Carter Rose : D

#5 | Brasher Falls, NY

Career Skater Statistics

Season	Class	GP	G	A	PTS	P/GP	+/-	PIM	SH	SH%	PPG	SHG	GWG	BLK	PACE
2025-26	Sophomore	37	2	8	10	0.27	-2	22	36	5.6%	0	0	1	23	0.85
CAREER TOTAL		37	2	8	10	0.27	-2	22	36	5.6%	0	0	1	23	0.85

Player Movement History

-Transferred from Clarkson University before the 2025-26 season.

Career Progression & Performance Tracking

Detailed Game Log

Season:

Date	Opponent	Result	G	A	PTS	+/-	PIM	SH	GWG	BLK
03/14/26	Princeton	L 2-5	0	0	0	0	0	1	0	0
03/13/26	Princeton	L 2-5	0	0	0	-2	0	0	0	1
03/07/26	Brown	W 9-0	0	1	1	+1	2	0	0	0
02/28/26	Brown	W 3-0	0	0	0	+2	0	1	0	0
02/27/26	Yale	W 5-4	0	0	0	-1	0	0	0	0
02/21/26	Dartmouth	T 3-3	0	0	0	-1	0	4	0	2
02/20/26	Harvard	W 4-1	0	0	0	+1	0	1	0	1
02/14/26	Cornell	W 4-1	0	0	0	+1	0	0	0	0
02/13/26	Colgate	W 7-6	0	0	0	0	0	0	0	0
02/07/26	Clarkson	L 7-8	0	0	0	-1	0	1	0	3
02/06/26	St. Lawrence	W 4-1	1	0	1	0	0	1	1	0
01/30/26	Dartmouth	L 2-4	0	0	0	-2	0	0	0	1
01/24/26	RPI	W 5-4	1	0	1	0	2	3	0	0
01/19/26	Harvard	L 0-4	0	0	0	0	0	1	0	0
01/17/26	Yale	L 1-4	0	0	0	0	0	2	0	0
01/16/26	Brown	W 4-0	0	0	0	0	0	3	0	0
01/10/26	Princeton	W 4-2	0	0	0	+1	0	3	0	1
01/09/26	Quinnipiac	L 2-7	0	0	0	-1	0	2	0	3
12/13/25	Alaska Fairbanks	W 3-2	0	0	0	-1	2	1	0	0
12/12/25	Alaska Fairbanks	W 5-1	0	0	0	0	0	1	0	2
12/06/25	Quinnipiac	W 4-0	0	0	0	0	0	0	0	0
12/05/25	Princeton	L 1-5	0	0	0	-1	0	1	0	0
11/30/25	Miami	L 2-3	0	0	0	-1	2	0	0	0
11/28/25	Sacred Heart	W 8-1	0	2	2	+4	2	0	0	0
11/22/25	Colgate	T 4-4	0	1	1	-1	0	0	0	0
11/21/25	Cornell	L 1-2	0	0	0	0	2	0	0	0
11/15/25	New Hampshire	W 6-0	0	0	0	+1	0	2	0	1
11/14/25	Massachusetts Lowell	W 7-1	0	1	1	+1	2	2	0	1
11/08/25	St. Lawrence	W 5-2	0	0	0	-2	2	1	0	1
11/07/25	Clarkson	L 1-5	0	0	0	0	2	1	0	1
11/01/25	RPI	W 3-0	0	0	0	0	2	0	0	1
10/31/25	RPI	L 2-5	0	1	1	0	2	0	0	0
10/18/25	Niagara	W 6-0	0	0	0	0	0	0	0	1
10/17/25	Niagara	W 3-2	0	0	0	-1	0	1	0	0
10/11/25	Mercyhurst	W 5-3	0	1	1	+1	0	2	0	0
10/10/25	Mercyhurst	W 5-2	0	1	1	-1	0	1	0	2
10/04/25	Army	T 1-1	0	0	0	+1	0	0	0	1

Historical Counterpart Matrix

Historical lookalike matches calculated via production paces through their corresponding class rank milestone season.

PACE 0.85

Streich, Sean

Through Sophomore Year • PACE Score: 0.86

100%

Buote, Andrew

Through Sophomore Year • PACE Score: 0.83

99.9%

Campolieto, Joseph

Through Sophomore Year • PACE Score: 0.82

99.9%

Henry, Noah

Through Sophomore Year • PACE Score: 0.83

99.9%

Todd, Alex

Through Sophomore Year • PACE Score: 0.8

99.8%

Historical Data Limitations

Note: Blocks and +/- were not recorded until the 2005-06 season, and shot data is missing from 1998-99 through 2004-05.

Skater Metrics

G / A / PTS: Goals, Assists, Total Points
P/GP: Points Per Game (Total Points ÷ Games Played)
GP: Games Played
+/-: Plus/Minus (Even strength/SH goals for vs against)
SH%: Shooting Percentage (Goals ÷ Shots on Goal)
PPG: Power Play Goals
SHG: Short-Handed Goals
BLK: Blocked Shots
PIM: Penalty Minutes
PACE: Player Action & Contribution Estimate (0-Baseline Accumulative WAR)

Goalie Metrics

Wins: Total Victories
Save%: Save Percentage (Total Saves ÷ Shots Against)
Shutouts: Games completed with zero goals against
PACE: Player Action & Contribution Estimate (0-Baseline Accumulative WAR)

Player Action & Contribution Estimate (PACE) Definitions

The Basics

The 0-Baseline WAR Calculation: Each player's raw production from boxscore statistics is converted into a value rating. We then subtract a positional replacement-level threshold. Finally, the rate is scaled by a mathematically optimized variance factor to convert it into an authentic win share, similar to WAR in baseball.

Expected Wins: We enter the team's accumulated roster PACE into a standard regression formula to convert cumulative player impact into expected wins in the standings. Under this framework, a theoretical roster consisting entirely of replacement-level talent mathematically projects to a baseline floor of minimal wins per season.

Expected Ties & Losses: Regression analysis reveals a direct correlation between Goaltending PACE and tie rates, as elite goaltending acts as a survival mechanism that actively preserves lower-scoring games into overtime. The engine calculates an expected tie rate derived from total goaltender workload and efficiency, and assigns the remaining schedule balance to the loss column.

Skaters Base Score

The skater tracking model evaluates game sheets chronologically, assigning algorithmic weights across multiple production domains:

Even Strength Goals: Weighted for baseline value impact.
Power Play Goals: Adjusted for standard special teams value.
Short Handed Goals: Premium weight applied for high-leverage scoring.
Assists: Accounted for uniformly across line scoring sequences.
Shot Generation: Evaluated to measure individual offensive creation.
Blocked Shots: Accounted for by volume, factoring in a defensive suppression workload adjustment for defensemen.
Penalty Minutes: Applies a progressive deduction to account for disciplinary leverage shifts.

Note: The final sum is reduced by a calibrated positional replacement level per game played, then scaled to determine total Wins contributed. Defensemen receive a structural normalization adjustment to mathematically balance their output against forwards on the league-wide leaderboard.

Goalies Base Score

Goalie impact is calculated by normalizing time-on-ice to 60-minute Game Equivalencies. Actual Save Percentage is evaluated relative to a historical replacement-level baseline to calculate deviation points from league average efficiency.

A dynamic shot-volume multiplier is then applied to assess true workload relative to typical historical shot averages. To adjust for full 60-minute workloads, goalie baselines are strictly normalized against skater values, preventing high-volume variance from over-inflating seasonal peaks.

Statistical Accuracy & Win Projection

Multi-season regression analysis confirms this custom model successfully explains over 90% of the variance in actual team standings points purely from base box-score metrics.

How to Read the PACE Scale (Calibrated to ECAC History)

+3.50+ (First-Team All-American / Hobey Baker Finalist): The absolute elite tier of college hockey. These players dominate games nationally, average well over a point per game (or post top-five goalie metrics), and frequently lead their teams to national prominence.
+2.70 to +3.49 (ECAC First-Team / All-American Contender): All-Conference locks and primary game-changers. They serve as top-line anchors and top-pair defensemen who reliably push win shares into elite territory each season.
+1.75 to +2.69 (ECAC Third-Team / Solid Top-Line Contributor): Upper-tier starters and key catalysts on winning teams. While they may just miss First-Team honors, they consistently earn All-Conference recognition and drive top-six forward or top-four defensive output.
+0.80 to +1.74 (Average ECAC Performer / Core Roster Mainstay): The exact baseline definition of an every-night college player (apprximately .9-1 PACE). These players eat crucial middle-six minutes, power secondary scoring, and safely maintain positive team impact.
0.00 to +0.79 (Bench Guy / Replacement Level / Depth Rotation): Replacement-level output and fringe lineup contributors. This range typically includes energy players in limited roles, third-pair defensive specialists, underclassmen finding their rhythm, or scratches fighting for ice time.

Union Hockey Blog

Carter Rose : D

Career Skater Statistics

Player Movement History

Career Progression & Performance Tracking

Detailed Game Log

Historical Counterpart Matrix

Streich, Sean

Buote, Andrew

Campolieto, Joseph

Henry, Noah

Todd, Alex

Skater Metrics

Goalie Metrics

Player Action & Contribution Estimate (PACE) Definitions

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