A hundred yards is a hundred yards. What it means depends on who was trying to stop you.
Every draft cycle brings a familiar argument. A receiver from a small programme piles up huge numbers, and half the room declares him a steal. The other half says the numbers came against opponents who would struggle to start in a bigger conference. Both camps have a point, which is exactly why the question is hard.
Comparing players across levels of competition is one of the central problems in draft evaluation. It matters most for prospects from the FCS, Division II, Division III, the NAIA and HBCU programmes, where the film is harder to find, the schedule is different and the gap to the NFL is harder to judge. There is no perfect answer, but there is a sensible process, and it beats both blind enthusiasm and reflexive dismissal.
Why Raw Numbers Mislead
Statistics describe what happened, not how hard it was. A pass rusher’s sack total, a running back’s yards per carry or a quarterback’s completion percentage all depend on the quality of the opponents, the scheme, the supporting cast and how often the game script put the player in a favourable spot.
This works in both directions. Gaudy production against weaker opponents may overstate a player’s ability. But a player on a strong small-school team who dominates every week might simply be ready for a bigger stage, and dismissing him because of the logo on the helmet is its own kind of bias. The goal is not to discount every small-school player automatically. It is to ask what the numbers do and don’t prove. Start With the Film
When you watch a prospect from a smaller programme, the questions are slightly different from those you’d ask about a player from a top conference.
Look at how he wins. Is it through technique, such as footwork, hand placement, route-running or processing, that would translate against better athletes? Or is it mostly size and speed advantages that disappear against NFL-calibre opponents?
Look at the best opponent on the schedule. If there is a game against a bigger programme, an FBS opponent or a standout defender, give it extra weight. A player who holds his own in those snaps is giving you the closest thing to a direct comparison that the season provides.
Look at what he does when he is not dominating. Plays where he is double-teamed, tracked by a better player or forced to work through traffic show more about his game than the highlights.
Add Context to the Numbers Once the film is in view, a few pieces of context help calibrate the statistics.
Strength of schedule. Not all small-school schedules are equal. Some FCS and HBCU programmes play several games against larger opponents each season, while others rarely do.
Role and usage. Was he the focal point of the offence or defence, or one of several contributors? A receiver who was clearly the first read on every play had different opportunities from one sharing targets.
Per-play rates. Totals reward volume. Rates such as yards per route run, yards after contact, pressure rate or targets per snap give a cleaner picture of efficiency, though they still need context.
Age and experience. A fifth-year player producing against younger opponents tells a different story from a young player who is still developing.
Level of competition in postseason events. All-star games, showcases and combine drills put prospects on the same field as players from other programmes. These settings are short and noisy, but they are one of the few places where direct comparisons happen. None of these factors settles the question alone. Together, they narrow it.
Build a Simple Comparison Framework
A framework keeps evaluation consistent and exposes your own biases. The idea is to line prospects up against the same criteria, whatever school they come from.
Start by choosing a handful of measurable inputs for each position: efficiency rates, athletic testing results, performance against the toughest opponents and any physical thresholds that matter for the role. Then add a column for the level of competition, such as a simple adjustment or tier that reflects how much you trust the production. The adjustment will always be somewhat subjective, which is fine as long as you apply it consistently and write down how you chose it.
Then give each factor a weight, compute a score and compare. If a small-school prospect ranks above a power-conference player, check why. Is it production alone? Or does the tape and testing back it up? If the model and your eyes disagree, treat that as a prompt to look again, not as a verdict.
The framework also lets you test your assumptions. Change the competition adjustment from small to large and see how much the rankings move. If a prospect only looks good under a very generous adjustment, you have learned something useful about how much of his case rests on a single assumption. Putting It Into a Spreadsheet
This kind of comparison is far easier to manage in a spreadsheet than in your head. A sheet lets you list players in rows, factors in columns and weights in a separate area, so you can change a weight once and watch every score update. It can also sort prospects by total score, pull a player’s numbers from a data tab with a lookup and calculate per-play rates from raw totals.
The skills involved are not advanced, but they do need to be solid. Anyone building a comparison sheet should be comfortable with averages, weighted sums, sorting, filtering and lookups, because small formula mistakes can quietly distort a ranking. A quick Excel evaluation of your own skills is a sensible first step: if you can complete a short set of tasks, such as combining two tables, calculating a weighted score and sorting the result, you are ready to build the sheet with confidence, and if you stumble, you know which functions to review first.
Keep the Limits in View
A model is a tool, not an oracle. Some of the most important traits for a pro, including processing speed, competitiveness, football intelligence, work habits and response to coaching, are poorly captured by any spreadsheet. Injuries, scheme fit and development environment can matter as much as raw ability.
Small-school evaluation also suffers from thinner data. Some programmes have limited film, incomplete statistics or fewer opportunities for direct comparison, and that uncertainty should be reflected in how confident you sound. Saying “this player is intriguing, and here is what would raise or lower my confidence” is more honest, and usually more useful, than a false certainty in either direction. The Takeaway
Evaluating prospects from smaller programmes means holding two ideas at once. Production against lesser competition deserves scepticism, and a talented player from a small school deserves a fair look. The way through is a consistent process: watch the film, add context, build a transparent comparison and stay open about what you don’t know.
Do that, and you will be better placed to spot the diamonds, and to avoid falling for numbers that looked better than they were.
NFL Draft Diamonds was created to assist the underdogs playing the sport. We call them diamonds in the rough. My name is Damond Talbot, I have worked extremely hard to help hundreds of small school players over the past several years, and will continue my mission. We have several contributors on this site, and if they contribute their name and contact will be in the piece above. You can email me at nfldraftdiamonds@gmail.com
