Duszyn Poirier — CS2 Stats

76561198846478107[U:1:886212379]

1,279Tracked matches46%Win rate2020Tracked since

CSDB Rating3.9 Learning

Premier CS Rating1,357Grey band · top ~94.2% of ranked players (population est.)

FaceitLevel 2Top 97.9% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim50

Positioning37

Utility57

0–100 skill scores via Leetify.

Recent form

STEADY47–49–4Last 10047%Win rateLLWLWWWTWW

Last 10 vs previous 10: +20pp win rate · -0.01 avg rating

Player DNA

Aim5.0

Aggression3.0

Utility5.7

Positioning3.7

Opening Duels0.0

Clutch1.0

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 NiKo 78% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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

Reaction time. 755ms 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

Aim5.0

Positioning3.7

Utility5.7

Mechanics5.8

Opening Duels0.0

Win Impact3.8

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time746ms+72ms

first ⅓ avg 674ms → last ⅓ avg 746ms

Headshot accuracy13.8%−0.4%

first ⅓ avg 14.2% → last ⅓ avg 13.8%

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

0.10Best rating — inferno 13–2

13–0Biggest win — dust2

9Longest win streak

L2Current streak

7–7In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 67% over 27nukeWeakest map · 0% over 7

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	27	18–9	67%	-0.01
ancient	B	21	10–11	48%	-0.02
dust2	B	18	9–9	50%	-0.03
mirage	D	16	4–12	25%	-0.02
anubis	A	7	4–3	57%	-0.03
nuke	D	7	0–7	0%	-0.02
cache	—	3	1–2	33%	0.03
overpass	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (0% over 7). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

43Matches

35%Win rate

0.72Avg K/D

59.9ADR

32%Headshot %

Clutches & streaks

25%1v1 clutch win

7%1v2 clutch win

2Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	5	60%	0.96	12.0
Mirage	4	25%	0.74	11.8
Ancient	3	33%	0.70	8.3
Inferno	2	0%	0.78	13.5
Nuke	1	0%	0.27	4.0
Vertigo	1	100%	1.00	16.0
Anubis	1	0%	0.68	13.0

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.

14.0%Headshot accuracy

41.2%Accuracy (enemy spotted)

38.5%Spray accuracy

76.2%Counter-strafing

12.0°Preaim

755msReaction time

23.9%T opening success

26.2%CT opening success

0.48Enemies flashed / flash

6.2%Flash assists

9.39HE damage / grenade

12.88Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.0126° — above the 12° mark we flag
Aim Training →
Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.9981% — below the 15% mark we flag
Aim Training →
Best CS2 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 754.5365ms — above the 700ms mark we flag
Aim Training →

Spend your practice time on Nuke

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

0% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	6–13	-0.00	9%	11 Aug →
mirage	7–13	-0.08	17%	8 Aug →
inferno	13–11	0.02	16%	3 Aug →
dust2	10–13	-0.02	24%	2 Aug →
inferno	13–11	-0.05	12%	30 Jul →
dust2	13–11	-0.02	17%	30 Jul →
anubis	13–9	0.03	14%	30 Jul →
mirage	15–15	-0.01	12%	26 Jul →
dust2	13–8	0.03	12%	26 Jul →
dust2	13–9	-0.04	11%	26 Jul →
dust2	11–13	-0.03	11%	26 Jul →
inferno	13–6	-0.04	10%	26 Jul →
ancient	8–13	-0.04	7%	21 Jul →
inferno	4–13	-0.06	14%	20 Jul →
inferno	13–4	-0.02	17%	19 Jul →
cache	11–13	-0.01	12%	18 Jul →
nuke	1–5	0.07	17%	18 Jul →
inferno	6–13	0.10	11%	18 Jul →
dust2	13–11	-0.06	10%	17 Jul →
ancient	13–5	0.05	21%	14 Jul →
mirage	4–13	-0.06	9%	13 Jul →
cache	5–13	0.07	9%	8 Jul →
inferno	8–13	-0.01	13%	8 Jul →
cache	13–9	0.03	28%	6 Jul →
nuke	7–13	-0.06	20%	6 Jul →
inferno	13–9	-0.07	15%	5 Jul →
inferno	9–13	0.04	12%	5 Jul →
ancient	10–13	-0.09	12%	5 Jul →
ancient	15–15	-0.07	17%	5 Jul →
ancient	13–6	0.02	14%	3 Jul →
inferno	13–8	-0.02	15%	30 Jun →
anubis	11–13	-0.01	9%	27 Jun →
ancient	8–13	-0.03	10%	24 Jun →
mirage	9–13	-0.05	8%	22 Jun →
anubis	8–13	-0.13	3%	20 Jun →
nuke	5–13	-0.03	6%	20 Jun →
inferno	13–2	0.10	13%	20 Jun →
dust2	10–13	0.02	30%	20 Jun →
inferno	13–9	0.03	17%	17 Jun →
ancient	4–13	-0.09	25%	14 Jun →
inferno	5–13	0.01	18%	14 Jun →
inferno	13–8	-0.07	5%	14 Jun →
nuke	9–13	0.00	18%	13 Jun →
dust2	13–11	-0.02	11%	13 Jun →
mirage	8–13	-0.03	13%	12 Jun →
ancient	6–13	-0.09	13%	10 Jun →
inferno	10–13	0.04	20%	9 Jun →
nuke	9–13	-0.05	14%	9 Jun →
inferno	11–13	-0.01	8%	8 Jun →
mirage	10–13	-0.03	17%	8 Jun →
ancient	13–8	-0.06	7%	6 Jun →
nuke	15–15	-0.03	8%	6 Jun →
nuke	11–13	-0.03	8%	6 Jun →
mirage	8–13	-0.05	9%	4 Jun →
inferno	13–1	-0.01	14%	4 Jun →
inferno	9–13	-0.04	19%	2 Jun →
mirage	13–10	0.02	4%	2 Jun →
ancient	5–13	-0.04	10%	30 May →
dust2	3–13	-0.02	11%	30 May →
ancient	13–10	0.02	16%	30 May →
dust2	13–0	0.02	11%	30 May →
mirage	7–13	-0.06	15%	28 May →
ancient	13–4	-0.03	14%	27 May →
inferno	13–5	-0.03	9%	27 May →
mirage	15–15	0.06	14%	26 May →
mirage	6–13	-0.03	17%	25 May →
anubis	13–10	-0.04	18%	25 May →
dust2	7–13	-0.09	27%	25 May →
dust2	7–13	-0.03	22%	25 May →
anubis	16–14	-0.02	6%	24 May →
dust2	6–13	-0.08	17%	24 May →
ancient	13–4	0.04	9%	24 May →
anubis	9–13	-0.02	23%	23 May →
inferno	13–6	-0.02	11%	21 May →
inferno	16–13	-0.04	9%	20 May →
ancient	13–9	0.02	10%	20 May →
mirage	7–13	-0.05	3%	18 May →
mirage	11–13	-0.01	13%	17 May →
dust2	13–3	0.03	21%	17 May →
ancient	13–10	-0.06	15%	17 May →
ancient	10–13	0.04	13%	17 May →
inferno	9–13	-0.03	23%	16 May →
mirage	13–7	0.03	19%	16 May →
inferno	13–9	-0.02	7%	16 May →
overpass	13–9	0.03	12%	16 May →
dust2	13–7	-0.07	19%	16 May →
inferno	13–9	-0.04	10%	15 May →
inferno	13–3	0.04	27%	15 May →
dust2	13–9	-0.08	7%	14 May →
mirage	13–7	0.03	14%	13 May →
ancient	16–13	0.06	12%	13 May →
ancient	9–13	-0.13	5%	11 May →
inferno	13–10	-0.00	18%	11 May →
mirage	13–11	0.04	11%	10 May →
dust2	13–16	-0.03	16%	10 May →
anubis	13–4	-0.00	17%	10 May →
inferno	13–6	0.03	14%	10 May →
dust2	11–13	-0.05	19%	4 May →
ancient	13–2	0.05	10%	4 May →
ancient	9–13	0.04	8%	3 May →