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 Contender)

Stat	Per game	Total	Percentile in tier
Points	308.19	6472	47th
Goals	1.0	21	82nd
Assists	0.62	13	78th
Saves	0.48	10	5th
Shots	2.52	53	70th
Demos	0.76	16	50th

League ranking (per game, among 1215 players)

Stat	Per game	Overall rank	Rank in Contender
Points	308.19	#712 / 1215	#59 / 134
Goals	1.0	#132 / 1215	#16 / 134
Assists	0.62	#314 / 1215	#24 / 134
Saves	0.48	#938 / 1215	#106 / 134
Demos	0.76	#628 / 1215	#54 / 134

64% of the season is played (21 → ~33 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 (41 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	6472	10170	10200	10200	10107 – 10293
Goals	21	33	32	31	27 – 37
Assists	13	20	20	21	16 – 24
Saves	10	16	18	18	14 – 22
Shots	53	83	83	81	74 – 91
Demos	16	25	25	26	21 – 30
MVPs	4	6	6	6	4 – 8

Advanced stats (ballchasing)

No ballchasing replay data for this player. Advanced stats (boost, speed, positioning, demos) only exist for the ~37% of players whose matches/scrims were uploaded to ballchasing - coverage depends on who uploads, not on the player.

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	0.51	0.55	0.5 – 0.67
Assists/game	0.76	0.71	0.64 – 0.76
Saves/game	1.02	1.07	0.96 – 1.23
Shots/game	2.0	2.15	2.0 – 2.23

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
Skriviere	S21	Veteran	0.5	0.75	1.0	1.15
Loyboy2	S18	Premier	0.5	0.88	0.75	1.18
Shune.	S24	Master	0.44	0.7	1.3	1.18
DEADLYFEET1001	S23	Challenger	0.54	0.85	0.69	1.20
Ruin5terr	S26	Premier	0.56	0.78	1.11	1.23
Sobes	S23	Elite	0.42	0.66	1.0	1.24
WittingHalo64	S20	Veteran	0.38	0.62	0.88	1.27
Sean	S22	Premier	0.58	0.64	1.31	1.27
Tropicalshortsba	S25	Veteran	0.49	0.71	1.0	1.28
Danub	S26	Rival	0.48	0.52	1.13	1.38

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.