This article explains how to measure how accurate FanDuel s NFL odds are using reproducible forecast-verification methods. It is written for sports analysts and enthusiasts who want a clear, step-by-step procedure to convert American odds to probabilities, remove the bookmaker margin, and evaluate probability forecasts with proper scoring rules. The guide focuses on practical choices: which snapshots to collect, how to de-juice implied probabilities, how to compute the Brier score, and how to present calibration diagnostics. Wherever a concrete methodological claim is made, the recommendations align with established verification guidance and public data sources so your work can be reproduced.

Convert American odds, de-juice them, and score with the Brier score for reproducible accuracy checks.

Reliability diagrams reveal where probabilities are systematically over- or under-confident.

Use public final results and document timestamps to make your study verifiable.

What FanDuel NFL odds are and how to read them

How sportsbooks express prices: American odds explained

FanDuel and other U.S. books present prices as American odds, a compact way to show the payout for a winning bet. The format is either a positive number for underdog payouts or a negative number for favorites, and understanding that sign convention is the first step before any accuracy analysis. Keep a consistent notation when you collect snapshots so the sign meaning is not lost in later conversions.

To prepare odds for later scoring, record whether the posted number was the opening price, a mid-game adjustment, or the closing market. FanDuel s operational rules clarify that prices can move and that settlement rules determine how outcomes are applied, so a clear timestamp on each snapshot is essential for reproducibility and for aligning the posted price to the eventual result FanDuel Sportsbook House Rules.

Minimalist Funded Plays style step by step infographic showing how to convert American odds to implied probability with a de juicing comparison, clean dark layout, fanduel odds nfl

Converting American odds into an implied probability is mechanical and can be done in a few lines of code or with a spreadsheet. For positive American odds, the simple verbal rule is: implied probability equals 100 divided by the odds plus 100. For negative American odds, the rule is: implied probability equals the absolute value of the odds divided by the absolute value plus 100. Applying these rules produces a raw implied probability for each side of a two-outcome market.

When you convert, note the raw implied probabilities will usually sum to more than one because the bookmaker adds a margin to the prices; this excess is called the overround or margin and must be accounted for before comparing those probabilities to actual outcomes Pinnacle Betting Resources.

The bookmaker margin is the built-in edge a sportsbook includes across a book to ensure long-term profitability. If you score raw implied probabilities without removing that margin, your analysis will treat every probability as slightly overconfident. That systematic bias makes comparisons unfair when evaluating whether FanDuel s odds are well calibrated.

De-juicing, the practical step of normalizing implied probabilities so they sum to one, is therefore required for reproducible accuracy work and applies regardless of whether you analyze opening lines, closing lines, or intraday moves Pinnacle Betting Resources.

Quick conversion checklist for American odds to implied probabilities and de-juicing

Positive odds rule
Negative odds rule
Compute implied probabilities
Sum overround
Normalize probabilities
Document snapshot timestamp

Use consistent notation when coding to avoid sign errors

When you compare probabilistic forecasts, choose scoring rules that reward truthful probability estimates rather than just correct picks. Strictly proper scoring rules ensure analysts and models minimize long-term loss only when they report honest probabilities, so scores give a fair basis for comparison between different methods or books Journal of the American Statistical Association.

Using a proper score matters because naive metrics like simple hit rate encourage overconfident betting on favorites; a proper score penalizes probability forecasts that are far from the observed frequency even if the most likely outcome occurs.

The Brier score is a straightforward proper scoring rule for binary outcomes: it measures the mean squared difference between predicted probabilities and outcomes. Lower Brier scores indicate better average probability forecasts, while higher scores show larger average errors. Because the Brier score treats probability differences continuously, it is more informative than counting correct picks alone Journal of the American Statistical Association.

Reliability diagrams, often called calibration plots, show whether events predicted with a certain probability actually occur at that frequency. For example, if games predicted with 70 percent probability happen about 70 percent of the time, the forecasts are well calibrated. Diagrams make it easy to spot systematic over- or under-confidence that aggregate scores can mask.

Hit rates, or the fraction of correctly predicted favorites, answer a different question from calibration. Hit rates ignore the forecast probability and only count whether the chosen side won. Calibration asks whether the magnitude of the quoted probability matches the observed frequency. Two bookmakers could have similar hit rates but very different calibration if one consistently quotes probabilities that are too high or too low.

For a rigorous evaluation of FanDuel s quoted probabilities, use the Brier score to summarize average accuracy and complement it with reliability diagrams to inspect where any calibration errors concentrate, for example in heavy underdogs or near-even matchups Guidelines on Verification of Operational Forecasts.

Start by defining the market and the snapshot policy. Decide whether you will analyze opening lines, closing lines, or a sequence of intraday snapshots; each choice answers a different question. Opening-to-closing studies test how market information accumulates, while a single pregame snapshot aligned with the settlement rules tests how well the posted price at a reference time reflects the eventual result.

Document the timestamp, the reported American odds, the market type, and any contextual notes for each snapshot so later reviewers can reproduce exactly which price you scored. FanDuel s house rules describe when prices can be adjusted and how matches are settled, which helps align your snapshot rules with operational reality FanDuel Sportsbook House Rules.

1. Choose your sample window and markets, for example the full regular season or a subset of weeks. 2. For each game, record the snapshot timestamp and the American odds for each side. 3. Convert the odds to implied probabilities and de-juice them. Follow these steps carefully and keep a raw copy of the collected snapshots for auditing.

Run a reproducible evaluation with the FundedPlays Challenges workflow

Follow the checklist for one short sample before scaling up to a full season so you can confirm your conversion and de-juicing code works as intended.

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Apply the conversion rules for American odds described earlier, then sum the raw implied probabilities to compute the overround. Normalize each implied probability by dividing by that sum so the adjusted probabilities form a valid probability distribution for the matchup. This de-juicing step makes odds comparable to observed frequencies and is essential before scoring.

Record which de-juicing method you used. The simplest approach rescales probabilities proportionally so they sum to one; alternative methods can apportion the margin differently but must be documented to keep comparisons reproducible and fair Pinnacle Betting Resources.

For each game, compute the per-game Brier score by taking the squared difference between the de-juiced probability assigned to the winning outcome and the outcome indicator, then average across games for an aggregate Brier score. Keep per-game scores so you can inspect distributions and not just the mean.

Aggregate scores by season, by market type, or by opening versus closing snapshots to compare performance. Use public NFL outcomes as the ground truth to make the analysis reproducible, and note that Pro-Football-Reference provides the final scores needed to compute hit rates, calibration curves, and Brier scores 2024 NFL Season Summary and Results.

For ground-truth outcomes, use a stable public source that records final game results and is widely accessible. Pro-Football-Reference is a commonly used source for season-level and game-level results and permits cross-checking your win-loss labels and final scores for reproducibility 2024 NFL Season Summary and Results.

Minimalist 2D vector reliability diagram with white diagonal reference line yellow calibration curve and gray binned bars on dark background for fanduel odds nfl

Store an immutable copy of the final results you used for a given analysis so later reviewers can confirm the mapping between odds snapshots and outcomes. Publish the exact season and sample window in your methods section.

Define whether you analyze the regular season, playoffs, single weeks, or a rolling window. Sample window choices affect the number of games and the balance of heavy favorites versus close matchups; explicitly state exclusions such as games with late cancellations or special settlement rules to avoid hidden biases.

Document whether you include moneyline markets only or also spreads and totals, because different market types have different informational dynamics and therefore different baseline expectations for scores and calibration.

Share code snippets, conversion formulas, and a table of snapshots with timestamps in a public repository or appendix so other analysts can reproduce your results. Provide clear versioning for the data you used and include checksums or export dates when possible.

When sharing, include a short README that states the de-juicing method, the exact Brier score computation, and any filters applied to the sample so comparisons remain apples-to-apples.

The aggregate Brier score summarizes the average squared error between forecast probabilities and realized outcomes. Lower scores mean the quoted probabilities were, on average, closer to reality. Because the Brier score depends on the difficulty of the forecasted market, avoid fixed pass-fail thresholds and interpret the number relative to reasonable baselines or competing datasets.

Report both the mean Brier score and the distribution of per-game scores so readers can see whether a few outliers drive the average or whether errors are widespread.

Pair the Brier score with a reliability diagram to show whether specific probability bands are systematically off. For example, a diagram may reveal that probabilities near 0.5 are well calibrated while strong favorites are overstated; that nuance is invisible in a single aggregate Brier score.

Use hit rates as a complementary diagnostic but do not treat them as a substitute for calibration. Hit rates answer a different operational question and can mislead when probabilities vary in magnitude across the sample Journal of the American Statistical Association.

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Benchmarking opening against closing prices helps quantify how information arriving before kickoff affects calibration. General verification guidance suggests that, in many domains, later forecasts incorporate additional information and may show reduced calibration errors, but the magnitude is sample-dependent and should be measured rather than assumed Guidelines on Verification of Operational Forecasts.

When reporting open-versus-close comparisons, keep the timestamp rules consistent and report any games with unusually large price moves separately so readers can judge whether those cases drive the overall effect.

Forgetting to remove the margin yields systematically biased probabilities that overstate confidence, which in turn inflates apparent calibration errors. Always normalize implied probabilities before scoring or explicitly account for the margin in your interpretation Pinnacle Betting Resources.

Document the de-juicing approach you used so readers can determine whether different normalization choices would change the qualitative conclusion.

Taking snapshots without considering the sportsbook s settlement and adjustment rules can lead to scoring prices that were never intended to apply to the final result. Align snapshots with the sportsbook s operational rules and annotate any exceptions or markets with special settlement cases FanDuel Sportsbook House Rules.

If you use an automated scraper for odds, include checks for timestamps and occasional manual verification so that outages or API changes do not silently corrupt the sample.

Small sample sizes produce high variance in Brier scores and calibration estimates, so be cautious about drawing broad conclusions from a handful of weeks or games. State confidence intervals, bootstrap the Brier score for uncertainty, and highlight that results may shift with a larger or different sample window Guidelines on Verification of Operational Forecasts.

When possible, present per-week or per-month summaries to show stability over time rather than a single aggregated number.

Pick a compact, documented sample to validate your pipeline, for example 20 games from a single week. For each game, record the American odds for both sides, convert to implied probabilities, compute the overround and de-juice, then save the de-juiced probabilities and the final outcome label.

How accurate are FanDuel odds for NFL games and how can I measure that accuracy reproducibly?

You can measure FanDuel odds accuracy by converting American odds to implied probabilities, removing the bookmaker margin, scoring forecasts with the Brier score, and using public NFL results for reproducible calibration checks.

For each game in your sample, compute the per-game Brier score then compute the mean for the sample. Also examine the distribution of per-game scores to see whether a few games generate most of the error. Present the sample output as a small table with columns for game, de-juiced probability assigned to winner, outcome indicator, and per-game Brier score.

Save the table and a short script that reproduces it so others can rerun the steps with a different sample or the full season if they wish.

Extend the small example by recording both an opening snapshot and a closing snapshot for each game, then compute Brier scores for both sets. A compact table can show per-game open score, close score, and the change. Summarize the changes with a simple mean and median to indicate whether closing prices tended to improve calibration in your sample.

State clearly how you handled games with late odds moves or suspended markets so readers can judge whether those edge cases influenced the comparison.

Markets move because new information arrives: injury reports, weather shifts, or late public betting can change the price. Information updating can, in principle, improve calibration if the new information is informative and properly priced into the market, but the measurable effect depends on the sample and how often meaningful new information appears close to kickoff Guidelines on Verification of Operational Forecasts.

Be careful not to conflate movement with improvement. Prices can move for liquidity reasons or risk management without improving the underlying probability estimate.

Define the exact timestamps you treat as opening and closing. For each game, compute de-juiced probabilities for each snapshot and then calculate per-snapshot Brier scores. Aggregate the scores to report mean open and mean close Brier scores and conduct a paired test to see whether differences are statistically meaningful given the sample size.

Control for games with large intraday moves by reporting a separate summary of high-movement games so readers can see whether those cases drive any observed improvement.

If calibration errors shrink from open to close in your sample, that suggests late information had predictive content or the market integrated available signals more effectively by close. If errors do not shrink, it can mean either the market was already well calibrated or that late moves did not systematically improve probability accuracy.

Report effect sizes and uncertainty rather than binary claims so readers understand the magnitude and reliability of any observed improvement.

Summarize your reproducible procedure in five steps: collect timestamped American odds; convert to implied probabilities; remove the margin to de-juice; compute per-game Brier scores; and report aggregate scores plus reliability diagrams and uncertainty measures. Keep raw snapshots and final-result mappings available so others can reproduce your work.

Proper scoring rules and calibration checks are the recommended standard for evaluating fanduel odds nfl because they reward truthful probability estimates and reveal where forecasting errors concentrate Journal of the American Statistical Association.

Remember that results depend on sample choices and timing; avoid sweeping claims from small or narrowly selected samples. Include sensitivity checks and be explicit about exclusions and filters.

After a base reproducible study, explore stratified analyses such as by game closeness, weather, or injury reports, and consider comparing performance across market types. Publish code, snapshots, and clear documentation to support independent verification and incremental improvements.

Adopt transparency-first habits: state the de-juicing method, the exact Brier formula, the season and weeks analyzed, and provide per-game outputs so subsequent analysts can extend or challenge your findings.

How do I convert American odds to probabilities?

For positive American odds, implied probability is 100 divided by (odds plus 100). For negative odds, it is the absolute value of the odds divided by that value plus 100. Then normalize probabilities to remove the bookmaker margin.

What is the Brier score and why use it?

The Brier score is the mean squared difference between predicted probabilities and outcomes. It is a proper scoring rule that rewards honest probability estimates and is useful for comparing forecast quality.

Where can I get final NFL outcomes for reproducible checks?

Use a stable public source such as Pro-Football-Reference for final game results and archive the exact dataset and export date you used for reproducibility.

Measuring sportsbook probabilities requires discipline: clear snapshots, documented de-juicing, and proper scoring rules. By following the steps here and publishing your data and code, you can make transparent, reproducible statements about how well FanDuel s NFL odds track real outcomes. Responsible reporting means acknowledging limits, stating sample choices, and avoiding overconfident claims based on small samples.

What FanDuel NFL odds are and how to read them

How sportsbooks express prices: American odds explained

Run a reproducible evaluation with the FundedPlays Challenges workflow

References