Rising players board
Ascension: who's rising
Every NHL skater's last few games against his previous 20: more ice time, a PP1 spot, a promotion to the top six, minutes with his team's best players and better chances. Each player gets a 0–100 score with the reasons spelled out, so you can grab the riser before your league notices, and see who is losing his role.
2026-27 · games through Oct 1, 2026 · 428 skaters scored on the last 5 games · updated Oct 2, 2026.
Biggest risers
- On-ice xGF/60 3.76 (was 1.85)
- +2:31 PP TOI
- PP1 in 1 of last 2 (was 0 of 20)
- ixG/60 2.97 (was 1.13)
- +2:37 PP TOI
- PP1 in 2 of last 2 (was 6 of 20)
- +1:47 PP TOI
- 2 P in last 2 (0.55/GP before)
- 24% of team PP time (was 2%)
- 4 P in last 2 (0.20/GP before)
- +5:07 TOI a game
- 36% of 5v5 TOI with Boeser (was 0%)
- 3 P in last 2 (0.25/GP before)
- +6:09 TOI a game
- 29% of 5v5 TOI with Boeser (was 0%)
Biggest fallers: losing their role
- 0 P in last 2 (0.70/GP before)
- PP1 in 0 of last 2 (was 19 of 20)
- −1:29 PP TOI
- On-ice xGF/60 1.36 (was 2.28)
- −6:21 5v5 TOI
- Top-six in 0 of last 2 (was 11 of 20)
- On-ice xGF/60 1.19 (was 2.73)
- −3:22 TOI a game
- PP1 in 1 of last 2 (was 16 of 20)
- ixG/60 0.21 (was 1.04)
- −1:11 PP TOI
- 18% of team PP time (was 35%)
- On-ice xGF/60 0.51 (was 3.23)
- −1:13 PP TOI
- 39% of team PP time (was 51%)
The board
| # | Player | Score | Tier | Wk | Rostered | Why |
|---|---|---|---|---|---|---|
| 1 | Kasperi KapanenR · EDM | 80 | Surging | ▲ 47 | 8% |
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| 2 | Ryan SheaD · EDM | 76 | Surging | ▼ 3 | 15% |
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| 3 | Paul CotterC · VAN | 75 | Surging | ▲ 19 | 14% |
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| 4 | Jamie OleksiakD · VAN | 73 | Rising | ▲ 14 | 5% |
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| 5 | Jordan GreenwayL · CHI | 70 | Rising | ▲ 8 | 0% |
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| 6 | Kaapo KakkoR · SEA | 67 | Rising | ▲ 44 | 17% |
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| 7 | Hendrix LapierreC · PIT | 66 | Rising | ▲ 13 | 7% |
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| 8 | Mathieu JosephR · EDM | 66 | Rising | ▲ 34 | 0% |
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| 9 | Denton MateychukD · CBJ | 65 | Rising | ▲ 11 | 42% |
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| 10 | Alexandre CarrierD · MTL | 65 | Rising | ▲ 3 | 14% |
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| 11 | Kaedan KorczakD · PIT | 65 | Rising | ▲ 19 | 7% |
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| 12 | Max SassonC · VAN | 65 | Rising | ▲ 24 | 5% |
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| 13 | Trent FredericC · EDM | 64 | Rising | ▲ 14 | 4% |
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| 14 | Alex TurcotteC · LAK | 64 | Rising | ▲ 45 | 9% |
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| 15 | Jack QuinnR · BUF | 64 | Rising | ±0 | 45% |
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| 16 | Shane WrightC · SEA | 64 | Rising | ▲ 38 | 27% |
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| 17 | Samuel GirardD · PIT | 63 | Rising | ▲ 14 | 8% |
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| 18 | Kent JohnsonC · CBJ | 63 | Rising | ▲ 28 | 30% |
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| 19 | Noah OstlundC · BUF | 63 | Rising | new | 25% |
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| 20 | Anton LundellC · FLA | 62 | Rising | new | 45% |
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| 21 | Ryan WintertonC · SEA | 62 | Rising | ▲ 24 | 4% |
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| 22 | Ryker EvansD · SEA | 62 | Rising | ±0 | 14% |
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| 23 | Luke SchennD · VAN | 62 | Rising | ▲ 15 | 7% |
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| 24 | Cody CeciD · LAK | 61 | Rising | ▲ 7 | 0% |
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| 25 | Jake MiddletonD · CGY | 61 | Rising | ▲ 8 | 6% |
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| 26 | Mark KastelicC · BOS | 61 | Rising | ▼ 17 | 13% |
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| 27 | Emil AndraeD · CBJ | 61 | Rising | ▲ 5 | 9% |
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| 28 | Liam OhgrenL · VAN | 61 | Rising | ▲ 22 | 17% |
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| 29 | Max ShabanovR · MIN | 60 | Rising | ▲ 1 | 26% |
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| 30 | Yegor SharangovichC · CGY | 60 | Rising | ▲ 39 | 8% |
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| 31 | Oliver BjorkstrandR · NYR | 60 | Rising | ▲ 16 | 20% |
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| 32 | Connor CliftonD · BOS | 60 | Rising | ▲ 4 | 7% |
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| 33 | Ville KoivunenR · PIT | 59 | Steady | ▲ 18 | 17% |
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| 34 | Isaac HowardL · EDM | 59 | Steady | ▼ 10 | 31% |
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| 35 | Jared SpurgeonD · MIN | 59 | Steady | ▲ 2 | 9% |
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| 36 | Egor ChinakhovR · PIT | 59 | Steady | ▲ 33 | 48% |
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| 37 | Berkly CattonC · SEA | 59 | Steady | ▲ 31 | 30% |
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| 38 | Will BorgenD · BOS | 59 | Steady | ▲ 29 | 4% |
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| 39 | Hampus LindholmD · BOS | 59 | Steady | ▲ 8 | 16% |
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| 40 | Marcus PetterssonD · NYR | 59 | Steady | ▲ 20 | 6% |
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| 41 | Declan CarlileD · PIT | 59 | Steady | ▼ 13 | 3% |
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| 42 | Tom WillanderD · VAN | 59 | Steady | ▲ 29 | 25% |
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| 43 | Nick PaulL · TOR | 58 | Steady | ▼ 28 | 8% |
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| 44 | Sean DurziD · NYR | 58 | Steady | ▲ 20 | 37% |
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| 45 | Connor ZaryC · CGY | 58 | Steady | ▲ 8 | 11% |
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| 46 | Jack RoslovicC · TOR | 58 | Steady | ▼ 5 | 34% |
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| 47 | Matias MaccelliL · NYI | 57 | Steady | ▲ 38 | 14% |
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| 48 | Brian DumoulinD · LAK | 57 | Steady | ▲ 12 | 0% |
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| 49 | Niko MikkolaD · FLA | 57 | Steady | new | 5% |
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| 50 | Matthew WoodR · NSH | 57 | Steady | ▲ 23 | 32% |
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New role and want to know what it led to for similar players? See Breakout Comps.
How Ascension works
We take each skater's last 3, 5 or 10 games (you pick the window) and compare them with his previous 20 games. Early in the season the 20 reach back into last season. Six components measure the change:
- Ice time
- All-situations, 5v5 and power-play TOI per game in the window against his previous 20 games. A two-minute jump in 5v5 time or a minute more on the power play counts for a lot; a one-game spike is shrunk away.
- Power-play role
- His share of the team's PP time and how many games he spent on PP1 (detected from shift data), compared with before. "PP1 in 4 of last 5 (was 0 of 10)" is the classic riser.
- Line role
- His line slot each game from our line detector: L1 counts 1, L2 0.67, L3 0.33, L4 0 (D1 1, D2 0.5, D3 0). Moving into the top six or top four shows up here.
- Elite linemates
- The share of his 5v5 ice time spent with his team's top three scorers (points per game over their last 20 games), from shared-TOI pairs. "61% of 5v5 TOI with McDavid" is a role, not luck.
- Underlying production
- Individual expected goals per 60 (our xG v1 model), on-ice 5v5 xGF/60 and points per game, window vs baseline. It carries the most weight because it was the strongest predictor in the backtest.
- Line Watch events
- Promotions and demotions our deployment tracker flagged in the window (PP1 in or out, line up or down, ice-time jumps or drops), weighted by their significance score.
Each component is a signed value from −1 to +1 (the tanh of the change over a typical move), shrunk by sample size: the window counts for n / (n + 1.5) and the baseline for b / (b + 3). The weights are ice time 0.15, power-play role 0.15, line role 0.05, elite linemates 0.05, underlying production 0.55, line watch events 0.05. The score is 50 + 50 × tanh(Σ weight × value / 0.4): 50 means no change. 75+ is Surging, 60+ Rising, 41–59 Steady, 26–40 Cooling and 25 or lower Falling.
Full details, including how the weights were fit: Ascension methodology.
Does it work? The backtest
We scored every skater every week of 2024-25 and 2025-26 and checked his points per game over the next 10 games. The weights were fit on 2025-26, Oct 27 – Dec 29 (6,020 player-weeks); the rows below are games the fit never saw.
| Holdout | Player-weeks | R² baseline → with score | Error cut | Surging next 10 | Falling next 10 |
|---|---|---|---|---|---|
| 2025-26, Jan – Mar | 6,788 | 0.487 → 0.501 | 1.3% | +0.08 P/GP, 58% beat baseline | −0.09 P/GP, 32% beat baseline |
| 2024-25, Nov – Mar (no pair data) | 10,761 | 0.426 → 0.440 | 1.2% | +0.10 P/GP, 61% beat baseline | −0.10 P/GP, 29% beat baseline |
The honest caveat: over just 10 games, a simple "previous 20 plus last 5 points" model predicts points as well as the score does (R² 0.515). Ascension's value is that it sees the role change (PP1, the top line, more minutes) before or without the points, and tells you why.
FAQ
What is the Ascension score?
A 0–100 score of how much a skater's role and underlying production have changed over his last 3, 5 or 10 games compared with his previous 20. 50 means no change; Surging (75+) players are gaining ice time, power-play time, a better line or better linemates and are producing more chances.
Does a high Ascension score predict more points?
A little, and we publish how much. On games the weights never saw (2025-26, Jan – Mar), Surging players averaged +0.08 points per game more over their next 10 games than in their previous 20, and 58% beat their baseline; Falling players averaged -0.09 and only 32% beat it. Adding the score to a baseline-only model cut the error by 1.3%. Ten-game point totals are noisy, so treat it as a tiebreaker and an early warning, not a guarantee.
Is this just a hot streak list?
No. Points are only one part of one component. A player can be Surging with zero points if he has moved onto PP1 and the top line with more ice time, which is exactly when to pick him up. Check the Luck Meter as well: a riser who is also running hot is more likely to cool off.
Why is a player I know is rising not on the board?
Players need at least five games before the window as a baseline, and anyone who has not played in three weeks drops off. Early in the season the baseline reaches back into last season, which the board notes. The Regulars only filter also hides depth players under 12 minutes a night.
How often does the board update?
After each night's games: the board refreshes when the night's games are ingested and again in the morning once Line Watch events are re-scored.
Can I see only players I can actually pick up?
Yes. By default the board shows players available in an average league: rostered in 50% of leagues or fewer (LineupExperts rostered %), and you can switch the cut to 25% or 75% or show everyone. Connect your Yahoo league and "Available in my league" hides players already rostered in it, using the same check as the Streamer Finder.