How We Measure Odds Accuracy

A transparent, scientific approach to evaluating bookmaker predictions

The OA Score™

The OA Score™ (OddsAccuracy Score) is our branded implementation of the Brier Score, a well-established metric in probability forecasting originally developed by Glenn W. Brier in 1950.

💡 Key Principle

Lower scores indicate more accurate predictions. A perfect forecast has an OA Score™ of 0.0000, while random guessing averages around 0.2500.

Why the Brier Score?

📊

Industry Standard

Used by meteorologists, financial analysts, and sports forecasters worldwide

🎯

Accuracy + Confidence

Penalizes both incorrect predictions AND overconfident forecasts

⚖️

Fair Comparison

Enables objective comparison between different bookmakers

The Mathematics

Step 1: Convert Odds to Probabilities

Bookmakers express their predictions as decimal odds. We convert these to implied probabilities:

\[ P_{outcome} = \frac{1}{odds_{outcome}} \]

Example: Odds of 2.50 → Probability = 1/2.50 = 0.40 (40%)

Step 2: Normalize Probabilities

Bookmakers include a profit margin, so probabilities sum to more than 100%. We remove this margin:

\[ P_{normalized} = \frac{P_{outcome}}{\sum P_{all}} \]

Step 3: Calculate the OA Score™

The Brier Score measures the mean squared error between predicted probabilities and actual outcomes:

\[ OA\ Score = \frac{1}{N} \sum_{i=1}^{N} (f_i - o_i)^2 \]

Where:

f_i = Forecasted probability for outcome i (Home/Draw/Away)
o_i = Actual outcome (1 if occurred, 0 if not)
N = Number of possible outcomes (always 3 for football)

Worked Example

Match: Manchester City vs Liverpool

Bookmaker odds: Home 2.10 | Draw 3.60 | Away 3.40

Actual result: Home Win

Calculation:

Convert: P(Home)=0.476, P(Draw)=0.278, P(Away)=0.294
Normalize: P(Home)=0.455, P(Draw)=0.265, P(Away)=0.281
Actual outcome vector: [1, 0, 0] (Home Win)
Calculate: [(0.455-1)² + (0.265-0)² + (0.281-0)²] / 3
OA Score™ = 0.1484

Moving Averages & Trend Analysis

To smooth out variance and identify trends, we calculate moving averages over different windows:

15-Match Window

Short-term form and recent changes in accuracy

30-Match Window

Medium-term trends, our default view

50-Match Window

Long-term performance and seasonal patterns

Moving averages help us identify whether a bookmaker is improving, declining, or maintaining consistent accuracy over time.

Market Efficiency Analysis

We compare opening odds (first published) vs closing odds (final odds before kick-off) to measure how markets improve with more information:

Market Correction = OA Score_opening - OA Score_closing

Positive correction: Closing odds are more accurate (market improved)
Negative correction: Opening odds were more accurate (market degraded)

This metric reveals how efficiently bookmakers incorporate new information (team news, weather, betting patterns) into their odds.

Team Predictability

We analyze which teams have the most predictable vs unpredictable results by calculating the average OA Score™ for matches involving each team.

⚽ Predictable Teams

Consistently low OA Scores™ indicate:

Dominant teams that win as expected
Stable form and performance
Market correctly prices their matches

Example: Manchester City typically has very predictable results

🎲 Unpredictable Teams

Consistently high OA Scores™ indicate:

Inconsistent performance
Frequent surprises and upsets
Market struggles to price their matches

Example: Newly promoted teams often have unpredictable results

Data Sources & Processing

Primary Data Source

We use historical odds and match results from Football-Data.co.uk, a reputable aggregator of football statistics and betting odds.

Bookmakers Analyzed

Pinnacle

Benchmark

Bet365

Industry Leader

William Hill

Traditional

BetVictor

Competitive

Bwin

European

Data Processing Pipeline

Data Collection: Download CSV files from Football-Data.co.uk (updated weekly)
Data Cleaning: Remove matches with missing odds or results
Probability Conversion: Convert decimal odds to normalized probabilities
Score Calculation: Compute OA Score™ for each match and bookmaker
Aggregation: Calculate moving averages, rankings, and efficiency metrics
Visualization: Generate interactive dashboard with Chart.js

🔄 Update Frequency

Our analysis is updated weekly after each Premier League matchweek, typically on Monday mornings.

How to Interpret OA Scores™

0.0000 - 0.0500: Excellent

Highly accurate predictions, minimal forecasting error

0.0500 - 0.1000: Good

Above-average accuracy, reliable predictions

0.1000 - 0.1500: Average

Moderate accuracy, typical for competitive markets

0.1500 - 0.2000: Below Average

Lower accuracy, significant room for improvement

0.2000+: Poor

Weak predictions, approaching random guessing (0.2500)

Note: These ranges are approximate and context-dependent. Premier League odds are generally more accurate than lower divisions due to better information availability.

Limitations & Caveats

While the OA Score™ is a robust metric, users should be aware of these limitations:

⚠️

Not Betting Advice

Lower OA Scores™ indicate accurate predictions, but do NOT guarantee profitable betting
📊

Retrospective Analysis

We evaluate past performance; historical accuracy doesn't guarantee future results
🎯

Margin-Adjusted

We normalize probabilities to remove bookmaker margins, which affects absolute values
⏰

Sample Size Matters

Short windows (15 matches) are more volatile; longer windows (50 matches) are more stable
🔄

Market Dynamics

Bookmaker accuracy can change over time due to new models, staff changes, or market conditions

Academic References

Brier, G.W. (1950)

"Verification of forecasts expressed in terms of probability"

Monthly Weather Review, 78(1), 1-3
Constantinou, A.C. & Fenton, N.E. (2012)

"Solving the problem of inadequate scoring rules for assessing probabilistic football forecast models"

Journal of Quantitative Analysis in Sports, 8(1)
Hvattum, L.M. & Arntzen, H. (2010)

"Using ELO ratings for match result prediction in association football"

International Journal of Forecasting, 26(3), 460-470

Transparency & Open Methodology

We believe in transparent analytics. Our methodology is:

✅ Based on published academic research
✅ Using publicly available data sources
✅ Fully documented on this page
✅ Consistently applied across all bookmakers

For technical questions or suggestions, please contact us at: methodology@oddsaccuracy.com

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OA Score™ is a trademark of OddsAccuracy