How Valuation Works

Value is a range, not a single number — a low, mid, and high estimate of what a player's performance and tools are worth against your program's own configured budget benchmarks. It's a planning tool, not a promise: it is not an NIL offer, not a guarantee any player will sign for that figure, and not an appraisal any recruit, family, or coach should treat as authoritative on its own.

The range itself is deliberate, not a hedge. A player with thin data (one season, a couple of measurable events) gets a wide range, reflecting real uncertainty. A player with a deep, corroborated track record gets a tighter one. A narrow range on a thin profile would be a false confidence, not a better estimate.

A prospect's profile shows four money figures, and they answer four different questions. Estimated value is the range above — one year of scholarship plus your program's own institutional NIL / revenue-share allocation, priced from comparable signings at your level. It excludes commercial NIL (a brand deal or a collective's own arrangement with the player), which Sightline estimates separately and never adds in. Suggested allocation is one actionable number: that range's midpoint scaled by your interest level, by how much of your budget is still uncommitted, and by how many other recruits are competing for the same roster spot — so it can sit well below the estimate when a budget is nearly spent, on purpose. ‘Uncommitted’ there means the pool minus every commitment and every offer already out (an offer counts the moment it goes out); prospects you are merely considering are shown as pending and are not subtracted from that figure. Planned offer is what your staff has actually entered on the board; the engine never sets it, it only shows the gap. Signing risk is a 0–100 read (higher is riskier) on how exposed the program is at that price given what's on file — the offer as a share of what's left, your own talent grade, how complete the file is, academics and eligibility. It is not a probability the recruit signs, and paying more never guarantees a signing.

Ethan Whitfield is a catcher who enrolls in 2027, the season the demo program's two senior catchers have graduated. His estimated value is $12.5K–$19.5K (midpoint $16K, medium confidence). The board carries a planned offer of $15.5K — $13K scholarship plus $2.5K institutional NIL — which is −$0.5K against the midpoint. The suggested allocation is only $6.5K: $93K of a $1.9M pool is uncommitted, four other catchers are still under consideration, and the engine scales its suggestion to that reality rather than to the recruit's value alone. At the planned $15.5K, signing risk reads moderate — the offer is a meaningful share of what's left, offset by a strong file and hot interest. You can change the offer on his demo profile and watch all four numbers respond.

Six kinds of input feed a Value estimate:

A .350 average at a small HS program and a .350 average in a power-conference D1 lineup don't mean the same thing. Stats and tools are adjusted based on the level they were produced at before being compared to your program's level — a translation, not a raw pass-through.

This adjustment is honestly imprecise in places. Some level-to-level relationships (for example, how a HS hitter's numbers typically translate toward college competition) are grounded in published transfer-performance research. Others — most notably how a JUCO player's stats translate to a four-year program — have no public research to draw on at all; no study we could find measures that shift at a population level. Where that's true, the model applies a general, clearly-flagged estimate rather than pretending to a precision the data doesn't support, and that shows up as wider uncertainty in the resulting range.

Makeup, coachability, and character are not in this model at all — they matter, and Sightline doesn't attempt to quantify them. Injury history and risk are only as good as what's entered; the model doesn't independently assess medical risk. Small samples are handled by widening uncertainty, not by pretending a short run of good or bad games means more than it does.

Several inputs — including a handful of advanced batted-ball-quality metrics — are currently priced against seed estimates rather than measured population data, because no public research exists yet to calibrate them precisely. Where that's the case, the underlying constant is documented internally and gets replaced the moment real data is available, rather than being presented as more certain than it is.

Every input carries its own uncertainty, and that uncertainty is carried through to the final range rather than averaged away. A thin stat line, a single measurable reading, and a level-translation estimate with no real research behind it all widen the range they touch. The result: a wide range is the model being honest about what it doesn't know, not a hedge to protect against being wrong.

A player's School Matches tab grades their measurables against the recruit-target ranges that published recruiting sources (NCSA, NextCommit, Perfect Game's 2024 circuit data, Baseball America and 11point7 TrackMan reporting) quote for each level — NCAA Division I (Power-4 and mid-major where the source separates them), Division II, Division III, NAIA and NJCAA. The result is a tier per level, never a score per school: Above targets when every measurable on file is at or beyond the best end of the range, Meets targets when every one is inside or above it, Reach when some are below, Below targets when all are, Partial data when fewer than half the gradable measurables are on file, and Not enough data / No published targets when there is nothing to grade or nothing to grade against. Targets are quoted for recruiting-age (17U) players; underclassmen see Perfect Game's age-group tiers alongside for context. A core-course GPA under the NCAA D1 (2.30) or D2 (2.20) floor caps that level at Reach. SAT/ACT scores are shown but never graded — the NCAA removed test scores from Division I and II initial eligibility for students enrolling from August 2023 on.

Every range is transcribed from a research file that cites its source, and a test in the codebase fails if the numbers in the app ever drift from that file. Where a source publishes nothing for a level and position — several cells, all listed on the tab — the app says so instead of estimating. The player's own reading is their best value across every event on file, because targets are quoted as showcase tops.

The program list under the tiers is a filter, not a ranking. Sightline holds no per-school roster needs, admissions standards, cost, or scholarship data, so a school appears because its level fits and it matches the player's location filters — sorted by level tier, in-state, straight-line distance from hometown, and whether published coaching contacts are on file. A D1 program is graded against Power-4 targets only when its conference is on file from the NCAA member directory; otherwise the generic D1 tier is shown and the gap is labeled.