Penn

2026 · descriptive season · nil-value-v3 · Team results

Roster valuesβ

Roster values for Penn, 2026: retrospective net points per 100 possessions and, for 2025–26 only, a speculative compensation best guess. Players are listed by possession share, not by value or dollars.
Player	Possession share	Net and range	Wins above replacement and range	Speculative compensation (best guess)	Compensation 80% range
TJ Power	88.6%	+2.0range +1.1 to +2.8Sufficient evidence	+6.3range +5.7 to +6.8Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Michael Zanoni	74.2%	-0.4range -1.6 to +0.7Sufficient evidence	+4.3range +3.7 to +4.8Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
AJ Levine	62.7%	+0.7range -0.6 to +2.1Sufficient evidence	+4.1range +3.4 to +4.7Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Ethan Roberts	59.9%	+0.8range -0.1 to +1.8Sufficient evidence	+3.9range +3.5 to +4.3Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Augustus Gerhart	51.0%	-0.1range -0.9 to +0.7Sufficient evidence	+3.1range +2.6 to +3.4Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Lucas-Allan Lueth	37.2%	+1.4range +0.8 to +2.2Sufficient evidence	+2.6range +2.4 to +2.9Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Cam Thrower	37.0%	+1.2range +0.4 to +2.1Sufficient evidence	+2.5range +2.3 to +2.8Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Dalton Scantlebury	36.4%	+2.4range +1.1 to +4.1Sufficient evidence	+2.8range +2.4 to +3.2Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Jay Jones	28.7%	+1.4range +0.2 to +2.3Sufficient evidence	+2.0range +1.8 to +2.2Sufficient evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Niklas Polonowski	10.4%	-2.0range -2.7 to -1.3Limited evidence	+0.5range +0.4 to +0.6Limited evidence	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Dylan Williams	4.5%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Alex Massung	3.6%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Michelangelo Oberti	3.6%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Johnnie Walter	1.4%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
Payton Kamin	0.4%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading
William Kruse	0.3%	Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence	Not applicable	$0 (assumed opted out)Loading	80% range $0 to $0 (assumption, not data)Loading

Ranges are the 10th to 90th percentile of whole-game resampling draws. They are not calibrated intervals. Compensation is a speculative best guess of a share of the school's own revenue-sharing budget, not observed pay.

Team pool and per-player compensation · 2025–26β

Team Pool: $0 (assumed opted out); 80% Range $0 to $0 (assumed)
Tier: Low and other; low evidence

Assumed from one unverified press article that names schools that did not opt in. Methodology

No player figures. The Team Pool is $0.

What-if calculator on the team page

School Finances · School-Reported (EADA)

Self-reported to the U.S. Department of Education. Expenses cover coaching, travel, aid and operations, not player pay.

School-reported finances, 2024-25, University of Pennsylvania (NCAA Division I-FCS)
Measure	School-Reported Amount	Note
Men's basketball revenue	$2,357,216	Equals expenses (budget identity)
Men's basketball expenses	$2,357,216
Athletics department expenses	$59,309,407
Athletics department revenue	$59,309,407

Coverage and exclusions

28 of 29 games passed lineup acceptance (97%). 100% of accepted on-court possessions are bound to registered players.

1 of 29 audited games did not pass lineup acceptance; per-game reasons are counted for the whole season (see methodology), not per team

Program revenueβ

EADA year 2024-25 (alternate pairing to repo season 2026; fiscal-year mapping unconfirmed) · self-reported by the school, no external review · EADA revenue is any money used to pay expensesrevenue equals expenses

Reported revenue	$2,357,216	Reported by the school; not NIL pay and not a model output.
Reported expenses	$2,357,216	Reported by the school.

EADA link: matched to the registry school by a unique institution name and state.

No model-implied dollar range is shown (status: suppressed). The published dollar status could not be loaded; see NIL methodology for the reason.

Schedule loadβ

Counts are descriptive and associational, with neutral formatting. Consecutive away games is the only travel proxy; distance, time zones and injuries are not modeled.

Rest days before each game

Rest days	Games
First game (no rest value)	1
1 day	6
2 days	3
3 or more days	19

Rest is capped at three days. Descriptive count.

Load summary

Mean games in prior 7 days	1.1
Games with fewer rest days than the opponent	2
Longest run of consecutive away games	2

Association between rest and margin, all teams

Pooled association passes the declared test (gate S1); not causal and not specific to this team · 0.86 points of margin associated with each extra rest day, range +0.33 to +1.41

This is an association, not a causal lever, pooled across Division I and not specific to this team.

Manifest 13921361a27d · NIL methodology