenting venue type alongside closing totals helps analysts test whether dome games show a different under frequency than open-air, cold-weather games TheLines Super Bowl odds history and totals trends.

Rule changes and game tempo

Rule changes and league-wide stylistic shifts affect overall scoring. The 2024 kickoff rule is a clear example because it can alter typical starting field position after kickoffs, which feeds into scoring probabilities; account for such rule effects when comparing eras to avoid conflating a rule-driven shift with a secular trend in under rates NFL announcement on the 2024 kickoff rule.

Markets also price tempo and offensive style: teams that run ball-control offenses or slow the clock tend to reduce scoring expectations, and sharp bettors and market makers incorporate those matchup signals into the closing total. Recording a few matchup covariates, such as season-long pace metrics or team scoring averages, can help analysts interpret surprising under outcomes.

How to use the under frequency: decision criteria for analysts and bettors

When a historical under rate is actionable

A historical under rate is informative about long-run tendencies but does not guarantee a single-game outcome. Use the historical rate as a prior rather than a forecast for one game: combine it with matchup-specific adjustments, venue context, and up-to-date injury or weather information before making any decision informed by that rate. For disciplined decision-making, document how your prior is adjusted for each new game and keep exposure small relative to sample uncertainty Action Network Super Bowl odds history.

Actionable signals arise when the historical rate, properly segmented by era and matchup context, meaningfully disagrees with an individual market price after your adjustments. Even then, treat the difference as an edge estimate, not a certainty, and size positions conservatively according to your risk rules.

Limitations and risk controls

Limitations include small sample sizes, evolving league rules, and the fact that a Super Bowl is a single-game event with unique incentives and media effects. Recommended risk controls are straightforward: limit stakes relative to bankroll, test your method on out-of-sample seasons, and preserve a clear provenance log showing sources and retrieval dates so you can revisit calculations if new data appears.

Also, do not confuse the platform used to organize or test your strategies with a guarantee of performance. For a skill-based environment that emphasizes reproducibility and disciplined performance without promising earnings, consider systems that let you test forecasting methods in structured evaluation challenges.

Common mistakes and pitfalls when measuring Super Bowl unders

Data and grading errors

A common error is mixing opening and closing totals or failing to note the retrieval timestamp. Opening lines reflect early betting and are not the settled market number; using them for a historical under rate will produce inconsistent and unreproducible results. Always specify that you used the market closing total and cite the exact dataset and retrieval date where possible VegasInsider Super Bowl odds history.

Other frequent data mistakes include transcribing final combined points incorrectly, misreading half-point totals, or ignoring pushes. These errors can flip a single game's classification and materially change percentage points when the sample is small.

Quick verification checklist for dataset and grading validation

Closing total recorded
Final combined points
Source and retrieval date
Push handling documented
Era label assigned

Run this checklist for each game

Overfitting to recent games

Overfitting is the tendency to overreact to a short run of recent outcomes. Several early-to-mid 2020s Super Bowls have been reported as unders in recaps, which may indicate a pattern, but verify those observations against the year-by-year datasets before treating them as a sustained structural shift TheLines Super Bowl odds history and totals trends.

To avoid overfitting, compute rolling-window under rates, report confidence intervals where feasible, and emphasize that small post-2024 samples cannot definitively prove a new era until more games accumulate.

Practical walkthroughs: reproducible examples and reader tasks

Example A: computing the overall under rate through 2026

Task 1, pull the year-by-year closing totals and result columns from Action Network and SportsOddsHistory for every Super Bowl through 2026. Keep the raw table in a spreadsheet with these columns: Year, Closing Total, Final Combined Points, Over/Under Classification, Source, Retrieval Date. Use the exact column names so you can write simple filters and pivot summaries later Action Network Super Bowl odds history.

Task 2, reconcile discrepancies: if the two sources report different closing totals for a single year, refer to a third source like VegasInsider to resolve the difference or note both values and flag the row for follow-up. Record which source you trust for the final entry and why.

Task 3, compute counts: add a calculated column that marks 1 for under, 0 for over, and NA for pushes. Use spreadsheet functions or a short script to sum the under column and divide by the chosen denominator to get the under percentage. Keep the spreadsheet and export a small reproducibility note listing each source and retrieval date so others can verify the computation.

Example B: era comparison and post-2024 check

Task 1, subset the table into decade buckets and compute per-decade under rates. Document the per-decade denominator and any excluded pushes. Present the results in a simple table in your notes; do not generalize beyond what the counts support.

Task 2, create a pre-2024 vs post-2024 comparison to inspect whether the 2024 kickoff rule coincides with a perceptible change in Super Bowl unders. Because the post-2024 sample through 2026 is small, show the raw counts and refrain from strong claims. For guidance on where to get year-by-year numbers and how to format them, start with Action Network and SportsOddsHistory, and keep your retrieval dates explicit in your exported worksheet SportsOddsHistory Super Bowl betting history.

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Checklist to rerun the analysis: 1) download closing totals and results from two sources, 2) confirm push handling, 3) compute under counts and percentages, 4) segment by era and venue, and 5) save a provenance log with retrieval dates. Following this checklist makes your conclusion reproducible and easier to audit. Visit Funded Plays.

Conclusion: key takeaways and next steps for readers

Summary of recommended method

Use the closing total as your primary number, record source and retrieval date, cross-check two or more authoritative datasets, and apply a clearly stated grading convention for ties and half points. Segment results by decade and by the 2024 kickoff rule to see whether era effects explain observed changes in under frequency Action Network Super Bowl odds history. See how funded plays evaluations work.

Close up of a printed historical odds table with highlighted closing totals and a pen marking under and over classifications for over under super bowl betting reference

Where to go next: run the reproducible steps on your own spreadsheet, present counts and denominators rather than speculative percentages, and update the analysis as more post-2024 games occur. If you want a structured environment to practice disciplined forecasting and document your method, consider participating in skill-based evaluation challenges that emphasize repeatable performance rather than short-term outcomes.

Minimalist 2D vector split image of a domed stadium interior on the left and a simplified era segmentation spreadsheet on the right over under super bowl

How is an under defined for Super Bowl totals?

An under is recorded when the final combined points are strictly less than the market closing total; pushes occur when the final points equal the closing total and should be documented in your grading convention.

Which datasets should I use to compute the under rate?

Use maintained year-by-year datasets such as Action Network, VegasInsider, and SportsOddsHistory and cross-check at least two sources for reproducibility.

Does a historical under rate predict a single Super Bowl outcome?

No, a historical rate is a long-run descriptive prior; combine it with matchup, venue, and rule-context adjustments before applying it to a single game.

Run the step-by-step method on a single season of closing totals first to verify your process, then scale up to decade and era comparisons. Keep a provenance log of sources and retrieval dates so you and others can replicate the calculation. If you want practice applying disciplined forecasting and reproducible methods, consider participating in structured evaluation challenges that reward consistency and transparent recordkeeping.