What is the NIL Go clearinghouse and how does it review deals in 2027?

Question

Pulse RevOps · The Machine · Accepted Answer

Published Jun 14, 2026 · Updated Jun 14, 2026

## Direct Answer

**NIL Go is the College Sports Commission's online clearinghouse — built with Deloitte — that reviews every third-party NIL deal worth $600 or more to confirm it reflects fair market value and a legitimate business purpose.** Launched to enforce the **House** settlement, it functions like a corporate **deal desk**: athletes submit deal details, and **Deloitte** benchmarks them against a database of thousands of past college and professional NIL deals to make **fair-market-value** determinations. The screening has teeth — Deloitte estimated as many as **70%** of past collective deals would have been rejected under the new formula. In a recent January–February window, the system cleared **3,704** deals worth **$39.29 million** and rejected **187** deals worth **$14.36 million**, with roughly **50%** resolved within **24 hours** and **70%** within **seven days**. The clearinghouse is already **strained** by a surge in school-linked deals.

For RevOps, NIL Go is a real-world **approval-workflow and fair-market-value engine** — the same machinery as a deal desk that validates pricing against benchmarks, enforces thresholds, and runs to an SLA.

## 1. How NIL Go Works

### A threshold and a review

Every third-party NIL deal at or above **$600** must be submitted to **NIL Go** for review against the **House** settlement rules. Below the threshold, deals pass without review; at or above it, they enter the clearinghouse. That is a classic **approval threshold** — concentrate scrutiny on deals large enough to matter.

### Two tests: value and purpose

Each deal is judged on two criteria: does it reflect **fair market value**, and does it serve a **legitimate business purpose** (real marketing services) rather than disguised pay-for-play. **Deloitte** administers the system and makes the value determinations.

```mermaid
flowchart TD
  A[Athlete Submits NIL Deal] --> B{Value >= $600?}
  B -->|No| C[No Review Required]
  B -->|Yes| D[NIL Go Clearinghouse]
  D --> E[Fair Market Value Test]
  D --> F[Legitimate Business Purpose Test]
  E --> G{Pass Both?}
  F --> G
  G -->|Yes| H[Approved]
  G -->|No| I[Rejected]
```

## 2. The Fair-Market-Value Engine

### Benchmarking against a deal database

To decide whether a deal is fairly priced, **Deloitte** leverages a database of **thousands** of past NIL deals — college and professional — to establish **benchmarks**. A submitted deal is compared against comparable deals to judge whether the price is real or inflated to funnel money to an athlete.

### The 70% signal

Deloitte stated that as many as **70%** of past collective deals would have been **rejected** under the new formula — a striking signal that much pre-clearinghouse "NIL" was priced well above market to function as pay-for-play. The benchmark engine exists precisely to catch that gap between stated price and real value.

```mermaid
flowchart LR
  A[Submitted Deal Price] --> B[Compare to Deloitte Benchmark DB]
  B --> C{Within Market Range?}
  C -->|Yes| D[Legitimate Value - Approve]
  C -->|No| E[Inflated - Likely Reject]
  E --> F[~70% of Old Collective Deals Fail]
```

## 3. Throughput, SLAs, and Strain

### The numbers so far

In one January–February window, **NIL Go** cleared **3,704** deals worth **$39.29 million** and rejected **187** worth **$14.36 million**. Note the asymmetry — a small number of large, high-dollar deals drove most of the rejected value, exactly where scrutiny should concentrate.

### Speed and the bottleneck

Roughly **50%** of submissions resolve within **24 hours** and **70%** within **seven days** once complete information is provided. But the system is **strained** by a surge in school-linked deals that require greater investigator scrutiny, lengthening reviews and frustrating schools and attorneys. The clearinghouse, like any deal desk, slows when volume and complexity spike.

## 4. The RevOps Lessons

### Set thresholds so scrutiny scales with value

The **$600** floor is a textbook **materiality threshold** — review what matters, auto-pass what does not. RevOps deal desks should do the same: route small, standard deals straight through and reserve human review for the deals large or non-standard enough to carry real risk. The rejected-value asymmetry proves the few big deals are where the exposure lives.

### Validate price against benchmarks, not opinion

NIL Go's fair-market-value engine is benchmark-driven, not subjective. RevOps should price and approve the same way — validate discounts and non-standard terms against a **benchmark of comparable deals**, so approvals are consistent and defensible rather than dependent on whoever reviews them.

### Publish the SLA and staff for peaks

The strain story is the warning. A deal desk that does not staff for peak volume becomes the bottleneck that slows revenue. RevOps should set a clear **review SLA**, measure resolution times, and add capacity before predictable surges

What is the NIL Go clearinghouse and how does it review deals in 2027?

Direct Answer

1. How NIL Go Works

A threshold and a review

Two tests: value and purpose

2. The Fair-Market-Value Engine

Benchmarking against a deal database

The 70% signal

3. Throughput, SLAs, and Strain

The numbers so far

Speed and the bottleneck

4. The RevOps Lessons

Set thresholds so scrutiny scales with value

Validate price against benchmarks, not opinion

Publish the SLA and staff for peaks

5. What to Watch

FAQ

Bottom Line

Sources

What is the NIL Go clearinghouse and how does it review deals in 2027?

Direct Answer

1. How NIL Go Works

A threshold and a review

Two tests: value and purpose

2. The Fair-Market-Value Engine

Benchmarking against a deal database

The 70% signal

3. Throughput, SLAs, and Strain

The numbers so far

Speed and the bottleneck

4. The RevOps Lessons

Set thresholds so scrutiny scales with value

Validate price against benchmarks, not opinion

Publish the SLA and staff for peaks

5. What to Watch

FAQ

Bottom Line

Sources

What does the score mean?