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.

Per-game production (percentile within Elite)

Stat	Per game	Total	Percentile in tier
Points	331.87	4978	27th
Goals	0.8	12	52nd
Assists	0.33	5	6th
Saves	1.47	22	54th
Shots	2.33	35	29th
Demos	1.6	24	88th

League ranking (per game, among 1215 players)

Stat	Per game	Overall rank	Rank in Elite
Points	331.87	#568 / 1215	#94 / 179
Goals	0.8	#391 / 1215	#59 / 179
Assists	0.33	#813 / 1215	#117 / 179
Saves	1.47	#303 / 1215	#58 / 179
Demos	1.6	#109 / 1215	#15 / 179

56% of the season is played (15 → ~27 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 (116 games across 2 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	4978	8960	9055	9055	8954 – 9156
Goals	12	22	21	22	17 – 26
Assists	5	9	10	10	6 – 14
Saves	22	40	39	42	33 – 46
Shots	35	63	64	66	55 – 72
Demos	24	43	41	41	34 – 47
MVPs	2	4	4	4	2 – 6

From 15 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	362.6
Avg boost	49.4
Boost stolen / game	566.1
% time at 0 boost	8.9%
Avg speed (uu/s)	1514.0
% supersonic	10.4%
% time high in air	3.8%
Avg distance to ball	3129.9
% time attacking third	19.6%
Demos / game	1.6
Demos taken / game	1.1
Shooting %	36.1%

Career history (season over season)

Season	Tier	Games	Goals/g	Assists/g	Saves/g	Boost/min
S23	Veteran	7	1.29	0.71	1.29	346
S24	Veteran	57	0.82	0.47	1.7	378
S25	Veteran	59	0.81	0.56	1.95	359
S26	Elite	15	0.8	0.33	1.47	363

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

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.

Stat	This season	Comparables median	Typical range
Goals/game	0.8	0.74	0.71 – 0.79
Assists/game	0.33	0.39	0.37 – 0.43
Saves/game	1.47	1.38	1.28 – 1.54
Shots/game	2.33	2.35	2.27 – 2.5

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.

Player	Season	Tier	Goals/g	Assists/g	Saves/g	Similarity
Defiance	S23	Veteran	0.85	0.37	1.54	0.69
OurStevie	S25	Challenger	0.74	0.3	1.23	0.91
derrrrrrrrp	S22	Veteran	0.78	0.38	1.49	0.96
Lorak	S25	Challenger	0.74	0.37	1.74	1.12
Whiffy_RL	S23	Challenger	0.69	0.51	1.49	1.14
jknop2	S20	Veteran	0.75	0.38	1.29	1.14
Kaisaroh	S26	Master	0.93	0.32	1.68	1.16
Mathews175	S19	Veteran	0.67	0.39	1.33	1.16
BARDOWNSKI .	S26	Challenger	0.81	0.25	1.25	1.19
mykul.457	S17	Rival	0.75	0.25	1.38	1.19

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

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