Evaluating Future NFL Stars Through BackCAST Projections

Evaluating Future NFL Stars Through BackCAST Projections

The NFL draft is almost here folks! No wonder we’ve all turned to the incoming class of running back prospects who might follow in Barkley’s footsteps and produce immediate dividends on an NFL stage. Among the systems built to predict these players’ potential is BackCAST, a projection model developed by Nathan Forster. This unique system creatively blends together multiple metrics. It predicts running backs achieving the value of their first five years in the NFL versus an “expected” drafted back.

When scanning for prospects, BackCAST takes a holistic approach, looking not just at financials. Specifically, it examines their size-speed blend, college-era yards per carry average and the percentage of their collegiate program’s rushing game they represented. This detailed analysis allows BackCAST to determine a BackCAST score. This score is an indication of how much a running back is expected to exceed the value of an average player selected in the same draft slot. A score of plus-50% simply means that the prospect is projected to accumulate 50% more yards. This performance is way better than the average running back who gets selected in the draft.

For the next 2025 NFL draft, BackCAST has already found nine running backs who scored more than 40%. This combined score is predictive of which prospects will outperform their peers in the league. The system ranks these athletes based on their expected performance, offering insights into which players might become key contributors at the professional level.

Ashton Jeanty, Oklahoma State another good prospect. It is the incentive many believe, and have been rewarded with all the attention he’s caught with his huge contributions to his college team’s running game. BackCAST appreciates the trust the Oklahoma State coaching staff had in Jeanty. They depended on him to set up a huge part of their offense, underlining his essential presence to the team’s overall chess match. This broad use is important especially. It feeds into BackCAST’s Average Opportunity per Every Snap (AOEPS) metric, which compares a prospect’s utilization to the average drafted running back.

BackCAST deeper than merely examining hurry stats. It incorporates a RecIndex metric that tracks a player’s value as a receiving back. High Positive RecIndex scores indicate a player has a very high ceiling as a receiver. This increases a running back’s overall value in the NFL even more.

As the draft date soon approaches, teams will surely continue to use data-backed systems, such as BackCAST, to guide them to better, fact-based choices. By using specific forecasts and comparisons to NFL history, BackCAST is a tremendous resource for assessing running back talent.

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Alex Lorel

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