Umberto Gigli

Umberto Gigli

B

Minneapolis Blizzards · Post Scorer / Anchor Big

College: Stanford · Arzignano, Italy

Long shot-blocking center

A rotation center averaging 6.5 PPG, 4.7 RPG, 0.6 APG. Excels in 1.23 BPG (80th pctl), post execution (14 rating, 79th pctl) and mid-range shooting (15 rating, 77th pctl). Limited by passing (3 rating, 1st pctl) and finishing (8 rating, 4th pctl).

49
Impact
3
CA
3
PA
23
Age
$4.3M
Salary
Stat Value Pctl
Per Game
PPG 6.5 41
RPG 4.7 72
APG 0.6 21
SPG 0.20 18
BPG 1.23 80
MPG 17.6 46
Shooting
FG% .566 90
3P% .500 98
FT% .691 19
TS% 0.597 68
Impact
Impact 49 48
Off Impact 41 12
Def Impact 53 70
Advanced
PER 12.9 34
WS 2.8 58
BPM -1.8 27
VORP 0.1 40

Strengths & Weaknesses (Win Model)

Strengths
Defensive Rebounding 15 (coef=0.0204)
Offensive Rebounding 16 (coef=0.0145)
Help Defense 15 (coef=0.0134)
Rim Protection 14 (coef=0.0122)
Foul Drawing 15 (coef=0.0080)
Weaknesses
Pick & Roll Execution 8 (coef=0.0152)
Inside Shooting 15 (coef=0.0145)
3PT Shooting 6 (coef=0.0122)
Athleticism 8 (coef=-0.0111)
Isolation Execution 5 (coef=0.0096)

Play Style

Driving Frequency
19%
Roll : Pop
73:27
Catch & Shoot : Pull-Up
87:13
Corner 3 : Above the Break
79:21

Positional Fit

Guard 0%
Wing 0%
Big 60%

Player Impact Breakdown

Average score driven by weak win-model ratings. Defense is the primary value driver.

49 / 100 #296 of 503
On-Court Impact (EPM) — 60% weight +0.25z
EPM +0.64 (Off +0.73, Def -0.13)
Win-Model Ratings — 25% weight -1.11z
Ridge coefficient score: -0.0574
Hidden Intangibles — 15% weight +0.92z
WS/48 residual: +0.0511 (actual vs predicted from ratings)
Offense
41
#452
Defense
53
#173
Confidence
94%
1442 min
Tendencies
Salary
$4.3M
Years Left
3
Expiry
End of 2051
Option
Team Option
Status
Rotation
Trade Value
0.406

Contract Breakdown

Season Salary Notes
2050-51 $4,300,000
2051-52 $4,300,000 Team Option
Total Owed $8,600,000

Win Model Development

WM Score
2.047
Expected WM
2.287
Dev Residual
-0.2400
Peak Age
33
Peak WM
2.315
PA Tier
Medium
Upside Gap
0
Dev Status
Behind Curve
Win Model Score = sum(rating * Ridge coefficient). Measures predicted win contribution from ratings — unbiased across positions.

Win Model Trajectory

Most Similar Players

Player Team Age CA Similarity Archetype
C
Chase Camby New York Renegades 20 3.5 99.0% Post Scorer / Anchor Big
J
Jalen Humphrey Miami Cyclones 29 4.0 99.0% Roll-and-Cut Big / Anchor Big
K
Kepa Lagares San Diego Calaveras 24 3.5 98.5% Post Scorer / Anchor Big
D
Devon Walton New York Renegades 26 4.0 98.5% Roll-and-Cut Big / Mobile Big
P
Paris Salas Houston Lightning 27 3.5 98.5% Roll-and-Cut Big / Anchor Big

Predicted Archetype

Offensive
Defensive
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