sloth — CS2 Stats

76561198007148166[U:1:46882438]Steam profile ↗✓ No bans

3,247Tracked matches43%Win rate2021Tracked since

CSDB Rating4.9 DevelopingHybrid Rifler

Premier CS Rating23,714Top 25% of 44,590 CSDB-tracked playersPink band · top ~4.4% of ranked players (population est.)

CSDB Leaderboard#10438 of 57889 tracked

FaceitLevel 8 · 1,945 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim66

Positioning51

Utility34

0–100 skill scores via Leetify.

Recent form

STEADY45–50–5Last 10045%Win rateLWWLWLLWLW

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.

Aim6.6

Aggression6.3

Utility3.4

Positioning5.1

Opening Duels3.1

Clutch2.8

Limited utility dependence

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 ropz 85% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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

Areas to improve

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

Reaction time. 569ms 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

Aim6.6

Positioning5.1

Utility3.4

Mechanics5.0

Opening Duels3.1

Win Impact2.6

Composite 4.9/10 (Developing), 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 rating0.00−0.00

first ⅓ avg 0.00 → last ⅓ avg 0.00

Reaction time578ms−36ms

first ⅓ avg 613ms → last ⅓ avg 578ms

Headshot accuracy18.9%−0.5%

first ⅓ avg 19.4% → last ⅓ avg 18.9%

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

0.12Best rating — dust2 13–3

13–0Biggest win — inferno

6Longest win streak

6–11In matches decided by ≤2 rounds

12Overtime games

Map breakdown

ancientBest map · 56% over 16overpassWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	27	12–15	44%	0.01
nuke	C	16	7–9	44%	-0.00
ancient	A	16	9–7	56%	0.02
dust2	B	15	7–8	47%	0.02
mirage	A	11	6–5	55%	-0.00
anubis	D	6	2–4	33%	0.01
overpass	D	5	1–4	20%	-0.05
cache	—	4	1–3	25%	0.02

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,838Matches

49%Win rate

1.08Avg K/D

81.0ADR

44%Headshot %

Clutches & streaks

34%1v1 clutch win

18%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	394	51%	1.15	17.0
Ancient	272	49%	1.07	16.3
Nuke	230	52%	1.04	16.3
Vertigo	123	52%	1.12	16.9
Train	110	52%	1.05	16.0
Anubis	103	46%	1.05	16.4
Dust2	99	40%	1.03	15.7
Mirage	76	38%	0.95	15.6

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.

20.0%Headshot accuracy

33.3%Accuracy (enemy spotted)

34.6%Spray accuracy

72.7%Counter-strafing

9.3°Preaim

569msReaction time

35.7%T opening success

49.0%CT opening success

0.56Enemies flashed / flash

9.6%Flash assists

11.38HE damage / grenade

1.80Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 1.7955 — below the 4 mark we flag
Grenade Lineups →
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 35.6948% — below the 40% mark we flag

Spend your practice time on Overpass

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	8–13	0.05	19%	29 Aug →
mirage	13–10	-0.00	20%	29 Aug →
nuke	13–11	0.02	14%	29 Aug →
ancient	4–13	0.09	21%	24 Aug →
dust2	13–5	-0.01	22%	24 Aug →
nuke	8–13	-0.09	14%	24 Aug →
dust2	11–13	0.05	25%	22 Aug →
cache	13–7	-0.02	16%	22 Aug →
mirage	6–13	-0.09	14%	22 Aug →
nuke	13–4	0.04	23%	22 Aug →
inferno	12–12	-0.03	31%	21 Aug →
cache	8–13	-0.02	26%	20 Aug →
dust2	6–13	-0.02	17%	16 Aug →
mirage	10–13	-0.02	13%	16 Aug →
dust2	13–4	0.07	18%	16 Aug →
dust2	13–4	0.04	22%	16 Aug →
mirage	3–13	-0.02	18%	16 Aug →
dust2	16–13	0.03	18%	13 Aug →
nuke	9–13	0.02	16%	30 Jul →
inferno	13–6	0.03	23%	30 Jul →
anubis	11–13	0.09	24%	30 Jul →
nuke	10–13	-0.05	29%	29 Jul →
ancient	9–13	-0.02	12%	29 Jul →
inferno	13–9	0.02	21%	28 Jul →
dust2	0–6	-0.06	0%	28 Jul →
dust2	15–15	-0.01	23%	27 Jul →
mirage	13–6	0.03	26%	27 Jul →
ancient	13–7	0.05	17%	25 Jul →
inferno	7–13	-0.04	14%	25 Jul →
inferno	11–13	0.02	26%	24 Jul →
ancient	11–13	-0.03	12%	24 Jul →
inferno	16–14	-0.04	11%	23 Jul →
mirage	11–13	-0.03	17%	23 Jul →
dust2	4–13	-0.03	33%	22 Jul →
ancient	13–11	0.02	23%	22 Jul →
inferno	13–4	0.00	10%	22 Jul →
dust2	8–13	0.02	27%	22 Jul →
inferno	13–4	0.01	15%	22 Jul →
mirage	13–10	0.03	14%	22 Jul →
anubis	6–13	-0.05	19%	22 Jul →
mirage	5–13	-0.01	30%	21 Jul →
dust2	13–8	0.00	25%	21 Jul →
mirage	13–6	-0.02	21%	21 Jul →
dust2	13–3	0.12	28%	21 Jul →
inferno	13–10	0.04	11%	21 Jul →
dust2	13–5	0.06	20%	21 Jul →
inferno	13–8	0.05	10%	20 Jul →
nuke	14–16	-0.03	17%	20 Jul →
ancient	6–13	0.09	31%	20 Jul →
nuke	14–16	0.04	22%	19 Jul →
cache	8–13	0.10	43%	19 Jul →
ancient	13–7	0.06	37%	19 Jul →
dust2	9–13	0.04	15%	19 Jul →
inferno	13–7	-0.02	23%	19 Jul →
inferno	13–0	0.01	100%	19 Jul →
inferno	13–6	0.04	18%	15 Jul →
cache	13–16	0.01	14%	13 Jul →
inferno	7–13	0.06	35%	10 Jul →
nuke	13–2	0.04	22%	10 Jul →
ancient	13–10	0.02	38%	10 Jul →
overpass	1–13	-0.14	6%	5 Jul →
ancient	13–11	-0.02	13%	5 Jul →
nuke	10–13	0.01	21%	7 May →
overpass	13–7	-0.01	22%	7 May →
inferno	10–13	0.00	21%	7 May →
inferno	14–16	0.05	24%	7 May →
ancient	8–13	0.07	23%	7 May →
nuke	13–7	0.03	49%	4 May →
mirage	16–12	0.08	23%	1 May →
overpass	6–13	-0.02	17%	1 May →
dust2	15–15	0.05	21%	25 Apr →
mirage	13–10	0.01	19%	25 Apr →
inferno	13–8	-0.01	30%	12 Apr →
anubis	6–13	-0.01	23%	12 Apr →
inferno	15–15	-0.00	18%	12 Apr →
ancient	8–13	-0.05	16%	12 Apr →
ancient	9–13	0.02	18%	11 Apr →
nuke	13–8	0.00	13%	11 Apr →
ancient	13–10	0.07	18%	11 Apr →
nuke	13–6	0.03	21%	11 Apr →
inferno	9–13	-0.05	14%	11 Apr →
ancient	13–4	0.07	23%	11 Apr →
nuke	3–13	-0.03	23%	6 Apr →
inferno	3–13	-0.06	18%	4 Apr →
nuke	15–15	-0.05	11%	4 Apr →
anubis	13–7	-0.02	18%	4 Apr →
inferno	8–13	-0.00	15%	4 Apr →
ancient	13–3	-0.00	24%	23 Mar →
nuke	13–5	-0.02	14%	23 Mar →
inferno	11–13	-0.02	18%	23 Mar →
inferno	11–13	0.01	15%	22 Mar →
anubis	11–13	0.02	18%	22 Mar →
overpass	4–13	-0.06	6%	22 Mar →
anubis	13–11	0.05	23%	21 Mar →
inferno	8–13	0.09	15%	19 Mar →
overpass	7–13	-0.03	18%	19 Mar →
nuke	5–13	-0.05	19%	19 Mar →
inferno	16–14	0.10	21%	19 Mar →
inferno	9–13	-0.05	25%	18 Mar →
ancient	13–3	-0.03	17%	18 Mar →