Tag: womens-college-hockey

Introducing Two New ChampsRank Models for DI Women’s Hockey

Post author By Ray Tenenbaum
Post date December 2, 2025

To complement the existing subjective polls and the NCAA’s NPI system, we’ve developed two fully objective ranking models built on modern analytics:

ChampsRankSOS – Strength-of-Schedule Model
ChampsRankELO – ELO-Based Rating System

Here are the first two iterations of the models as of games completed on November 30th, 2025:

ChampsRankSOS – Strength-of-Schedule Model

ChampsRankELO – ELO-Based Rating System

Both models are designed to be transparent, data-driven, and updated within a few hours of each game, making them some of the fastest-refreshing public rankings available.

Our intent is to provide a clear, unbiased picture of team strength that reflects actual on-ice performance while avoiding the opacity and inertia that can affect human-voted polls.

ChampsRankSOS — Strength-of-Schedule Model

This system is structurally similar to MyHockeyRankings, but with important enhancements that make it better suited for college hockey.

Key Features

Strength-of-Schedule + margin of victory as core components
±7 goal cap on margin of victory (Note: There was consideration for increasing/ignoring a cap, but after the recent 17-2 Wisconsin win over Stonehill the current cap would not let these kind of anomalies bias the data)
Full iterative recalculation of all ratings until stable
45-day decay model — recent games are weighted more heavily
- Games older than 45 days typically represent 10+ games ago, meaning they don’t accurately reflect a team’s current form.
- The decay ensures the rankings reward teams improving now, not teams who were hot months ago.
Updated within hours of each game

Core Formula

Rating = GD + SOS

GD: Average goal differential per game (capped at ±7)
SOS: Average opponent rating (recalculated iteratively)

How It Works

Compute each team’s average goal differential
Initialize ratings
Iteratively recalculate: Rating = GD + SOS
Anchor the top team at 20.0
Recompute until convergence
Apply time decay to down-weight older games

ChampsRankELO — ELO-Based Model

Our second system is a modernized hockey-specific ELO model. The ELO model is a rating system that evaluates team or player strength by updating ratings after every game based on the expected outcome versus the actual result. It rewards upsets, penalizes underperformance, and naturally adjusts as more games are played. Originally developed for chess, ELO has since become widely used in sports such as tennis, soccer, basketball, and esports due to its ability to track performance dynamically and objectively.

Key Features

Home-ice advantage bonus: +11 ELO points (based on historical win rates)
45-day half-life time decay on older games
K-factor multipliers for early-season games, conference games, etc.
Margin-of-victory multiplier for blowout wins
Adjusts outcomes differently for regulation, OT, and shootout
Updated within hours of each game

Core Formula

R_new = R_old + K × MOV_multiplier × (S − E)

K: Sensitivity constant (base 32, with multipliers)
MOV: Margin of victory multiplier
S: Actual game outcome
E: Expected outcome (based on rating difference + home-ice advantage)

How It Works

All teams begin at 1500 ELO
Process games chronologically (one pass)
For each game:
- Compute expected outcome
- Apply home-ice advantage
- Update ratings using K-factor + MOV + decay
No iteration required — ratings naturally evolve over time

Main Differences at a Glance

Feature	ChampsRankSOS	ChampsRankELO
Basis	Goal differential	Win/loss outcomes
Processing	Iterative	Sequential (one pass)
Starting Point	AGD-based	All teams start at 1500
Top Team	Fixed at 20.0	Emerges naturally
Home Advantage	Not modeled	+11 ELO points
Time Decay	Yes — 45-day decay	Yes — 45-day half-life

Tags college-hockey-recruiting, rankings, tag, womens-college-hockey

Women's College Hockey Women's Hockey

ChampsRankELO – ELO-Based Rating System

Post author By Ray Tenenbaum
Post date December 2, 2025

This is the first iteration of the ChampsRankELO ranking report. An explanation of the methodology can be found here.

Note: As we make tweaks and automate this ranking system, updates will be made throughout each game day. Hopefully, this will happen in the next week or two.

Click here to view our other ranking: ChampsRankSOS

ChampsRankELO: DI Women’s College Hockey

as of November 30, 2025

Rank	Team	ELO Rating	Games Played
1	Ohio State	1712	16
2	Wisconsin	1663	18
3	UConn	1647	16
4	Penn State	1644	18
5	Minnesota	1599	16
6	Northeastern	1598	16
7	Minnesota Duluth	1597	16
8	Princeton	1588	13
9	Clarkson	1574	17
10	Minnesota State	1570	18
11	Cornell	1566	14
12	Quinnipiac	1564	18
13	Mercyhurst	1547	20
14	Boston College	1531	18
15	Vermont	1530	18
16	Yale	1530	14
17	Colgate	1523	18
18	Holy Cross	1521	18
19	Saint Anselm	1514	17
20	Union	1513	18
21	St. Cloud State	1505	18
22	St. Lawrence	1504	19
23	Franklin Pierce	1499	17
24	Harvard	1495	12
25	New Hampshire	1489	18
26	St. Thomas	1483	18
27	RIT	1481	20
28	Brown	1479	14
29	Syracuse	1466	20
30	Maine	1466	18
31	Dartmouth	1442	12
32	Providence	1439	17
33	Bemidji State	1437	16
34	Stonehill	1435	17
35	Boston University	1430	15
36	Merrimack	1429	16
37	Assumption	1426	18
38	Post	1420	17
39	Lindenwood	1408	20
40	Robert Morris	1404	20
41	LIU	1391	14
42	RPI	1384	19
43	Sacred Heart	1369	15
44	Delaware	1366	18
45	Saint Michaels	1326	13

St. Anselm vs. St Cloud State?

Why St. Anselm is ranked #19 (1514 ELO)

Win record: 11-6-0 (64.7%) vs St. Cloud State’s 6-11-1 (33.3%)

Nearly twice as many wins, which ELO rewards directly

2. Goal differential: +12 (+0.71/game) vs St. Cloud State’s -6 (-0.33/game)

Positive differential plus blowout wins (e.g., 8-2 vs LIU) boost ELO via the MOV multiplier

3. Weak schedule: Average opponent rating 1441.54

108 ELO points weaker than St. Cloud State’s opponents
Easier wins, but sequential ELO compounds early wins

Why St. Cloud State is ranked #21 (1505 ELO)

Losing record: 6-11-1 (33.3%)

Fewer wins despite playing stronger competition

2. Negative goal differential: -6 (-0.33/game)

Compounded by losses to strong teams

3. Strong schedule: Average opponent rating 1549.28

108 ELO points stronger than St. Anselm’s opponents
Early losses to strong teams (UConn, Minnesota) deflated their rating early

The core problem: Sequential compounding

ELO processes games chronologically, so early results set the trajectory:

St. Anselm: Early wins against weak teams (starting at 1500) boosted their rating. Even after those teams’ ratings dropped, St. Anselm’s rating stayed higher, making later wins worth more.
St. Cloud State: Early losses to strong teams deflated their rating. Even after those teams’ ratings rose, St. Cloud State’s rating stayed lower, making later wins worth less.

The SOS adjustment (post-processing, multiplier 1.0) helps but can’t fully undo the 108-point schedule gap and the compounding effects. This is why ChampsRankSOS ranks St. Cloud State #9 vs St. Anselm #36 — the iterative approach accounts for schedule strength holistically.

ChampsRankELO vs. ChampsRankSOS:

Consensus at the top: Both systems rank Ohio State #1 and Wisconsin #2, but ELO shows a larger gap (49.23 points vs 0.22 in ChampsRank1).

2. Major differences in middle rankings:

UConn: #3 in ELO vs #7 in ChampsRankSOS (ELO favors recent momentum)
St. Cloud State: #9 in ChampsRankSOS vs #21 in ELO (ChampsRankSOS better accounts for schedule strength)
Saint Anselm: #19 in ELO vs #36 in ChampsRank1 (17-rank difference – ELO influenced by early wins vs weak teams)

3 . Methodological differences:

ELO: Sequential processing captures momentum; recent games have immediate impact
ChampsRankSOS: Iterative approach provides a more holistic season evaluation
Both use 45-day time decay, but apply it differently

Got feedback on the ChampsRankELO model? Submit feedback here

Tags rankinigs, tag, womens-college-hockey

2025 2026 Rankings Women's College Hockey Women's Hockey

ChampsRankSOS – Strength-of-Schedule

Post author By Ray Tenenbaum
Post date December 2, 2025

This is the first iteration of the ChampsRankSOS ranking report. An explanation of the methodology can be found here.

We initially planned to publish only the time-decay version of our Strength-of-Schedule model (using a 45-day decay rate). However, the differences between the decay and no-decay versions were significant enough that it made sense to release both. This allows a clear comparison between a full-season evaluation and a ranking system that emphasizes recent performance — something both subjective polls and postseason selection committees tend to value. This weekend’s upcoming games between Wisconsin and Ohio State, might tell us which methodology makes more sense.

Click here to view our other ranking: ChampsRankELO

ChampsRankSOS with Decay Rate: DI Women’s College Hockey

as of November 30, 2025

GD = Goal Differential vs. Opponent

SOS = Strength of Schedule Rating of Opponent

Rank	Team	Rating	GD	SOS	Games Played
1	Ohio State	20.00	3.46	16.54	16
2	Wisconsin	19.78	3.96	15.82	18
3	Minnesota	18.71	1.82	16.89	16
4	Penn State	18.15	3.56	14.58	18
5	Minnesota Duluth	17.76	0.33	17.44	16
6	Minnesota State	16.77	0.24	16.53	18
7	UConn	16.73	1.21	15.52	16
8	Northeastern	16.66	1.58	15.08	16
9	St. Cloud State	16.48	-0.53	17.01	18
10	Quinnipiac	16.41	1.50	14.91	18
11	Cornell	16.35	1.74	14.61	14
12	Princeton	16.21	0.94	15.27	13
13	Clarkson	16.04	0.60	15.44	17
14	St. Thomas	15.94	-0.64	16.58	18
15	Colgate	15.74	0.04	15.71	18
16	Yale	15.67	0.74	14.93	14
17	Mercyhurst	15.52	0.54	14.99	20
18	Boston College	15.22	0.21	15.01	18
19	Harvard	15.04	0.68	14.37	12
20	RIT	15.04	0.10	14.93	20
21	St. Lawrence	14.83	-0.45	15.27	19
22	New Hampshire	14.75	0.52	14.23	18
23	Holy Cross	14.73	1.14	13.59	18
24	Vermont	14.72	-1.02	15.74	18
25	Union	14.64	0.41	14.23	18
26	Brown	14.46	-0.01	14.47	14
27	Maine	14.39	-1.07	15.46	18
28	Bemidji State	14.36	-2.24	16.60	16
29	Boston University	14.34	-1.02	15.36	15
30	Providence	14.08	-1.21	15.30	17
31	Syracuse	13.85	-1.06	14.91	20
32	Lindenwood	13.77	-0.75	14.53	20
33	Robert Morris	13.72	-0.71	14.44	20
34	Dartmouth	13.33	-2.27	15.61	12
35	Merrimack	13.08	-1.71	14.80	16
36	Saint Anselm	13.01	0.99	12.02	17
37	RPI	12.84	-2.01	14.85	19
38	Franklin Pierce	12.38	0.92	11.46	17
39	Assumption	11.74	-0.34	12.09	18
40	Stonehill	11.67	-1.25	12.92	17
41	Sacred Heart	11.65	-0.61	12.26	15
42	Delaware	11.38	-3.07	14.46	18
43	Post	11.12	-1.29	12.41	17
44	LIU	10.66	-0.98	11.64	14
45	Saint Michaels	8.24	-3.74	11.97	13

ChampsRankSOS without Decay Rate (Full Season Rating): DI Women’s College Hockey

as of November 30, 2025

Rank	Team	Rating	GD	SOS	Games Played
1	Wisconsin	20.00	4.06	15.94	18
2	Ohio State	19.81	3.25	16.56	16
3	Minnesota	19.14	2.25	16.89	16
4	Penn State	18.10	3.72	14.37	18
5	Minnesota Duluth	17.80	0.63	17.18	16
6	St. Cloud State	16.73	-0.33	17.06	18
7	Northeastern	16.69	1.69	15.00	16
8	Cornell	16.66	2.00	14.66	14
9	Quinnipiac	16.65	1.83	14.82	18
10	UConn	16.62	1.00	15.62	16
11	Minnesota State	16.49	0.11	16.38	18
12	Princeton	16.05	0.77	15.29	13
13	St. Thomas	15.97	-0.06	16.02	18
14	Clarkson	15.93	0.76	15.17	17
15	Colgate	15.79	0.06	15.74	18
16	Yale	15.71	0.79	14.92	14
17	Mercyhurst	15.53	0.35	15.18	20
18	Boston College	15.17	-0.11	15.28	18
19	RIT	15.02	0.35	14.67	20
20	Harvard	14.98	0.58	14.40	12
21	St. Lawrence	14.89	-0.47	15.37	19
22	Vermont	14.79	-0.94	15.74	18
23	New Hampshire	14.78	0.61	14.16	18
24	Bemidji State	14.68	-2.25	16.93	16
25	Brown	14.61	0.07	14.53	14
26	Holy Cross	14.57	1.11	13.46	18
27	Union	14.49	0.17	14.32	18
28	Maine	14.43	-1.22	15.65	18
29	Boston University	14.40	-1.27	15.66	15
30	Providence	13.99	-1.47	15.46	17
31	Syracuse	13.78	-1.15	14.93	20
32	Lindenwood	13.69	-1.20	14.89	20
33	Robert Morris	13.62	-0.75	14.37	20
34	Dartmouth	13.47	-2.00	15.47	12
35	Merrimack	13.18	-1.63	14.81	16
36	RPI	12.85	-2.00	14.85	19
37	Saint Anselm	12.81	0.71	12.10	17
38	Franklin Pierce	12.32	0.47	11.85	17
39	Sacred Heart	11.77	-0.33	12.10	15
40	Assumption	11.72	-0.44	12.16	18
41	Stonehill	11.66	-1.06	12.72	17
42	Delaware	11.35	-3.00	14.36	18
43	Post	11.01	-1.76	12.77	17
44	LIU	10.82	-0.64	11.46	14
45	Saint Michaels	8.60	-3.38	11.99	13

#1 Ranking Flip

When recent games are weighted more heavily, Ohio State takes over the top spot. Over the full season, Wisconsin remains #1.

• Without decay: Wisconsin #1 (20.00), Ohio State #2 (19.81)
• With decay: Ohio State #1 (20.00), Wisconsin #2 (19.78)

Why the flip occurs

• Wisconsin: Goal differential drops from 4.06 → 3.96 due to early-season blowouts being de-weighted (e.g., 17–2 vs. Stonehill, 8–0 vs. Minnesota State).
• Ohio State: Goal differential rises from 3.25 → 3.46, reflecting stronger recent games.
• Game volume: Wisconsin has 18 games — more older results get discounted. Ohio State has 16 — more of their games retain full weight.
• Decay math: Games older than ~60 days count at roughly 35% weight, boosting teams with stronger recent form.

Other Notable Shifts

• Minnesota State: +5 spots (11 → 6) — largest improvement
• Bemidji State: –4 spots (24 → 28) — largest decline
• 24 teams experienced movement between the two models

Got feedback on the ChampsRankSOS model? Submit feedback here

Tags rankings, tag, womens-college-hockey

College Hockey Recruiting Women's College Hockey Women's Hockey

Women’s DI Hockey Polls & Rankings: A Clearer Look

Post author By Ray Tenenbaum
Post date December 1, 2025

Over the past few weeks, I’ve grown increasingly frustrated with the two major weekly polls in women’s Division I college hockey. Because I track nearly all 45 DI teams closely, I have a pretty strong feel for each team’s true performance level. Yet after weekends filled with upsets or narrow wins over weaker opponents, I’m continually surprised by how certain teams — and some conferences — appear to be ranked higher than expected. While the NPI (see below for detailed explanation) is objective and used for at-large playoff selections, it also isn’t perfect.

As a result, I decided to apply my own analytics to create a new, objective Champs App ranking for DI women’s hockey. But before sharing that system, here’s a breakdown of the current major polls and ranking models.

🔢 Three Types of Ratings: Subjective vs. Objective

Women’s DI hockey currently uses three major rating systems, which fall into two categories:

Subjective (human-voted):
- USCHO.com Poll
- USA Hockey / AHCA Poll
Objective (mathematical):
- NCAA Power Index (NPI) — now the official NCAA selection metric
- PairWise Ranking (PWR) — the legacy system, replaced by NPI

Below is a clear summary of how each poll or model works.

1. USCHO.com Poll (Subjective)

The USCHO.com poll is a traditional, human-voted ranking composed of sportswriters, broadcasters, and coaches. Neither the list of voters nor their individual ballots are published.

PROS

Contextual Judgment

Captures elements no algorithm can quantify: the “eye test,” injuries, momentum, travel fatigue, and lineup changes.

Media Relevance

Drives debate, fan engagement, and weekly storylines.

Focus on Current Form

Voters can quickly adjust for hot streaks or slumps, sometimes more rapidly than data-based systems.

CONS

Lack of Transparency

No published criteria. Voters have full discretion, making results unpredictable and unauditable.

Inconsistency and Bias

Subject to inertia (teams maintaining rank despite bad losses) and regional bias. It’s not difficult to guess which conferences receive the benefit of the doubt.

Weak Tournament Predictor

Often diverges significantly from the objective NPI used to select NCAA tournament teams.

2. USA Hockey / AHCA Poll (Subjective)

This weekly poll is conducted by USA Hockey in partnership with the American Hockey Coaches Association (AHCA).

Methodology

Human-voted, similar to USCHO.
Voters include coaches and journalists from all NCAA women’s hockey conferences.
Rankings are based on total points from submitted ballots.

While it provides valuable insight from actual DI coaches, it shares the same challenges as USCHO:

Only 19 voters
No transparency into who they are or how they vote
Susceptible to the same regional biases and subjective inconsistencies

The coexistence of two separate human polls does help smooth out extreme opinions — and when they differ noticeably, it signals a lack of consensus that adds useful context that a single mathematical model cannot provide.

3. NCAA Power Index (NPI) and PairWise (PWR) (Objective)

The NCAA Power Index has fully replaced PairWise as the official NCAA tournament selection tool. NPI is a streamlined, strength-of-schedule-driven model that uses an opponent-based rating system and assigns bonuses for beating highly rated teams.

PROS

Pure Objectivity

Removes human bias. Rankings come directly from win percentage and opponent strength, based on a fully transparent formula.

Improved Strength-of-Schedule (SOS)

Uses opponents’ NPI ratings directly, replacing the more convoluted RPI components of the old PairWise system.

Rewards Quality Wins

Includes a Quality Win Bonus (QWB) for beating strong opponents — and importantly does not penalize teams for beating weaker opponents (a major flaw of old RPI).

CONS

No Contextual Adjustments

Ignores coaching changes, injuries, goalie slumps, or roster disruptions that human voters naturally account for.

Occasional Mathematical Oddities

Any complex model can produce counterintuitive outcomes in specific cases.

Self-Referencing Structure

Because a team’s NPI depends on opponents’ NPI — which depends on their opponents — the calculation must be iterated to find a stable solution.

NPI Statistical Engine (Simplified)

25%: Win Percentage
75%: Opponents’ NPI (Strength of Schedule)
Quality Win Bonus (QWB): Extra credit for beating high-NPI teams
Bad Win Treatment: Mechanisms to remove or neutralize extremely low-value wins
Strength-of-Schedule (SOS): Directly uses opponents’ final NPI rating for a cleaner, more intuitive strength measure

🔜 What’s Next

In the next post, I’ll introduce the Champs App proposal for two new objective ranking models:

A simplified, transparent Strength-of-Schedule Index
An ELO-based model similar to the systems used in chess and tennis

Both provide intuitive, statistically robust alternatives to today’s polls — without the subjectivity of human rankings.

Tags college-hockey-recruiting, tag, womens-college-hockey, womens-hockey

2025 College Hockey Recruiting Women's College Hockey Women's Hockey

🏒 How ChampsEyeQ Player Reports Work

Post author By Ray Tenenbaum
Post date October 8, 2025

ChampsEyeQ turns your game video into a professional, data-driven evaluation that helps you understand where you stand and how to improve.

🎥 Step 1: Submit Your Video

Players upload at least 10 minutes of edited game footage showing complete shifts with real game flow — not just highlights.

👀 Step 2: Expert Scout Evaluation

Our professional scouts — who have evaluated thousands of youth players — analyze your performance across 15+ key attributes, including:

Skating
Hockey IQ & Decision Making
Offensive & Defensive Skills
Compete Level & Intangibles

📊 Step 3: Ratings, Tiers & Feedback

Each player receives a quantitative and qualitative report with:

A numerical rating (1–10) for every skill
An overall average score
A Tier ranking showing how they compare to peers nationwide
Written feedback highlighting key strengths and priority areas for improvement

DOWNLOAD A SAMPLE REPORT Download

🧮 How Ratings Translate into Tiers

Average Rating	Tier	Meaning
8.5+	🏅 Top 5% – Elite Player	Exceptional performance; top national tier
7.8–8.4	🎓 Top 20% – D1 Potential	Typical range of future NCAA Division I players
6.5–7.7	💪 Top 33%	Strong skill base; competitive pathway to D1
5.5–6.4	⚔️ Top 50%	Solid player development foundation
Below 5.5	🔄 Bottom 50%	Early-stage development; focus on fundamentals

Formula: =IFS(Rating≥8.5,“Top 5%–Elite Player”, Rating≥7.8,“Top 20%–D1 Potential”, Rating≥6.5,“Top 33%”, Rating≥5.5,“Top 50%”, TRUE,“Bottom 50%”)

🧭 Step 4: Actionable Insights

ChampsEyeQ combines objective data and expert insight to give players a clear development roadmap — showing not just what their rating is, but why and how to improve.

As more athletes are evaluated, ChampsEyeQ continually updates its benchmarks, giving families an evolving, data-backed view of what it takes to reach the NCAA Division I level.

🚀 Ready to See Where You Stand?

Submit your game footage today and receive your personalized ChampsEyeQ Player Evaluation Report.
👉 Start your submission at www.ChampsEyeQ.com

Tags college-hockey-recruiting, hockey-development, tag, womens-college-hockey

Coaching Women's College Hockey

Boston College Women’s Hockey: A Shift from Dominance to Rebuilding

Post author By Ray Tenenbaum
Post date October 2, 2025

The Boston College women’s ice hockey program, a consistent top-10 powerhouse from 2010 to 2019, has experienced a noticeable downturn in recent years, seeing them fall out of the national top rankings. This shift can be attributed to a confluence of factors, most notably a significant loss of top-tier talent through the NCAA transfer portal, coupled with the natural cycle of player graduation and the increasing parity in women’s college hockey.

The gap between the Eagles and the nation’s elite was starkly highlighted at the start of the 2025-26 season. In a two-game series on September 25th and 26th, 2025, Boston College was outscored by a combined 18-1 in back-to-back losses to the University of Minnesota, falling 7-1 and 11-0. These results provided a clear illustration of the team’s current challenges against top-tier programs.

While the program enjoyed a decade of dominance under head coach Katie Crowley, marked by numerous NCAA tournament appearances and Hockey East championships, the tide began to turn following the 2019-20 season. An examination of their season records reveals a stark contrast. After a strong 2018-19 season with a 26-12-1 record, and a respectable 17-16-3 showing in 2019-20, the team’s performance started to dip. The COVID-19-shortened 2020-21 season saw a 14-6-0 record, but the subsequent seasons marked a significant decline with losing records of 19-15-1 in 2021-22, 11-20-3 in 2022-23, and 14-18-3 in 2023-24.

The most significant factor contributing to this decline has been the departure of several high-impact players. This exodus of talent has created significant gaps in their lineup and leadership. Key losses include:

Daryl Watts: The 2018 Patty Kazmaier Award winner as the nation’s top female college ice hockey player transferred to Wisconsin after the 2018-19 season, a move that sent shockwaves through the college hockey world.
Cayla Barnes and Hannah Bilka: Two of the team’s captains and key veteran leaders, defenseman Cayla Barnes and forward Hannah Bilka, departed for rival powerhouse Ohio State following the 2022-23 season. It is important to note that both players had graduated from Boston College and were using their fifth year of eligibility, granted due to the COVID-19 pandemic, to play for the Buckeyes. While they completed their academic and athletic careers at BC, their departure meant the Eagles lost two of their most experienced and productive players, leaving a significant void in on-ice production and veteran leadership for the following season.
Julia Pellerin: The team’s leading goal-scorer in the 2023-24 season, Pellerin, transferred to conference rival UConn, further depleting the Eagles’ offensive firepower.
Molly Jordan: Adding to the recent challenges, standout defender Molly Jordan transferred to Minnesota in the 2024 off-season, representing another significant departure from the team’s blue line.

Compounding the challenges of player turnover was a major change behind the bench. In April 2023, longtime Associate Head Coach Courtney Kennedy left the program after 16 seasons to become a skills coach in the Professional Women’s Hockey League (PWHL) for the Boston Fleet and Head Coach of the 2026 USA Hockey U18 Women’s Team. Kennedy had been an integral part of the program’s success, working alongside Katie Crowley for their entire tenure. Her departure broke up one of the most stable and successful coaching partnerships in the country

These high-profile departures, coupled with the graduation of other key players, have made it challenging for Boston College to maintain its previous level of dominance.

While head coach Katie Crowley has remained a constant and respected figure behind the bench, the significant roster turnover has necessitated a period of rebuilding. The program continues to recruit talented players, but the immediate impact of losing established stars is difficult to overcome in the highly competitive landscape of NCAA Division I women’s ice hockey. The rise of other programs and the increasing talent pool across the country mean that sustained dominance is more challenging than ever.

The Boston College women’s ice hockey program’s slide from the top 10 is not due to a single catastrophic event, but rather a combination of the growing influence of the transfer portal, the loss of veteran talent, and the ever-increasing competitiveness of the sport. The program is currently in a rebuilding phase, focused on developing its younger players and navigating the new era of player movement in college athletics.

Tags college-hockey-recruiting, tag, usa-girls-hockey, womens-college-hockey

2025 College Hockey Recruiting Women's College Hockey Women's Hockey

Your NCAA Women’s Hockey Recruitment Video: What Coaches REALLY Want to See

Post author By Ray Tenenbaum
Post date July 21, 2025

Aspiring to play NCAA women’s hockey? Your recruitment video is a key piece of the puzzle, but what exactly are college coaches looking for? We recently surveyed both D1 and DIII women’s hockey coaches for their specific video-submission preferences to give you the inside scoop. Forget the guesswork – here’s what you need to know to make your video stand out.

Keep It Concise: Less Than 6 Minutes is Key

First and foremost, keep your video submission under 6 minutes. Coaches are busy, and a succinct, impactful video is far more likely to be watched in its entirety. This isn’t the time for a lengthy highlight reel; focus on quality over quantity.

Video: Helpful, But Not the Only Factor

While your video is “somewhat important,” coaches emphasized that it’s helpful but not critical for their initial evaluation. Think of it as a strong supporting document that complements your athletic profile and academic achievements. It’s a tool to get you noticed, not the sole determinant of your recruitment.

What Kind of Footage Do They Prefer?

This is where many players go wrong. Coaches overwhelmingly prefer full game shift-by-shift footage with selected shifts from multiple games (e.g., 10-15 shifts). They want to see you in real-game scenarios, demonstrating your hockey sense and decision-making under pressure.

What to avoid? Tightly edited highlight reels with just goals or flashy plays. Coaches want to see the full sequence of play, not just the spectacular finish. This provides a much more accurate representation of your abilities.

How to Submit Your Video

The preferred methods for submission are straightforward: YouTube, Hudl, or Instat. Providing a profile/channel link or a direct email attachment (e.g., an .mp4 file) are both acceptable. Note: Coaches made it clear that they will almost always watch your videos via another service if you’re already in that system.

When to Submit

Consistency is important. Aim to submit new video during recruiting season every 1-3 months. This keeps coaches updated on your progress and reminds them of your interest.

Special Considerations for Goalies

Goalies, pay close attention! Coaches want to see a mix of both full games and a highlight reel. Critically, they prefer gameplay highlights over practice sessions. When it comes to the content, they’re looking for a breadth of skills, including:

Rebound control
Puck handling
Odd Man Rushes
Net Front Scrambles
High Danger Shots

Perhaps the most surprising insight for goalies: coaches find it helpful to show clips where you let in a goal but demonstrate strong fundamentals. This shows resilience, good technique even in challenging situations, and provides a more realistic assessment of your abilities than only showing perfect saves.

In Summary:

Length: Under 4 minutes.
Importance: Helpful, but not critical for initial evaluation.
Content: Full game shift-by-shift with selected shifts from multiple games (20-30 shifts). Full sequence clips, not just highlights.
Method: YouTube/Hudl/Instat link or direct email attachment. But know that coaches will review their own subscriptions service like Hudl/Instat to watch your footage.
Frequency: Every 1-3 months during recruiting season.
Goalies: Mix of full games & highlight reel, game play preferred, include clips demonstrating strong fundamentals even if a goal is scored.

By following these guidelines, you can create a recruitment video that truly resonates with Division 1 women’s hockey coaches and helps you take the next step in your athletic journey. Good luck!

The NCAA Settlement: Practical Impacts on Division I Ice Hockey Rosters and Scholarships

Post author By Ray Tenenbaum
Post date July 7, 2025

The recently approved NCAA House settlement is poised to fundamentally reshape collegiate athletics, and its impact on Division I men’s and women’s ice hockey programs will be significant. While many details are still emerging, the core changes revolve around athlete compensation, scholarship flexibility, and roster limits.

Understanding Scholarship Flexibility

For schools that opted into the NCAA House settlement, a critical change is the newfound flexibility in offering athletic scholarships. Previously, strict scholarship caps limited teams. Now, if a Division I hockey team cannot afford to offer the maximum of 26 full athletic scholarships, they have the discretion to offer fewer.

This flexibility stems from several key aspects of the settlement:

Roster Limit as a Maximum: The 26-player roster limit for Division I ice hockey is an absolute maximum. It dictates the highest number of players a team can have on its active roster, not a minimum or a mandated number of scholarships. Teams are not required to fill all 26 spots, nor are they required to offer full scholarships to all players on their roster.
Equivalency Scholarships: Under the new system, all athletic scholarships are “equivaency scholarships.” This grants schools the ability to:
- Offer Partial Scholarships: For instance, instead of two full scholarships, a school might offer four half-scholarships.
- Mix Full and Partial Scholarships: Teams can create a blended approach, with some players receiving full scholarships and others partial aid.
- Offer Fewer Overall Scholarships: A school might decide that its budget allows for only 15 full scholarships, even if it carries 22 players on the roster. The remaining players would either be true walk-ons (receiving no athletic aid) or receive very small partial scholarships if financial resources permit.
Budgetary Constraints: The settlement introduces an annual cap on the total amount of revenue a school can share directly with athletes, starting at approximately $20.5 million for the first year. This cap includes scholarship costs that exceed previous limits. For many institutions, particularly those outside the major revenue-generating conferences, fully funding 26 scholarships for a hockey team in addition to other sports, while remaining within this overall cap, will present a significant financial challenge. Strategic decisions on fund allocation across all sports will be essential.
Strategic Roster Management: Coaches and athletic departments will need to balance their desired roster size for competitive reasons with their financial realities. Some may opt for a smaller, more highly funded roster, while others might spread aid among more players if their budget allows for a greater number of partial scholarships.

In summary, while the settlement removes the old scholarship caps and permits up to 26 scholarships for hockey, it does not mandate that a school must provide 26. Each institution will make its own decisions based on its financial capacity and athletic priorities.

The “Grandfather Rule” Exception

An important caveat to the strict roster limits is the “grandfathering” provision. Current or incoming 2025-26 student-athletes who were already on a roster or had a promised spot and would otherwise be cut due to the new limits are designated as “Designated Student-Athletes.” These individuals do not count against the 26-player limit for their remaining eligibility at their original institution or any transfer institution. However, once these players complete their eligibility, the strict 26-player cap will apply, reinforcing that the new system streamlines roster management: the number of players a team can carry is now the number they can offer aid (including scholarships and direct payments) to, up to that specific sport’s roster cap.

Schools Not Opting In

While the vast majority of Division I schools opted into the settlement (approximately 319 out of 389), some notable exceptions relevant to hockey exist:

The Ivy League: All eight Ivy League institutions, including their six hockey schools, have opted out. This decision aligns with their longstanding model of not awarding athletic scholarships or providing direct athletic compensation.
Military Academies: Institutions like Air Force and Army have opted out due to military rules that prevent their cadets from receiving Name, Image, and Likeness (NIL) compensation.
Other Hockey Programs: Certain other Division I hockey programs, such as Nebraska-Omaha, also chose not to opt in, often citing financial considerations or a desire to observe how the new system unfolds before committing.

Impact on Women’s Ice Hockey

The new rules could be beneficial for women’s hockey. Traditionally, women’s hockey teams have averaged around 25 roster spots. The new 26-player cap is very close to this average, suggesting less drastic changes in immediate roster size. This consistency may alleviate concerns about increasing roster sizes potentially forcing players into unhealthy competition for ice time or risking being healthy scratched.

However, schools like Sacred Heart, which have historically maintained larger women’s hockey rosters (sometimes exceeding 30 players), will face a significant adjustment. While the grandfather rule will mitigate immediate impacts for current players, these programs will see a necessary decrease in their roster size for future recruiting classes as the grandfathered players cycle out.

Impact on Men’s Ice Hockey

The new rules are expected to have a more pronounced impact on decreasing roster sizes in men’s hockey. On average, men’s teams have historically carried around 29 players. Given that men’s hockey tends to have more injuries than women’s hockey, larger rosters were often maintained to provide depth.

Now, these rosters will shrink to the 26-player maximum. While the grandfather rule will offer a short-term buffer, this ultimately means the overall number of players participating in Division I men’s hockey will decrease, potentially from approximately 1,800 players to 1,600 players across the country.

This reduction in available spots is further compounded by the recent change allowing Canadian junior players, who were previously ineligible due to stipends, to now play college hockey. This new pool of eligible talent will intensify competition for the fewer available roster spots in Division I men’s programs.

Tags mens-college-hockey, ncaa-settlement, tag, womens-college-hockey

2025 Women's Hockey

NCAA Dominance Shines at the 2025 PWHL Draft: A Look at the Top Programs

Post author By Ray Tenenbaum
Post date June 30, 2025

Last week, the hockey world turned its attention to the highly anticipated 2025 Professional Women’s Hockey League (PWHL) Draft, held on June 24th. As the league continues to solidify its place as the premier destination for elite female talent, the draft provided a fascinating snapshot of where the next generation of stars are coming from. Unsurprisingly, NCAA Division I programs once again proved to be the powerhouse pipeline, alongside a strong showing from European leagues.

Leading the charge in player development was Ohio State University, which saw an impressive six of its athletes selected, showcasing the strength and depth of their program. Close behind, the University of Minnesota Duluth (UMD) celebrated five of its own making the leap to professional ranks, reinforcing their consistent high-level output.

Quinnipiac University had a phenomenal draft, with four players hearing their names called, a testament to their growing influence in women’s hockey. Following them with three draftees each were Clarkson University, the University of Minnesota, and St. Cloud State University, highlighting the continued excellence across multiple conferences.

The draft also recognized talent emerging from beyond North American collegiate play, with three players selected directly from European leagues, emphasizing the global reach of the PWHL.

Further contributing to the NCAA’s robust representation, a strong contingent of programs each had two players drafted: Boston University, Colgate, Cornell, Penn State, Providence, St. Lawrence, UConn, and Wisconsin. Rounding out the selections were Boston College, Mercyhurst, Northeastern, and Yale, each celebrating one draftee.

Please note: The numbers above reflect the last college or university the drafted player attended. Schools like Wisconsin, Penn State, New Hampshire and Brown had drafted players transfer out prior to this past season.

Tags tag, womens-college-hockey, womens-hockey

2025 Coaching Women's College Hockey Women's Hockey

Who Will Replace Brian Idalski as Head Coach of St. Cloud State Women’s Hockey?

Post author By Ray Tenenbaum
Post date June 24, 2025

With the surprise announcement that Brian Idalski will be leaving St. Cloud State to become the inaugural head coach of PWHL Vancouver, the Huskies face a critical decision. Idalski helped elevate the program’s competitiveness in the WCHA during his tenure, and his successor will be tasked with maintaining that upward trajectory. Here’s a breakdown of the leading candidates to take the reins—and how their credentials stack up in 2025.

After successfully including Courtney Kessel in our list of candidates for the Princeton head coaching role, let’s see how we do on this analysis:

🔝 Leading Contenders

Jinelle Zaugg‑Siergiej

Current Role: Associate Head Coach, St. Cloud State (2019–present)
Why She’s a Top Choice:
A silver medalist with Team USA (2010) and two-time NCAA champion at Wisconsin, Zaugg‑Siergiej has been a steady hand behind the bench for the past six seasons. She knows the program inside and out, has strong relationships with current players and recruits, and would provide continuity at a time of transition. She has never been a head coach, but she’s well-positioned to step up.

Mira Jalosuo

Current Role: Assistant Coach, PWHL Minnesota (2023–present)
Why She’s a Top Choice:
After spending the 2022–23 season as an assistant at St. Cloud, the Finnish Olympian joined Ken Klee’s staff in the PWHL and helped guide Minnesota to back-to-back Walter Cup championships. Known for her defensive acumen and elite playing background, Jalosuo brings both credibility and a championship mentality. Her return would inject high-level tactical knowledge and energy into the program.

Molly Engstrom

Current Role: Head Coach, University of Maine (since 2022)
Why She’s a Top Choice:
A former assistant at St. Cloud State (2018–2022) and two-time U.S. Olympian, Engstrom has transformed Maine into a defensively responsible team. She was one of three finalists for the St. Cloud State job in 2022 before Idalski was ultimately hired. Her success at Maine and familiarity with SCSU make her a very attractive candidate—if she’s interested in returning.

Erik Strand

Current Role: Assistant Coach, University of Vermont (since May 2025)
Why He’s a Top Choice:
Strand was also a finalist for the SCSU head coach role in 2022. Prior to joining Vermont, he spent 10 years as head coach at UW–Eau Claire, guiding the DIII program to consistent success, including multiple NCAA tournament appearances and conference championships. A veteran of player development and known for his high-character leadership, Strand is ready for the Division I spotlight.

🔁 Long-Shot Options

Jeff Giesen

Current Role: Associate Head Coach, Minnesota State
Why He’s Notable:
Giesen was St. Cloud State’s head coach from 2006 to 2014, leading the team through eight seasons. While he’s been at Minnesota State for nearly a decade, his familiarity with the Huskies’ program and the WCHA landscape gives him a theoretical path back—though it’s unclear whether he’s looking for a return to head coaching.

Britni Smith

Current Role: Head Coach, Syracuse (since 2022)
Why She’s Notable:
A former Clarkson assistant and Hockey Canada coach, Smith has turned around Syracuse’s program in the CHA. While she’s respected as a rising leader, her current commitment at Syracuse may keep her focused out east.

Nick Carpenito

Current Role: Associate Head Coach, Northeastern
Why He’s Notable:
A key architect of Northeastern’s success over the past decade, Carpenito is highly respected in NCAA circles. A jump to head coach in the WCHA would be a bold but potentially rewarding move—for both sides.

Greg May

Current Role: Associate Head Coach, Minnesota (joined July 2023)
Former Augsburg University DIII Head Coach (Sept 2021–July 2023), where he led the team to back-to-back NCAA Division III appearances and MIAC titles with a 41–15–2 record
Named an assistant coach for the 2026 U.S. Women’s U18 National Team
Why He’s Notable: Proven leadership at DIII and college program building. Now adding national-team experience. A fresh, well-rounded external hire.

Dan Koch

Current Role: Assistant Coach, University of Wisconsin
Why He’s Notable:
Koch has spent years in the powerhouse Wisconsin program, developing elite players. Like others on this list, he’d represent a fresh external hire with deep knowledge of what winning programs look like.

🏁 Final Thoughts: Familiarity or Fresh Blood?

St. Cloud State has no shortage of qualified candidates, and their decision may ultimately come down to priorities:

If the goal is continuity, promoting Zaugg‑Siergiej or recruiting Jalosuo back from the pros makes the most sense.
If the program seeks a proven leader, Engstrom or Strand—both past finalists—are strong, familiar names with NCAA and program-building experience.
For a bold shake-up, external hires like Carpenito, Smith, or Koch could introduce a new culture and broader recruiting reach.

Whoever takes over will inherit a program on the rise and a passionate fanbase eager for sustained WCHA and NCAA success.

Tags hockey-coach, ncaa-college-hockey-coach, tag, womens-college-hockey, womens-hockey

ChampsRankSOS — Strength-of-Schedule Model

Key Features

Core Formula

How It Works

ChampsRankELO — ELO-Based Model

Key Features

Core Formula

How It Works

Main Differences at a Glance

ChampsRankELO: DI Women’s College Hockey

as of November 30, 2025

St. Anselm vs. St Cloud State?

Why St. Anselm is ranked #19 (1514 ELO)

Why St. Cloud State is ranked #21 (1505 ELO)

The core problem: Sequential compounding

ChampsRankELO vs. ChampsRankSOS:

ChampsRankSOS with Decay Rate: DI Women’s College Hockey

as of November 30, 2025

ChampsRankSOS without Decay Rate (Full Season Rating): DI Women’s College Hockey

as of November 30, 2025

#1 Ranking Flip

Why the flip occurs

Other Notable Shifts

🔢 Three Types of Ratings: Subjective vs. Objective

1. USCHO.com Poll (Subjective)

PROS

CONS

2. USA Hockey / AHCA Poll (Subjective)

Methodology

3. NCAA Power Index (NPI) and PairWise (PWR) (Objective)

PROS

CONS

NPI Statistical Engine (Simplified)

🔜 What’s Next

🎥 Step 1: Submit Your Video

👀 Step 2: Expert Scout Evaluation

📊 Step 3: Ratings, Tiers & Feedback

🧮 How Ratings Translate into Tiers

🧭 Step 4: Actionable Insights

🚀 Ready to See Where You Stand?

Keep It Concise: Less Than 6 Minutes is Key

Video: Helpful, But Not the Only Factor

What Kind of Footage Do They Prefer?

How to Submit Your Video

When to Submit

Special Considerations for Goalies

In Summary:

READ MORE ON THIS TOPIC:

🚨Champs App Profile 2.0 is Here – With Videos, References & More!

🎥 Upload Videos Directly

Understanding Scholarship Flexibility

The “Grandfather Rule” Exception

Schools Not Opting In

Impact on Women’s Ice Hockey

Impact on Men’s Ice Hockey

Jinelle Zaugg‑Siergiej

Mira Jalosuo

Molly Engstrom

Erik Strand

Jeff Giesen

Britni Smith

Nick Carpenito

Greg May

Dan Koch

🏁 Final Thoughts: Familiarity or Fresh Blood?