GroBoulard — CS2 Stats

FR76561199108965387[U:1:1148699659]Steam profile ↗✓ No bans

1,949Tracked matches56%Win rate2020Tracked since

2,288Hours in CS6Hrs last 2 wks

CSDB Rating8.0 StrongAggressive Rifler

Premier CS Rating24,363Top 25% of 44,590 CSDB-tracked playersPink band · top ~3.7% of ranked players (population est.)

CSDB Leaderboard#8853 of 58972 tracked

FaceitLevel 10 · 2,316 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=7,415), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	65.6%	51.7%
Shot accuracy	7.5%	13.8%
Kill/death ratio	1.53	1.09
Match win rate	53.8%	48.7%

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Performance scores

Aim94

Positioning70

Utility67

0–100 skill scores via Leetify.

Recent form

STEADY43–48–9Last 10043%Win rateLLTWLLWWWT

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.

Aim9.4

Aggression10.0

Utility6.7

Positioning7.0

Opening Duels5.5

Clutch3.4

Sharp aimerExcellent counter-strafingStrong CT-side openerEffective flashes

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 ZywOo 97% playstyle similarity

Most alike: opening-fight frequency, positioning 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

Aim. Aim score of 94 — the mechanical foundation is a clear strength.

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

CT openings. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Flashes. 0.84 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 64% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 615ms 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

Aim9.4

Positioning7.0

Utility6.7

Mechanics9.2

Opening Duels5.5

Win Impact6.9

Composite 8.0/10 (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 rating0.05+0.00

first ⅓ avg 0.05 → last ⅓ avg 0.05

Reaction time617ms+58ms

first ⅓ avg 560ms → last ⅓ avg 617ms

Headshot accuracy32.9%+5.7%

first ⅓ avg 27.2% → last ⅓ avg 32.9%

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

0.23Best rating — dust2 13–4

13–1Biggest win — train

3Longest win streak

L2Current streak

4–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

vertigoBest map · 60% over 5infernoWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	29	14–15	48%	0.04
mirage	C	19	8–11	42%	0.04
cache	C	15	6–9	40%	0.04
train	A	11	6–5	55%	0.07
nuke	C	7	3–4	43%	0.06
inferno	D	6	1–5	17%	0.04
vertigo	A	5	3–2	60%	0.06
anubis	—	4	1–3	25%	-0.00
overpass	—	3	1–2	33%	0.07
ancient	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

113,416Lifetime kills

1.53K/D · Top 10% of Level 10 players

2,835Matches

53.8%Match win rate · Top 25% of Level 10 players

65.6%Headshot % · Top 10% of Level 10 players

7.5%Shot accuracy

9,652MVPs

2,426Hours (in match)

2,701Bombs planted

1,058Bombs defused

Most-used weapons

AK-4767,612

M4A4 / M4A1-S11,399

AWP10,868

Desert Eagle6,849

P2000 / USP-S5,204

Glock-182,420

Galil AR1,531

SSG 081,460

FAMAS1,250

Knife1,016

Lifetime map wins

7,000dust2

4,088inferno

1,923train

1,592nuke

1,513vertigo

105cbble

41lake

3office

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

Faceit stats

Combat

1,055Matches

52%Win rate

1.26Avg K/D

87.0ADR

49%Headshot %

Clutches & streaks

37%1v1 clutch win

25%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	235	54%	1.38	19.1
Mirage	179	46%	1.20	18.4
Inferno	103	49%	1.24	18.0
Anubis	63	54%	1.28	18.5
Overpass	56	50%	1.29	18.3
Nuke	45	53%	1.31	18.0
Train	38	55%	1.54	21.6
Ancient	20	45%	1.15	17.3

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.

32.6%Headshot accuracy

38.4%Accuracy (enemy spotted)

41.4%Spray accuracy

91.4%Counter-strafing

7.8°Preaim

615msReaction time

40.5%T opening success

63.7%CT opening success

0.84Enemies flashed / flash

12.3%Flash assists

12.20HE damage / grenade

13.40Flashes / match

Recommended for you

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.

17% win rate across 6 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
anubis	10–13	0.04	26%	28 Aug →
inferno	11–13	0.01	27%	28 Aug →
overpass	12–12	0.09	24%	26 Aug →
dust2	13–5	0.10	43%	26 Aug →
mirage	13–16	0.09	31%	17 Aug →
dust2	10–13	0.10	34%	16 Aug →
dust2	13–6	0.14	32%	16 Aug →
mirage	13–5	0.15	30%	16 Aug →
dust2	16–12	0.04	25%	15 Aug →
dust2	12–12	0.00	19%	14 Aug →
dust2	3–13	-0.00	33%	13 Aug →
cache	13–4	-0.02	38%	13 Aug →
train	4–13	0.04	32%	12 Aug →
dust2	9–13	0.05	27%	12 Aug →
train	13–4	0.06	44%	12 Aug →
dust2	2–13	-0.01	29%	8 Aug →
cache	13–7	0.14	46%	8 Aug →
nuke	13–6	0.13	24%	6 Aug →
train	9–13	0.05	43%	6 Aug →
train	13–3	0.03	21%	4 Aug →
dust2	13–11	0.09	39%	4 Aug →
cache	12–12	0.06	30%	4 Aug →
mirage	9–13	0.14	36%	3 Aug →
vertigo	13–7	0.17	28%	3 Aug →
dust2	4–13	-0.04	54%	31 Jul →
train	13–1	0.10	44%	29 Jul →
mirage	13–8	-0.05	36%	29 Jul →
nuke	9–13	0.03	33%	29 Jul →
train	13–6	0.01	39%	28 Jul →
vertigo	13–3	0.07	33%	28 Jul →
cache	4–13	0.01	20%	28 Jul →
cache	8–13	-0.04	39%	27 Jul →
mirage	12–12	-0.01	23%	27 Jul →
dust2	10–13	-0.02	21%	27 Jul →
overpass	13–10	0.10	33%	26 Jul →
train	13–2	0.10	46%	26 Jul →
anubis	4–13	-0.03	35%	25 Jul →
vertigo	7–13	0.02	20%	25 Jul →
inferno	7–13	0.03	64%	25 Jul →
cache	2–13	0.02	41%	25 Jul →
cache	7–13	-0.01	43%	25 Jul →
cache	13–5	-0.03	19%	22 Jul →
mirage	6–11	0.00	18%	22 Jul →
cache	13–9	0.01	52%	22 Jul →
dust2	13–7	0.07	44%	22 Jul →
mirage	13–10	-0.01	36%	22 Jul →
mirage	12–12	-0.03	31%	21 Jul →
nuke	8–13	0.05	30%	21 Jul →
cache	1–7	0.01	32%	20 Jul →
nuke	13–4	0.06	42%	20 Jul →
dust2	15–15	0.04	30%	18 Jul →
dust2	13–4	0.23	17%	18 Jul →
overpass	11–13	0.02	22%	18 Jul →
cache	7–13	0.12	23%	17 Jul →
dust2	10–13	0.10	21%	17 Jul →
mirage	13–9	0.09	31%	16 Jul →
vertigo	10–13	-0.00	28%	16 Jul →
dust2	1–13	-0.10	0%	16 Jul →
anubis	11–13	-0.01	29%	16 Jul →
mirage	4–13	0.04	36%	16 Jul →
anubis	16–14	-0.02	27%	16 Jul →
nuke	10–13	0.03	35%	16 Jul →
dust2	13–3	-0.02	30%	16 Jul →
mirage	5–13	-0.03	36%	15 Jul →
dust2	13–11	0.04	26%	13 Jul →
train	12–12	0.06	43%	13 Jul →
cache	1–13	-0.01	33%	13 Jul →
dust2	13–5	0.17	26%	13 Jul →
inferno	9–13	0.10	35%	13 Jul →
train	11–13	0.01	35%	11 Jul →
mirage	5–13	-0.05	37%	11 Jul →
mirage	7–13	0.10	36%	11 Jul →
cache	13–3	0.12	45%	11 Jul →
dust2	9–13	0.02	36%	11 Jul →
cache	13–5	0.12	25%	11 Jul →
nuke	13–1	0.16	28%	11 Jul →
mirage	7–13	0.10	29%	11 Jul →
train	8–13	0.14	32%	11 Jul →
dust2	13–7	0.08	26%	11 Jul →
dust2	13–4	0.03	28%	10 Jul →
mirage	13–10	-0.00	17%	10 Jul →
inferno	8–13	0.03	26%	10 Jul →
mirage	13–8	0.06	29%	8 Jul →
vertigo	13–5	0.04	33%	8 Jul →
train	13–8	0.19	39%	8 Jul →
dust2	12–12	0.02	22%	8 Jul →
cache	11–13	0.13	29%	8 Jul →
inferno	0–7	0.00	0%	6 Jul →
dust2	7–13	-0.04	12%	6 Jul →
dust2	8–13	-0.01	45%	5 Jul →
dust2	15–15	0.04	31%	5 Jul →
inferno	13–11	0.04	26%	4 Jul →
dust2	13–9	0.03	24%	4 Jul →
dust2	13–6	0.07	8%	3 Jul →
mirage	11–13	-0.00	31%	3 Jul →
ancient	6–13	-0.02	14%	3 Jul →
dust2	13–3	0.03	26%	3 Jul →
mirage	13–7	-0.01	16%	3 Jul →
nuke	3–13	-0.02	23%	2 Jul →
mirage	13–7	0.08	27%	2 Jul →