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 Amateur)

Stat	Per game	Total	Percentile in tier
Points	351.78	11257	79th
Goals	0.88	28	60th
Assists	0.38	12	43rd
Saves	0.91	29	53rd
Shots	2.84	91	89th
Demos	0.5	16	36th

League ranking (per game, among 1213 players)

Stat	Per game	Overall rank	Rank in Amateur
Points	351.78	#406 / 1213	#10 / 61
Goals	0.88	#286 / 1213	#18 / 61
Assists	0.38	#750 / 1213	#27 / 61
Saves	0.91	#832 / 1213	#22 / 61
Demos	0.5	#797 / 1213	#30 / 61

69% of the season is played (32 → ~46 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 (137 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	11257	16182	16019	16019	15917 – 16122
Goals	28	40	40	40	35 – 45
Assists	12	17	17	18	14 – 21
Saves	29	42	42	41	36 – 47
Shots	91	131	129	129	119 – 138
Demos	16	23	24	23	20 – 28
MVPs	8	12	11	11	9 – 14

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	318.5
Avg boost	51.5
Boost stolen / game	383.4
% time at 0 boost	9.4%
Avg speed (uu/s)	1426.3
% supersonic	8.7%
% time high in air	3.6%
Avg distance to ball	3165.1
% time attacking third	20.0%
Demos / game	0.5
Demos taken / game	1.2
Shooting %	28.5%

Career history (season over season)

Season	Tier	Games	Goals/g	Assists/g	Saves/g	Boost/min
S23	Amateur	26	0.5	0.46	0.58	320
S24	Amateur	55	0.91	0.44	0.8	298
S25	Amateur	56	0.88	0.52	0.82	327
S26	Amateur	32	0.88	0.38	0.91	318

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	0.88	0.87	0.82 – 0.93
Assists/game	0.38	0.42	0.35 – 0.47
Saves/game	0.91	0.95	0.86 – 1.0
Shots/game	2.84	2.73	2.58 – 2.83

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
MobBossCitrus	S24	Challenger	0.92	0.46	0.92	0.85
RL Camaro	S25	Amateur	0.88	0.52	0.82	0.87
ChrisakaMrXD	S13	Elite	0.92	0.42	0.83	0.88
fender_bender2	S25	Prospect	0.83	0.33	0.97	0.94
Mortal Frenzy	S26	Contender	0.83	0.5	0.92	0.94
Auty RL	S24	Challenger	0.83	0.4	0.98	1.09
El_Macho	S23	Challenger	0.64	0.36	0.71	1.10
OG_Cuddles_	S19	Contender	0.82	0.27	0.82	1.10
Ducky	S17	Challenger	0.75	0.5	0.88	1.10
Bieles	S26	Prospect	0.92	0.5	1.08	1.13

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.