RootinTootinPutin — CS2 Stats

ZA76561198364166978[U:1:403901250]Steam profile ↗

1,644Tracked matches50%Win rate2021Tracked since

6,948Hours in CS

CSDB Rating6.3 SolidAggressive Rifler

WingmanSilver Elite

Ladder ranks via Leetify

Performance scores

Aim83

Positioning46

Utility51

0–100 skill scores via Leetify.

Recent form

STEADY51–45–4Last 10051%Win rateWLLLWLLWWW

Last 10 vs previous 10: -10pp win rate · -0.03 avg rating

Player DNA

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

Aim8.3

Aggression6.7

Utility5.1

Positioning4.6

Opening Duels2.5

Excellent 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 ropz 90% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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. 92% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Positioning. Positioning trails aim by 37 points — deaths here waste a strong aim profile.

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

Reaction time. 638ms 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

Aim8.3

Positioning4.6

Utility5.1

Mechanics9.4

Opening Duels2.5

Win Impact5.0

Composite 6.3/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.03

first ⅓ avg 0.01 → last ⅓ avg -0.02

Reaction time641ms+24ms

first ⅓ avg 617ms → last ⅓ avg 641ms

Headshot accuracy19.4%−5.9%

first ⅓ avg 25.4% → 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

0.16Best rating — train 13–1

13–1Biggest win — train

6Longest win streak

9–10In matches decided by ≤2 rounds

10Overtime games

Map breakdown

trainBest map · 88% over 8dust2Weakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
ancient	A	18	10–8	56%	-0.01
nuke	C	16	6–10	38%	-0.01
overpass	S	15	10–5	67%	-0.02
inferno	C	14	6–8	43%	-0.01
mirage	D	12	4–8	33%	0.01
dust2	D	11	3–8	27%	0.00
train	S	8	7–1	88%	0.03
anubis	—	4	4–0	100%	-0.04
cache	—	1	1–0	100%	-0.01
vertigo	—	1	0–1	0%	0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

52,599Lifetime kills

0.98K/D

2,584Matches

46.4%Match win rate · Top 50% of tracked players

47.5%Headshot % · Top 50% of tracked players

2.5%Shot accuracy

5,241MVPs

6,948Hours (in match)

1,341Bombs planted

536Bombs defused

Most-used weapons

AK-4720,376

M4A4 / M4A1-S8,102

AWP4,724

Desert Eagle2,984

MP92,454

P2000 / USP-S1,957

Glock-181,542

Galil AR1,430

MAC-101,411

SG 5531,182

Lifetime map wins

3,802inferno

3,686dust2

2,650nuke

1,418vertigo

1,160train

125cbble

79italy

54office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

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

20.1%Headshot accuracy

38.2%Accuracy (enemy spotted)

37.7%Spray accuracy

92.5%Counter-strafing

9.0°Preaim

638msReaction time

45.5%T opening success

34.4%CT opening success

0.54Enemies flashed / flash

11.8%Flash assists

11.56HE damage / grenade

8.70Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 34.355% — below the 40% mark we flag

Spend your practice time on Dust 2

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–9	-0.01	6%	14 Jul →
ancient	11–13	-0.04	24%	5 Apr →
overpass	6–13	-0.00	23%	11 Mar →
ancient	8–13	-0.05	13%	28 Feb →
anubis	16–13	-0.06	20%	28 Feb →
overpass	3–13	-0.02	16%	28 Feb →
ancient	10–13	-0.03	16%	27 Feb →
overpass	13–11	-0.04	18%	27 Feb →
overpass	13–10	-0.01	15%	27 Feb →
nuke	13–4	-0.06	17%	27 Feb →
inferno	10–13	-0.01	15%	25 Feb →
mirage	16–13	0.06	21%	25 Feb →
inferno	11–13	-0.04	15%	24 Feb →
dust2	16–13	0.04	27%	24 Feb →
overpass	13–5	-0.03	12%	18 Feb →
ancient	13–11	-0.04	34%	18 Feb →
ancient	13–4	0.07	26%	16 Feb →
inferno	10–13	-0.07	31%	16 Feb →
nuke	11–13	-0.05	20%	15 Feb →
inferno	13–6	0.01	18%	15 Feb →
ancient	13–11	-0.05	20%	15 Feb →
dust2	7–13	-0.05	9%	15 Feb →
dust2	3–13	0.01	19%	15 Feb →
mirage	11–13	0.05	22%	9 Feb →
ancient	13–6	-0.06	23%	8 Feb →
inferno	13–8	0.02	24%	8 Feb →
inferno	12–16	-0.02	27%	8 Feb →
nuke	6–13	-0.06	21%	8 Feb →
anubis	13–8	-0.02	24%	3 Feb →
dust2	8–13	-0.04	19%	3 Feb →
mirage	13–16	-0.01	13%	3 Feb →
inferno	5–13	-0.06	11%	29 Jan →
nuke	16–14	0.05	21%	27 Jan →
anubis	13–11	-0.06	20%	27 Jan →
overpass	8–13	-0.06	20%	13 Jan →
dust2	8–13	-0.01	22%	13 Jan →
ancient	1–13	-0.08	29%	12 Jan →
inferno	13–11	0.00	22%	11 Jan →
nuke	13–6	-0.00	10%	11 Jan →
ancient	2–7	-0.01	21%	11 Jan →
inferno	10–13	-0.00	22%	3 Jan →
nuke	5–13	0.04	24%	3 Jan →
ancient	13–3	0.04	28%	3 Jan →
nuke	4–13	-0.03	19%	3 Jan →
nuke	9–13	-0.07	22%	3 Jan →
overpass	13–10	-0.02	31%	2 Jan →
ancient	2–13	-0.10	12%	2 Jan →
nuke	6–13	-0.01	35%	27 Dec →
ancient	11–13	0.01	29%	27 Dec →
dust2	6–13	0.01	32%	27 Dec →
nuke	4–13	-0.05	37%	27 Dec →
ancient	13–10	0.08	34%	27 Dec →
overpass	13–5	0.01	29%	27 Dec →
dust2	2–13	-0.08	13%	15 Dec →
mirage	2–13	-0.00	30%	15 Dec →
ancient	13–10	0.04	32%	15 Dec →
inferno	6–13	0.00	21%	14 Dec →
dust2	12–12	0.08	23%	9 Dec →
overpass	13–10	-0.03	17%	6 Dec →
mirage	13–11	-0.03	17%	3 Dec →
inferno	13–6	0.03	16%	3 Dec →
train	13–6	0.05	24%	2 Dec →
overpass	13–5	0.05	36%	2 Dec →
overpass	13–7	-0.01	12%	2 Dec →
mirage	5–13	0.02	15%	2 Dec →
overpass	13–10	0.05	24%	2 Dec →
mirage	13–8	0.06	9%	2 Dec →
inferno	13–10	0.06	28%	2 Dec →
mirage	8–13	0.00	23%	14 Nov →
nuke	10–13	-0.03	26%	14 Nov →
inferno	13–9	-0.01	15%	14 Nov →
mirage	13–4	0.06	19%	14 Nov →
overpass	14–16	-0.08	50%	14 Nov →
nuke	13–10	0.05	23%	14 Nov →
nuke	13–8	0.08	21%	14 Nov →
train	13–11	-0.00	26%	14 Nov →
nuke	15–15	-0.04	15%	13 Nov →
vertigo	11–13	0.05	28%	11 Nov →
train	13–9	0.02	29%	11 Nov →
train	10–13	-0.02	30%	11 Nov →
overpass	13–11	-0.03	14%	11 Nov →
mirage	5–13	-0.07	27%	11 Nov →
train	13–8	0.02	21%	8 Nov →
mirage	11–13	0.01	24%	7 Nov →
train	13–9	-0.04	46%	7 Nov →
dust2	13–8	0.01	20%	7 Nov →
dust2	13–3	0.08	16%	6 Nov →
mirage	11–13	0.03	32%	6 Nov →
ancient	15–15	0.04	34%	5 Nov →
anubis	13–4	0.00	16%	5 Nov →
inferno	7–13	-0.03	21%	5 Nov →
train	13–1	0.16	24%	5 Nov →
dust2	7–13	-0.02	26%	4 Nov →
overpass	11–13	-0.05	23%	3 Nov →
ancient	13–9	-0.08	25%	3 Nov →
train	13–3	0.05	34%	3 Nov →
ancient	13–9	0.04	31%	3 Nov →
ancient	13–4	0.06	32%	1 Nov →
nuke	15–15	-0.02	16%	1 Nov →
nuke	13–7	0.07	24%	1 Nov →