JMS — CS2 Stats

US76561198211998809[U:1:251733081]Steam profile ↗✓ No bans

2,300Tracked matches27%Win rate2020Tracked since

CSDB Rating5.6 SolidHybrid Rifler

FaceitLevel 10 · 2,606 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim63

Positioning60

Utility75

0–100 skill scores via Leetify.

Recent form

COLD47–51–2Last 10047%Win rateLLWLLLLLLL

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

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.3

Aggression7.4

Utility7.5

Positioning6.0

Opening Duels3.5

Clutch4.0

Strong CT-side openerHigh utility contribution

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 Twistzz 88% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile.

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

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 599ms 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

Aim6.3

Positioning6.0

Utility7.5

Mechanics5.6

Opening Duels3.9

Win Impact0.0

Composite 5.6/10 (Solid), 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 rating0.03+0.04

first ⅓ avg -0.01 → last ⅓ avg 0.03

Reaction time597ms+2ms

first ⅓ avg 595ms → last ⅓ avg 597ms

Headshot accuracy22.4%−0.1%

first ⅓ avg 22.5% → last ⅓ avg 22.4%

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

0.16Best rating — dust2 13–4

13–1Biggest win — warden

7Longest win streak

L2Current streak

5–7In matches decided by ≤2 rounds

11Overtime games

Map breakdown

cacheBest map · 62% over 13infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	20	10–10	50%	0.02
mirage	C	19	7–12	37%	-0.02
inferno	D	15	5–10	33%	-0.01
ancient	B	15	8–7	53%	-0.01
cache	A	13	8–5	62%	0.05
anubis	D	9	3–6	33%	0.01
vertigo	—	2	1–1	50%	0.13
nuke	—	2	1–1	50%	-0.04
overpass	—	2	2–0	100%	-0.02
warden	—	1	1–0	100%	0.10
office	—	1	1–0	100%	0.01
train	—	1	0–1	0%	-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,554Matches

51%Win rate

1.11Avg K/D

75.2ADR

48%Headshot %

Clutches & streaks

40%1v1 clutch win

21%1v2 clutch win

11Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	223	51%	1.07	14.9
Ancient	201	51%	1.07	15.3
Mirage	199	50%	0.93	14.0
Anubis	152	47%	1.07	15.1
Inferno	135	52%	1.14	14.9
Nuke	43	51%	1.04	15.4
Overpass	28	50%	1.06	15.0
Cache	25	52%	1.25	17.2

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.

21.7%Headshot accuracy

34.0%Accuracy (enemy spotted)

34.7%Spray accuracy

75.1%Counter-strafing

11.3°Preaim

599msReaction time

26.5%T opening success

61.3%CT opening success

0.63Enemies flashed / flash

12.2%Flash assists

15.76HE damage / grenade

13.83Flashes / 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.

Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 26.4943% — below the 40% mark we flag

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 15 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	6–13	-0.04	30%	24 Aug →
dust2	10–13	0.04	14%	18 Aug →
cache	13–3	0.09	14%	12 Aug →
inferno	15–19	-0.00	26%	6 Aug →
anubis	4–13	-0.02	23%	31 Jul →
ancient	5–13	-0.01	35%	30 Jul →
dust2	3–13	-0.02	17%	30 Jul →
ancient	4–13	-0.05	17%	28 Jul →
ancient	13–16	0.01	17%	28 Jul →
cache	11–13	0.06	30%	22 Jul →
inferno	13–4	0.01	32%	22 Jul →
ancient	3–13	-0.01	26%	21 Jul →
ancient	4–13	-0.04	20%	18 Jul →
mirage	11–13	-0.04	16%	18 Jul →
anubis	11–13	-0.01	15%	18 Jul →
dust2	8–13	0.03	23%	18 Jul →
anubis	9–13	0.01	20%	14 Jul →
dust2	10–13	0.03	21%	14 Jul →
cache	13–7	0.06	19%	9 Jul →
inferno	3–13	-0.04	23%	9 Jul →
dust2	13–4	0.16	24%	9 Jul →
cache	9–13	-0.01	19%	9 Jul →
inferno	7–13	-0.00	26%	9 Jul →
ancient	13–7	0.10	17%	9 Jul →
cache	16–12	0.10	24%	8 Jul →
cache	16–12	0.10	22%	7 Jul →
cache	5–13	-0.02	22%	27 Jun →
inferno	8–13	0.03	26%	26 Jun →
anubis	13–9	0.10	19%	15 Jun →
dust2	8–13	-0.01	17%	10 Jun →
cache	12–12	0.11	28%	9 Jun →
vertigo	10–13	0.10	37%	9 Jun →
vertigo	13–6	0.15	20%	9 Jun →
mirage	0–13	-0.04	19%	9 Jun →
inferno	13–8	-0.01	28%	3 Jun →
mirage	13–10	0.01	18%	3 Jun →
mirage	15–15	0.05	18%	2 Jun →
dust2	3–13	-0.01	25%	31 May →
anubis	13–9	0.05	20%	31 May →
inferno	8–13	0.02	18%	31 May →
mirage	11–13	0.01	25%	31 May →
dust2	13–3	0.04	32%	31 May →
warden	13–1	0.10	32%	31 May →
cache	11–13	-0.06	20%	31 May →
cache	13–6	-0.02	33%	27 May →
dust2	7–13	0.05	22%	23 May →
dust2	6–13	-0.00	16%	21 May →
ancient	13–8	-0.02	15%	21 May →
nuke	13–7	-0.02	19%	21 May →
mirage	11–13	-0.01	25%	20 May →
mirage	9–13	-0.04	11%	9 May →
overpass	13–2	-0.03	10%	9 May →
cache	13–7	0.08	28%	6 May →
cache	9–2	0.05	17%	6 May →
cache	13–7	0.11	27%	3 May →
mirage	13–8	-0.02	22%	1 May →
mirage	13–11	-0.02	13%	1 May →
mirage	9–13	-0.06	22%	30 Apr →
nuke	2–13	-0.06	27%	30 Apr →
inferno	4–13	-0.02	38%	26 Apr →
ancient	16–14	-0.03	24%	25 Apr →
dust2	13–6	0.05	26%	25 Apr →
ancient	10–13	-0.06	18%	24 Apr →
anubis	16–12	0.03	20%	24 Apr →
mirage	11–13	-0.02	30%	22 Apr →
dust2	5–13	-0.07	30%	18 Apr →
overpass	13–8	-0.01	23%	14 Apr →
anubis	4–13	-0.02	28%	10 Apr →
anubis	10–13	-0.04	14%	7 Apr →
mirage	13–11	-0.03	29%	31 Mar →
ancient	13–9	-0.07	39%	25 Mar →
inferno	12–16	-0.04	29%	24 Mar →
anubis	7–13	-0.00	26%	12 Mar →
inferno	13–9	-0.00	31%	9 Mar →
inferno	13–3	0.03	30%	9 Mar →
inferno	16–14	0.01	21%	25 Feb →
dust2	13–1	0.13	20%	24 Feb →
inferno	4–13	-0.06	27%	24 Feb →
ancient	13–10	-0.02	20%	18 Feb →
mirage	7–13	-0.05	8%	18 Feb →
dust2	13–9	0.03	47%	18 Feb →
ancient	4–13	-0.04	16%	18 Feb →
mirage	6–13	-0.02	21%	13 Feb →
dust2	13–7	-0.05	8%	13 Feb →
dust2	13–2	0.04	24%	13 Feb →
inferno	6–13	0.01	25%	27 Jan →
mirage	13–7	-0.02	21%	25 Jan →
office	13–2	0.01	19%	25 Jan →
ancient	25–22	-0.03	22%	15 Jan →
train	7–13	-0.03	16%	14 Jan →
mirage	9–13	0.02	25%	5 Jan →
mirage	13–8	-0.06	17%	5 Jan →
ancient	13–5	0.07	32%	4 Jan →
mirage	13–10	-0.06	17%	2 Jan →
dust2	16–14	0.00	26%	2 Jan →
ancient	13–10	0.07	20%	27 Dec →
dust2	13–2	0.06	15%	25 Dec →
dust2	13–7	-0.01	23%	25 Dec →
inferno	6–13	-0.03	20%	18 Dec →
mirage	6–13	-0.04	10%	17 Dec →