For many NFL bettors, betting analysis follows the same patterns as it has done for years. Analysis relied on team form (measured in wins/losses), league position and big player stats like total yards or touchdowns. However, the modern NFL data systems are much more comprehensive. Sharp bettors are taking advantage by analyzing underlying stats that can tell more about a team’s performance than just whether they won or lost.
One great example is EPA or Expected Points Added. This is a measurement that tells you how many points a play should make based on historical data and positioning. Other stats are equally useful and are changing the way bettors look at the NFL.
In 2026 there is a lot of information, data and opinion to sift through if you’re trying to make an educated NFL bet. This has been further complicated by the rise of prediction market platforms, which add trading elements and market pricing into the equation.
For example, take a closer look at the Underdog promo as discussed by Covers. Here you’ll see a lesser-known prediction market and sportsbook assessed in great detail, from the bonus fine print to its payment options and user experience. This shows just how much choice there is for players on the betting market, alongside the mechanics of picking an individual wager.
That is part of the reason bettors are turning to more complex statistical analysis. These are ideas and concepts that go beyond the headline numbers all bettors are now used to looking at and they include:
By using EPA bettors can work out if a team is truly performing well, or just having a little luck swing their way. The eye test and narrative analysis can also tell you some of this, but the narrative especially can often diverge from the statistical reality in some surprising ways.
For example, an eight yard gain on first and 10 is less significant (less EPA) than the same yardage on a third and seven. EPA takes all this into account by giving each play a score – which lets fans, analysts and bettors see a quantified metric of team performance beyond win or loss
As another example, consider a 4-1 team that may look like a heavy favorite against a 2-3 team. However, if the results of the 4-1 team were well ahead of EPA scores across all their plays while the 2-3 team had high EPA in some unlucky losses, you could make a case for the 2-3 team having better underlying form.
This can be especially powerful when looking at teams towards the end of a season. A strong team might come away with victories against weaker opposition, while not playing well, or vice versa, and EPA scores across the games will reflect that more than the league table positions or win loss. EPA can also be adjusted to favor more recent results, giving a better picture of form across the season.
Another interesting example of underlying statistics that may shine a light on something hidden by actual results is in player form.
For example, consider running back A with 8 yards per carry across 12 attempts in two games. On the other team is a running back B with 5 yards per carry but 20 attempts in four games. While player B has more yards total, they have also had more opportunities in more games.
A player can’t score good numbers in plays they don’t make. So although the yard averages and efficiency of running back A are higher, for whatever reason they aren’t getting involved in enough plays or games.
This would make running back B a better candidate for the Over in many games, even though they have statistically been less efficient. On the other hand, if running back A’s team suddenly found attacking form and started getting them involved in plays – they could be a candidate for an underdog bet or a fantasy swap.
However, form is not always about results. Eventually, history will usually judge it as such. But in the short term it can make teams look better or worse than their actual performance data shows.
A player can score five touchdowns in three games. This might make many bettors pick them to score again the following week. However, if their team’s overall stats are poor and the EPA was low for most of those scores then a smart bettor might be wary.
Form isn’t just down to headline numbers and results. It can instead be analyzed by looking at the processes below the production output and how they have changed.
For example, a receiver with 80 yards averaged over the season might look like a nailed on candidate for the Over prop in almost any game. However, if their team is facing an elite defense and his target share has been declining in the recent games, the yard average may not tell the whole story. Which is why stats like EPA and efficiency are increasingly used by NFL bettors in 2026.
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