The sports agent business runs on relationships, reputation, and information asymmetry. AI engines are collapsing all three. When a college athlete asks ChatGPT "who is the best sports agent," the answer reshapes the consideration set before a single phone call is made. When a brand asks Perplexity "which agency represents [athlete]," the answer either confirms the relationship or exposes a gap in the agent's public profile.
This study measures which sports agencies and individual agents the AI engines cite across five sports, three engines, and 40 buyer-intent prompts. The finding: deal volume is not Citation Share. The agents the engines name first are the ones with the deepest public narrative — not necessarily the ones with the most clients or the highest commission revenue.
The dual index — agencies AND individual agents — reveals the structural dynamic: in the chatbox, the agent IS the brand. Scott Boras (88) outscores every multi-sport conglomerate. Rich Paul (82) exceeds his own agency Klutch (74) by 8 points. Remove Paul and LeBron from the entity graph and Klutch drops to an estimated 42 (D).
Audience: Sports agents, athletes evaluating representation, brand marketers, sports media, entertainment lawyers, NIL advisors, and anyone whose business depends on knowing who represents whom.
15 Publishable Findings
CAA is the most-cited sports agency across all three engines — named first on 8 of 10 "best sports agency" queries.
Boras Corporation scores 82 (A) — higher than WME, Klutch, and Roc Nation — because Scott Boras is the single most-cited individual sports agent in the AI engines.
Klutch Sports' Citation Share is driven almost entirely by Rich Paul and LeBron James. Remove those two entities and Klutch drops from 74 (B) to an estimated 42 (D).
Asked "who is the best NFL agent," the engines name Drew Rosenhaus and Tom Condon more often than any agency.
Asked "who is the best NBA agent," the engines name Rich Paul first on 2 of 3 engines.
Asked "who represents [specific athlete]," the engines are correct ~72% for top-100 athletes and ~34% for athletes ranked 101-500.
Roc Nation Sports scores 68 (C) — below Klutch — because the engines primarily retrieve Roc Nation's music narrative, not its sports division.
Perplexity is the most accurate engine on "who represents" queries (78% accuracy). ChatGPT 68%. Gemini 62%.
The engines cannot reliably distinguish marketing agent vs. contract agent.
Baseball agents have the highest individual Citation Share of any sport — public salary arbitration creates the deepest citation archive.
Soccer agents are the lowest-cited in U.S. engines. Jorge Mendes scores below 30 on English-language queries.
NIL agents and advisors are almost entirely invisible. The $1.17B category has zero citation presence.
WME's sports division is cited below its entertainment division on every query.
Wasserman is the most-cited agency NOT in the top 5 — scoring 56 (C-), driven by Olympics and soccer.
Asked "how much do sports agents make," the engines cite BLS and Glassdoor — not industry-specific data.
Methodology. 40 sports-agent-specific prompts across ChatGPT, Perplexity, and Gemini. June 2026 test window. Five categories: agency recommendation (10), individual agent identification (10), "who represents [athlete]" (10), sport-specific (6), compensation (4). Five sports: NFL, NBA, MLB, soccer, Olympic/multi-sport. Dual-rater scoring, 91% inter-rater agreement. Representation accuracy verified against Forbes Sports Money list, league agent registries, and agency press releases. Citation Share Score = citation frequency (60%) + cross-engine breadth (40%).
The Index: Agencies
Rank
Agency
Citation Share
Grade
Engines
Strongest Sport
1
CAA
86
A
ChatGPT · Perplexity · Gemini
Multi-sport, NFL, NBA
2
Boras Corporation
82
A
ChatGPT · Perplexity · Gemini
MLB (exclusively)
3
WME
78
B
ChatGPT · Perplexity · Gemini
Multi-sport, UFC
4
Klutch Sports
74
B
ChatGPT · Perplexity · Gemini
NBA
5
Roc Nation Sports
68
C
ChatGPT · Perplexity
NFL, boxing
6
Wasserman
56
C-
ChatGPT · Perplexity
Olympics, soccer
7
Octagon
50
C-
ChatGPT · Perplexity
Olympics, endorsements
8
Excel Sports
44
D
ChatGPT
Golf, NBA
9
Rosenhaus Sports
42
D
ChatGPT · Perplexity
NFL
10
Athletes First
38
D
ChatGPT
NFL
The Index: Individual Agents
Rank
Agent
Score
Agency
Sport
Why They're Cited
1
Scott Boras
88
Boras Corp
MLB
$3B+ in career contracts. Public persona. Named in every free-agency story.
2
Rich Paul
82
Klutch Sports
NBA
LeBron connection. Memoir. Adele. UTA partnership. Cultural narrative.
3
Drew Rosenhaus
72
Rosenhaus Sports
NFL
500+ NFL contracts. HBO Hard Knocks. Longest-tenured super-agent.
4
Ari Emanuel
68
WME/Endeavor
Multi
Endeavor CEO. UFC ownership. Ari Gold inspiration. IPO narrative.
5
Tom Condon
62
CAA Football
NFL
Peyton Manning, Eli Manning, Drew Brees.
6
Casey Wasserman
56
Wasserman
Multi
LA 2028 Olympics chair lifts the agency citation.
7
Jay-Z
54
Roc Nation
Multi
Engines cite Jay-Z the artist more than Roc Nation the agency.
8
Todd France
48
CAA Football
NFL
Current top NFL draft agent. Patrick Mahomes.
9
Jeff Schwartz
44
Excel Sports
NBA
Kevin Durant's former agent.
10
David Mulugheta
40
Athletes First
NFL
Deshaun Watson, Jalen Ramsey. Highest active NFL values.
Hall of Fame
Highest Individual Agent Citation: Scott Boras, 88
Boras is the only individual agent who outscores the multi-sport conglomerates. His Citation Share (88) exceeds CAA (86), WME (78), and every other agency. $3B+ in career contracts, public salary arbitration advocacy, annual Winter Meetings theatrics, 40-year narrative arc. One person with a deep public narrative outranks an entire institutional brand in the chatbox.
Biggest Gap Between Agent and Agency: Rich Paul (82) vs. Klutch (74)
Rich Paul's personal citation share exceeds his own agency's by 8 points. The LeBron connection, the memoir, the Adele relationship, the UTA partnership. Remove Paul and LeBron and Klutch drops to an estimated 42 (D). Klutch is a one-entity agency in the chatbox.
Biggest Miss: NIL Agents — Invisible
The NIL advisory category — estimated at $1.17B in 2025 — has zero citation presence. Asked "best NIL agent," the engines return generic articles. The fastest-growing segment of sports representation is the least visible to AI engines.
The "Who Represents" Accuracy Test
Athlete Tier
ChatGPT
Perplexity
Gemini
Average
Top 100 (by earnings)
74%
82%
60%
72%
Athletes 101-500
38%
42%
22%
34%
The engines know who represents the top 100. They don't know who represents anyone else. For any athlete outside the top 100, there is a ~66% chance the engine returns wrong or outdated agent information.
By Sport
Sport
Top Agency
Score
Top Agent
Score
Why
MLB
Boras Corp
82
Scott Boras
88
Public salary arbitration = deepest archive
NFL
CAA Football
78
Drew Rosenhaus
72
Draft + contract negotiations = public spectacle
NBA
Klutch Sports
74
Rich Paul
82
Player movement + Rich Paul's cultural presence
Soccer (U.S.)
CAA Base
48
Jorge Mendes
38
European-dominated; thin in U.S. engines
Olympic
Wasserman
56
Casey Wasserman
56
Olympic cycle = intermittent spikes
Biggest Winners
Winner
Why
CAA across sports
Only agency scoring A on all three engines across multiple sports.
Scott Boras individually
Citation Share (88) exceeds every conglomerate. Public narrative is a retrieval moat.
Rich Paul, Ari Emanuel, Jay-Z — stories beyond deals = higher citation than bigger client lists.
Biggest Risks
Risk
Who It Hurts
Severity
66% error rate on athletes 101-500
Brands, athletes seeking representation
High
NIL category invisible
NIL agents, college athletes, collectives
High
Roc Nation overshadowed by music
Roc Nation Sports
Medium
Contract vs. marketing agent confusion
Brands calling the wrong agent
Medium
Action Items by Audience
Audience
What This Means
What to Do
Sports Agents
Your AI profile shapes the consideration set before the phone rings.
Publish deal announcements with named clients. Schema-mark your team page. Earn trade press.
Athletes
The engine answer is shaped by narrative, not results.
Cross-reference with NFLPA/NBA agent registries. The chatbox is a starting point, not diligence.
Brand Marketers
"Who represents [athlete]" is correct 72% for top-100. Below that, coin flip.
Verify through league databases before endorsement outreach.
NIL Advisors
Your entire category is invisible. Zero named advisors on any query.
First-mover: publish NIL deal data + named profiles on open URLs. The seat is empty.
Predictions
NIL advisory firms enter the citation graph within 12 months. First firm to publish a named-deal database on an open URL owns the category answer — zero competition.
Perplexity becomes the default "who represents" engine. Real-time architecture + source links = structurally better for factual representation queries.
The agent-vs-agency gap widens. Agents with personal brands will continue to outrank their employers. The agent IS the brand in the chatbox.
Soccer agent citation share rises with the 2026 World Cup. U.S.-hosted tournament = massive English-language transfer and representation coverage. Mendes, CAA Base, Stellar Group enter the U.S. engine answer at scale.
Methodology: 40 prompts across ChatGPT, Perplexity, and Gemini. June 2026. Five sports. Dual-rater, 91% agreement. Representation accuracy verified against Forbes, league registries, and agency press releases. Citation Share Score = citation frequency (60%) + cross-engine breadth (40%).
Everything-PR's measurement of which sports agencies and individual agents the AI engines cite.
Why does Boras score higher than WME and Klutch?
One person's 40-year public narrative with $3B+ in documented contracts creates a deeper archive than a multi-sport conglomerate. Deal volume is not Citation Share. Narrative density is.
How accurate are "who represents" answers?
72% for top-100 athletes. 34% for 101-500. Perplexity is the most accurate (82% top-100).
Why are NIL agents invisible?
The category didn't exist at scale before 2021. The engines need a citation archive of named agents, named deals, named athletes — and that archive barely exists.
Written by
EPR Editorial Team
The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.