ChromaToad

Challenger - Panda Bears - 10-22 (0.312)
35 OVR
overall rating (0–100) · 32 games · how is this calculated?
Overall rating 35/100 Tier dominance: 31st (-0.6 SD) Projects as: Challenger Role: Anchor
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
4
12% of games
Shot %
25%

Per-game production (percentile within Challenger)

StatPer gameTotalPercentile in tier
Points 370.03 11841
71st
Goals 0.59 19
27th
Assists 0.59 19
61st
Saves 1.69 54
90th
Shots 2.41 77
42nd
Demos 1.19 38
77th

League ranking (per game, among 1213 players)

StatPer gameOverall rankRank in Challenger
Points370.03 #277 / 1213 #38 / 166
Goals0.59 #696 / 1213 #96 / 166
Assists0.59 #369 / 1213 #51 / 166
Saves1.69 #125 / 1213 #13 / 166
Demos1.19 #275 / 1213 #30 / 166

Season projection

Medium confidence

53% of the season is played (32 → ~60 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 (27 games across 1 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 11841 22202 22041 22041 21872 – 22210
Goals 19 36 37 36 30 – 44
Assists 19 36 35 35 29 – 42
Saves 54 101 99 96 88 – 110
Shots 77 144 145 146 131 – 159
Demos 38 71 70 74 61 – 80
MVPs 4 8 8 8 4 – 11

Advanced stats (ballchasing)

Advanced OVR 43 /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 363.2
Avg boost 48.2
Boost stolen / game 432.3
% time at 0 boost 10.1%
Avg speed (uu/s) 1505.5
% supersonic 15.5%
% time high in air 4.5%
Avg distance to ball 2730.6
% time attacking third 18.7%
Demos / game 1.2
Demos taken / game 1.0
Shooting % 20.4%

Career history (season over season)

SeasonTierGamesGoals/gAssists/gSaves/gBoost/min
S25Rival27 0.590.481.04 378
S26Challenger32 0.590.591.69 363

Beyond RSC - lifetime & other play

External skill estimate: ~43 OVR High confidence — inferred from 1959 public ranked-3v3 games (their score/game maps to OVR; this signal correlates ~0.71 with RSC OVR). Their actual RSC OVR is 35.
SourceGames RecordWin % Score/g
Lifetime (all)60332162-2221 49% 327
RSC (official)161-12 8% 314
Non-RSC ranked 3v31959693-711 49% 294
Non-RSC other40581468-1498 49% 342

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/game0.59 0.6 0.54 – 0.71
Assists/game0.59 0.58 0.57 – 0.61
Saves/game1.69 1.64 1.56 – 1.73
Shots/game2.41 2.37 2.29 – 2.44

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
Skulzy9 S23Elite 0.60.511.71 0.88
derrrrrrrrp S20Veteran 0.580.581.65 0.89
Stingray S25Elite 0.760.581.7 0.98
luckyy.12 S22Veteran 0.540.611.81 1.00
Kri0s S22Master 0.770.721.77 1.01
JK S20Premier 0.560.51.75 1.03
Fluffy S21Master 0.540.571.5 1.03
Kingtutt97 S26Challenger 0.530.661.41 1.04
Super S23Master 0.710.531.58 1.04
buckle S24Elite 0.650.61.7 1.05

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.