Mysticalpizza — CS2 Stats

76561198182744933[U:1:222479205]

820Tracked matches56%Win rate2020Tracked since

CSDB Rating7.0 StrongAggressive Rifler

Premier CS Rating22,175Top 50% of 819 CSDB-tracked playersPink band · top ~6.1% of ranked players (population est.)

FaceitLevel 7Top 42.3% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim85

Positioning63

Utility42

0–100 skill scores via Leetify.

Recent form

STEADY56–41–3Last 10056%Win rateWWWLLWWWLL

Last 10 vs previous 10: +30pp win rate · +0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.5

Aggression9.1

Utility4.2

Positioning6.3

Opening Duels3.3

Clutch3.0

Sharp aimerExcellent counter-strafing

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like jL 91% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Strengths

Counter-strafing. 93% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.1° off target when enemies appear — placement, not flicking, is the bigger win available.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 604ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.5

Positioning6.3

Utility4.2

Mechanics9.5

Opening Duels3.3

Win Impact6.9

Composite 7.0/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time607ms−3ms

first ⅓ avg 610ms → last ⅓ avg 607ms

Headshot accuracy19.4%+0.7%

first ⅓ avg 18.8% → last ⅓ avg 19.4%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.15Best rating — cache 13–3

13–2Biggest win — cache

5Longest win streak

W3Current streak

5–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 82% over 11infernoWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	26	13–13	50%	0.03
nuke	S	11	9–2	82%	0.05
anubis	B	11	5–6	45%	-0.01
dust2	S	10	7–3	70%	0.00
ancient	A	9	5–4	56%	0.04
inferno	D	9	3–6	33%	0.04
mirage	A	7	4–3	57%	0.00
vertigo	S	7	5–2	71%	0.00
overpass	—	3	1–2	33%	0.03
train	—	2	2–0	100%	0.05
office	—	2	1–1	50%	0.04
shelter	—	1	0–1	0%	-0.02
boulder	—	1	0–1	0%	-0.01
warden	—	1	1–0	100%	0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

333Matches

52%Win rate

1.27Avg K/D

81.7ADR

42%Headshot %

Clutches & streaks

35%1v1 clutch win

17%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	19	68%	1.33	17.7
Inferno	14	57%	1.17	17.8
Mirage	12	25%	1.03	14.9
Cache	9	78%	1.55	18.1
Anubis	8	75%	0.94	14.8
Overpass	7	57%	1.33	17.7
Ancient	7	0%	0.99	18.1
Dust2	6	0%	0.90	17.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

19.3%Headshot accuracy

37.4%Accuracy (enemy spotted)

45.1%Spray accuracy

92.7%Counter-strafing

10.1°Preaim

604msReaction time

41.5%T opening success

44.8%CT opening success

0.49Enemies flashed / flash

4.2%Flash assists

4.44HE damage / grenade

13.59Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4918 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–8	-0.02	19%	5 Aug →
mirage	13–3	-0.04	38%	5 Aug →
train	10–0	-0.03	23%	5 Aug →
vertigo	9–13	0.03	16%	30 Jul →
cache	5–13	-0.03	19%	30 Jul →
nuke	13–8	0.01	25%	29 Jul →
vertigo	13–8	0.02	20%	29 Jul →
nuke	13–8	0.02	9%	28 Jul →
cache	10–13	0.03	26%	26 Jul →
nuke	14–16	0.02	20%	26 Jul →
ancient	13–6	0.00	29%	26 Jul →
cache	5–13	-0.02	13%	24 Jul →
cache	7–13	0.02	20%	23 Jul →
ancient	13–10	0.00	18%	23 Jul →
shelter	6–13	-0.02	19%	22 Jul →
boulder	2–13	-0.01	6%	22 Jul →
office	12–12	0.02	11%	22 Jul →
dust2	3–13	0.02	36%	22 Jul →
cache	11–13	-0.00	14%	21 Jul →
anubis	13–9	-0.08	8%	20 Jul →
cache	13–2	0.08	19%	20 Jul →
anubis	13–9	0.01	20%	19 Jul →
anubis	8–13	-0.02	25%	18 Jul →
ancient	13–7	0.09	11%	18 Jul →
anubis	15–15	-0.00	21%	18 Jul →
inferno	5–13	0.02	26%	18 Jul →
inferno	13–5	0.13	14%	18 Jul →
dust2	13–6	0.06	20%	18 Jul →
anubis	15–15	0.03	15%	17 Jul →
nuke	13–3	0.11	33%	17 Jul →
cache	16–14	0.01	22%	17 Jul →
anubis	8–13	-0.03	8%	16 Jul →
mirage	10–4	0.07	18%	16 Jul →
cache	9–13	-0.04	12%	15 Jul →
dust2	13–10	0.02	20%	15 Jul →
dust2	13–4	-0.00	25%	15 Jul →
dust2	2–13	-0.01	14%	15 Jul →
inferno	6–13	0.01	33%	15 Jul →
inferno	13–10	-0.00	14%	14 Jul →
cache	13–7	0.08	14%	13 Jul →
inferno	10–13	0.03	11%	13 Jul →
nuke	13–5	0.06	29%	13 Jul →
ancient	8–13	0.09	30%	13 Jul →
inferno	10–13	0.05	14%	11 Jul →
mirage	8–13	-0.04	13%	11 Jul →
cache	13–10	0.02	8%	11 Jul →
mirage	13–11	0.01	26%	11 Jul →
anubis	13–10	-0.00	21%	11 Jul →
cache	13–7	0.12	15%	11 Jul →
anubis	13–7	-0.00	10%	11 Jul →
mirage	7–13	0.02	18%	10 Jul →
cache	10–13	-0.03	38%	10 Jul →
anubis	6–13	-0.03	20%	10 Jul →
nuke	13–10	0.04	16%	9 Jul →
office	13–6	0.05	9%	8 Jul →
inferno	11–13	0.07	15%	8 Jul →
ancient	11–13	0.00	19%	2 Jul →
ancient	13–8	0.05	28%	1 Jul →
ancient	13–4	0.06	30%	1 Jul →
anubis	13–3	0.14	35%	1 Jul →
nuke	13–8	0.00	26%	29 Jun →
mirage	2–13	-0.01	39%	20 Jun →
vertigo	13–3	0.01	13%	20 Jun →
cache	13–4	0.01	10%	13 Jun →
dust2	6–11	-0.03	15%	12 Jun →
cache	13–11	-0.01	16%	12 Jun →
vertigo	7–13	-0.04	14%	12 Jun →
warden	13–9	0.06	22%	4 Jun →
vertigo	13–6	0.05	20%	3 Jun →
vertigo	13–9	-0.00	21%	3 Jun →
anubis	3–13	-0.12	5%	31 May →
train	13–7	0.13	26%	23 May →
vertigo	13–7	-0.03	19%	23 May →
cache	13–3	0.15	30%	23 May →
overpass	7–13	0.02	24%	16 May →
dust2	13–10	0.01	20%	16 May →
inferno	5–13	0.04	24%	16 May →
cache	13–6	0.06	15%	16 May →
nuke	11–13	0.07	22%	13 May →
cache	5–13	0.04	26%	13 May →
ancient	13–16	0.02	19%	9 May →
cache	13–10	0.11	13%	9 May →
dust2	13–10	0.00	18%	9 May →
nuke	13–6	0.10	17%	9 May →
overpass	10–13	-0.01	31%	6 May →
overpass	13–10	0.08	19%	6 May →
nuke	13–11	0.02	30%	6 May →
cache	7–13	0.00	16%	1 May →
cache	13–8	0.02	10%	1 May →
mirage	13–11	0.01	10%	1 May →
inferno	13–7	0.01	13%	1 May →
dust2	13–3	-0.04	7%	1 May →
cache	6–13	-0.00	18%	30 Apr →
cache	10–13	0.06	17%	30 Apr →
cache	1–13	-0.06	26%	30 Apr →
cache	13–9	-0.02	8%	30 Apr →
cache	10–13	0.00	19%	29 Apr →
cache	13–6	0.11	24%	29 Apr →
nuke	13–7	0.06	20%	28 Apr →
ancient	11–13	-0.00	11%	28 Apr →