Understanding the ADGA Production Evaluation

If you’re new to ADGA’s performance data, the Production Evaluation page might look a little overwhelming at first. But once you understand what the numbers mean, it becomes one of the best tools you have to evaluate milk production and genetic potential—whether you’re breeding, buying, or tracking progress in your herd.

 

What Is the Production Evaluation Page?

 

The Production Evaluation page appears on ADGA Genetics when you look up a registered goat. It provides a detailed summary of that animal’s performance and genetic predictions. To view it, go to the goat’s profile and click the “Production Evaluation” link in the left-hand panel. This section includes standardized milk data, PTA and PPA values, and percentile rank—offering a helpful snapshot of the goat’s potential and performance based on available milk test records.

 

In this guide, we’ll walk through each part of the evaluation step-by-step and explain what the numbers mean and why they're important. 

 

1. General Information

Parameter

What It Means

Example Interpretation

SG

Superior Genetics.  This title is awarded to does and bucks with top-tier PTAs 

(Predicted Transmitting Ability)

A blank value means this goat has not been awarded SG status.  (Note that ADGA is several years behind on awarding SG status)

Registry

This is a registry code that tells you whether a goat is purebred, American, or experimental. It’s an important detail when evaluating genetics or planning breedings.

 AM = American 

PB = Purebred

ER = Experimental Registry

RG = Recorded Grade

Fluid Merit $

A dollar-based index that estimates how much more (or less) milk value a goat is expected to produce compared to the breed average. It factors in actual milk test data for volume, butterfat, and protein, and is shown as a dollar difference from average.

Example:  Fluid Merit value of +52 means that, based on the goat’s genetics, her offspring are expected to produce milk with $52 more economic value per lactation than the average goat of the same breed.

Lactations

Number of lactations completed.

More lactations means increased reliability in the production evaluation numbers.  

2. Average STD Milk/Fat/Protein 

These are Standardized Production Averages - the actual production numbers averaged over the goat’s lactations, adjusted to a standard 305-day lactation. Look at all three together—Milk + Fat + Protein—to assess total productivity.

 

Keep in mind that average production varies by breed. Saanens and Alpines are typically high-volume milkers, while Nubians and Nigerian Dwarfs produce less milk but higher fat. To compare across breeds, check out 2024 Dairy Goat Milk Production Averages by Breed for more information production averages for specific breeds.

 

Parameter

What It Means

Example Interpretation

Average STD Milk

Average Standardized Milk 

How many pounds of milk she produces in 305 days (adjusted for age, etc.), based on actual milk test data. 

For Saanens, 2,800–2,900 lbs is average. 3,000+ is very good. High-performance herds aim for 3,500+. For Nigerian Dwarfs, 500–600 lbs is typical.

Average STD Fat

Average Standardized Fat 

Pounds of butterfat produced (adjusted for age, etc.), based on actual milk test data. 

In Saanens, 90–100 lbs is typical. 110+ is strong. Nigerian Dwarfs average 25-30 lbs.

Average STD Protein

Average Standardized Protein 

Pounds of milk protein produced (adjusted for age, etc.), based on actual milk test data. 

In Saanens, 80–85 lbs is average. 90+ is excellent. Nigerians average 15 lbs.

3. PTA – Predicted Transmitting Ability

PTA tells you how much better or worse the goat's offspring are expected to perform compared to the average.  This tells you what the goat is likely to pass on to her offspring, based on her genetics.  PTA numbers can help you pick great breeding animals. Always pair this with reliability to know how confident the prediction is.

 

Parameter

What It Means

Example Interpretation

Milk PTA

Predicted increase (or decrease) in daughters’ expected milk production vs the average. PTA compares expected production against the breed average (not relative to the doe herself).  

+397 means a doe's daughters are expected to produce 397 lbs more milk per 305-day lactation.  0 means average milk production is expected.   Negative PTA means less than average production is expected. 

Fat PTA

Predicted increase (or decrease) in daughters’ butterfat vs average.

+14.8 = 14.8 lbs more butterfat than average

–5 = 5 lbs less than average

Fat % PTA

Expected difference in fat percentage.

–0.08 = slightly leaner milk

+0.15 = slightly richer milk

Protein PTA

Predicted increase (or decrease) in daughters’ protein vs average.

+11.5 = daughters are expected to produce 11.5 lbs more protein than average

Protein % PTA

Expected change in protein percentage.

-0.08 = slightly leaner milk protein content

+0.10 = slightly richer milk protein content

Reliability (%)

Confidence level in each PTA based on amount of data.  More daughters increases the reliability rating.

51% = early estimate (2–3 lactations)

85% = high confidence (many daughters)

4. PPA – Predicted Producing Ability

PPA is different than PTA—this is a prediction of what the goat herself will do in future lactations based on her actual records so far.  Use this to assess a doe’s actual producing consistency.  A high PPA means she’s a reliable performer.

 

Parameter

What It Means

Example Interpretation

Milk, PPA

Pounds of milk expected above breed average.

+963 PPA means this doe is expected to produce 963 lbs more milk than average per lactation.  Negative PPA means she is expected to produce less than average.

Fat, PPA

Pounds of fat above average.

+381 PPA = 381 lbs more butterfat than average for her breed

Protein, PPA

Pounds of protein above average.

+300 PPA = 300 lbs more protein than average

5. Percentile Rank

Parameter

What It Means

Example Interpretation

Percentile Rank

This number shows how a goat compares to all other tested animals in the same breed—based on milk, fat, protein, and overall production traits.

 

High-ranking does are valuable for improving herds and producing high-performance offspring.

A percentile rank of 90+ means she’s in the top 10% of her breed for production performance. A score of 95 or higher is considered elite, placing her among the very best in the country. Percentile rank is calculated from actual DHI milk test records and offers a quick way to see how a doe stacks up against others in the same breed.

 

 

Evaluating Goats with Limited Data

Not every goat will have high performance numbers —  sometimes it’s not about poor performance at all.  You may come across production evaluations with missing values, blank lactation records, or very low percentile ranks. So what does this mean?

Missing data does not mean it's a bad goat

Sometimes a goat’s evaluation shows all zeros or blanks. This usually just means the doe has never been on official milk test, or she was tested briefly without completing a 305-day lactation. In either case, there’s not enough information for the system to calculate accurate values.  Many high-quality goats never go on test due to owner choice or lack of access to a DHI program.

 

In cases like this, you might see:

 

Lactations = 0

Average STD Milk/Fat/Protein = 0

PTA and PPA = 0 or missing

Percentile Rank = very low (usually <20)

 

These numbers don’t reflect her actual ability—they simply mean there’s no data to evaluate.

 

Limited data gives an incomplete picture

If a doe has only one recorded lactation, her scores might be skewed. For example, a doe who was tested once, early in life, or during a challenging season may look underwhelming on paper—even if she went on to become a consistent producer.

 

You might see:

 

A low percentile rank (e.g. 18%)

Negative PTA values, simply because there’s not enough data to prove otherwise

Reliability scores under 40%, which means the system isn’t confident in the predictions

 

Use Caution When Comparing

When a goat has little or no data, it’s not fair to compare her directly to a doe with 3+ completed, tested lactations. Performance evaluations reward animals with long-term, consistent records—so incomplete or partial data often leads to underestimation, not underperformance.

 

If you’re evaluating a goat with minimal data:

 

Look deeper into her pedigree, especially tested relatives with more production evaluation data.

Sires, dams, and siblings can give clues about what she may produce over time. Pay special attention to traits that show up consistently across generations.

Consider her linear appraisal, if available. 

Even without milk test records, appraisals provide a snapshot of structural strengths and weaknesses that often correlate with long-term productivity and soundness.

Evaluate her based on structure, temperament, and consistency on your farm. 

A goat that maintains body condition, milks steadily (even off-test), and fits well into your system is valuable—even if she lacks numbers on paper.

Be patient with young does or new additions.  

Some of the most valuable animals start off with little or no data but build a strong record over time. Early records can be misleading—especially if a doe was freshened young, had complications, or wasn’t given full opportunity to perform.

Use common sense and context. 

If a doe’s only record is a short or interrupted lactation, her numbers might look low—but that doesn’t reflect her full potential.

Watch for consistency in real-world performance. 

Even without official records, you can track things like udder fill, butterfat feel, and overall milk-out experience.  Notes from a trusted breeder or your own hands-on experience matter.

Understanding production evaluations can feel overwhelming at first, but each number tells part of the story. When used together—PTA, PPA, standardized averages, and percentile rank—they offer powerful insight into both genetic potential and proven performance. Whether you’re making breeding decisions, evaluating purchases, or tracking your own herd’s progress, these tools help bring objectivity to a process that also relies on hands-on knowledge and thoughtful observation. The more we understand the data, the better we can breed for healthy, productive goats for generations to come.

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We’ve done our best to ensure the accuracy of the information in this article, but mistakes can happen—especially as programs and data evolve. If you spot an error or have updated information to share, please contact us so we can keep this resource as helpful and accurate as possible.