Eclipse

Premier - Gummy Bears - 20-12 (0.625)
99 OVR
overall rating (0–100) · 32 games · how is this calculated?
Overall rating 99/100 Tier dominance: 82nd (+0.9 SD) Projects as: Premier Role: Striker
How are these calculated?

Composite: each per-game stat (goals, assists, saves, shots, demos, shooting %, MVPs) is turned into a z-score vs the player's tier peers, weighted by how much it correlates with winning, summed, then shrunk toward the tier average for small samples (games / (games + 8)).

Tier dominance: that composite expressed two ways - a percentile within the tier (rank), and a margin in standard deviations above the tier average (how big an outlier). The margin is what flags genuine outliers vs. someone merely top of a tight tier.

Overall rating (0-100): the composite plus a tier-strength bonus (Premier counts most), turned into a league-wide percentile - so it's comparable across tiers, unlike tier dominance.

Projects as: re-sorting every player by overall skill into the tiers' real sizes, the tier this player would land in. Projecting up a tier (and being an outlier) = "overskilled." A model estimate.

MVPs
7
22% of games
Shot %
38%

Per-game production (percentile within Premier)

StatPer gameTotalPercentile in tier
Points 349.62 11188
52nd
Goals 1.03 33
83rd
Assists 0.44 14
21st
Saves 1.25 40
29th
Shots 2.75 88
58th
Demos 1.78 57
83rd

League ranking (per game, among 1213 players)

StatPer gameOverall rankRank in Premier
Points349.62 #418 / 1213 #25 / 73
Goals1.03 #134 / 1213 #9 / 73
Assists0.44 #647 / 1213 #41 / 73
Saves1.25 #507 / 1213 #36 / 73
Demos1.78 #79 / 1213 #9 / 73

Season projection

High confidence

64% of the season is played (32 → ~50 games). Projected (this season) blends the current rate with the tier average (regression to the mean). Projected (all data) instead regresses toward the player’s own career rate (155 games across 3 past seasons). Pace is the naive "keep current rate" number. Range = 80% prediction interval on the this-season projection.

Stat Now Pace Projected (season) Projected (all data) 80% range
Points 11188 17481 17529 17529 17406 – 17651
Goals 33 52 51 50 44 – 57
Assists 14 22 22 23 18 – 27
Saves 40 62 63 62 56 – 71
Shots 88 138 137 138 127 – 148
Demos 57 89 87 89 79 – 96
MVPs 7 11 11 11 8 – 14

Advanced stats (ballchasing)

Advanced OVR 90 /100

From 32 ballchasing replays (matches + scrims). Advanced OVR is a percentile among the 762 players with enough replay data - separate from the box-score OVR above.

Boost / min 434.9
Avg boost 48.2
Boost stolen / game 630.5
% time at 0 boost 13.2%
Avg speed (uu/s) 1561.0
% supersonic 16.4%
% time high in air 6.5%
Avg distance to ball 2638.1
% time attacking third 23.6%
Demos / game 1.8
Demos taken / game 1.1
Shooting % 37.2%

Career history (season over season)

SeasonTierGamesGoals/gAssists/gSaves/gBoost/min
S23Premier52 0.640.961.12 438
S24Premier51 0.90.711.16 439
S25Premier52 0.690.561.15 429
S26Premier32 1.030.441.25 435

Beyond RSC - lifetime & other play

External skill estimate: ~74 OVR Medium confidence — inferred from 75 public ranked-3v3 games (their score/game maps to OVR; this signal correlates ~0.71 with RSC OVR). Their actual RSC OVR is 99.
SourceGames RecordWin % Score/g
Lifetime (all)404150-168 47% 368
Non-RSC ranked 3v37517-35 33% 344
Non-RSC other329133-133 50% 373

From public ballchasing replays (score-based, so no goals/saves breakdown). Non-RSC play tracks a player's overall level well but not their standing within a tier — see the ratings notes. Only players with a Steam id and uploaded public games appear here.

Historical analysis - data: Official · All seasons (change in the nav)

Comparable-based outlook

High confidence

Where the 25 most similar players from 11 completed past season(s) landed for each per-game stat (median + middle-50% range). A "players like you finished here" anchor that complements the pace projection above.

StatThis seasonComparables medianTypical range
Goals/game1.03 0.92 0.84 – 1.02
Assists/game0.44 0.53 0.47 – 0.56
Saves/game1.25 1.27 1.17 – 1.36
Shots/game2.75 2.76 2.63 – 2.86

Most similar players (across RSC history)

Nearest matches by per-game production & play-style (goals, assists, saves, shots, boost, speed, positioning, demos), standardized across 6659 player-seasons. Lower distance = more similar.

PlayerSeasonTierGoals/gAssists/gSaves/gSimilarity
Talent? S26Elite 0.940.411.28 0.92
honk=bonk S17Master 0.880.381.25 1.15
ZachOff S22Elite 1.080.461.25 1.17
Tsheg S25Premier 0.80.481.3 1.18
Dx Geo xD S22Veteran 0.970.551.34 1.18
JayX S22Elite 1.210.541.33 1.20
oofitsfine S26Contender 1.090.621.28 1.25
Polashjl S23Veteran 1.190.531.47 1.30
Array S20Prospect 0.880.381.1 1.33
Catlas S26Veteran 1.080.581.38 1.35

Descriptive comparables - cross-season stat scales can shift, and players who changed names between seasons won't link.


Data source: live (rscna.com) - standings & schedule refresh hourly.