Swagrid — CS2 Stats

AU76561198169019261[U:1:208753533]Steam profile ↗✓ No bans

444Tracked matches33%Win rate2020Tracked since

1,346Hours in CS7Hrs last 2 wks

CSDB Rating4.2 Developing

Ladder ranks via Leetify

Performance scores

Aim51

Positioning39

Utility57

0–100 skill scores via Leetify.

Recent form

COLD40–56–4Last 10040%Win rateLLLLWLLLWW

Last 10 vs previous 10: -10pp win rate · -0.00 avg rating

Player DNA

Aim5.1

Aggression4.5

Utility5.7

Positioning3.9

Opening Duels0.2

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 84% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

Strengths

Flashes. 0.79 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 646ms 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

Aim5.1

Positioning3.9

Utility5.7

Mechanics6.5

Opening Duels0.2

Win Impact0.0

Composite 4.2/10 (Developing), 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-0.05−0.04

first ⅓ avg -0.01 → last ⅓ avg -0.05

Reaction time650ms−13ms

first ⅓ avg 663ms → last ⅓ avg 650ms

Headshot accuracy14.0%+1.0%

first ⅓ avg 13.0% → last ⅓ avg 14.0%

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

0.15Best rating — office 13–5

13–1Biggest win — ancient

4Longest win streak

L4Current streak

8–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

dust2Best map · 55% over 20infernoWeakest map · 31% over 16

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	24	9–15	38%	-0.03
dust2	A	20	11–9	55%	-0.03
inferno	D	16	5–11	31%	-0.05
nuke	C	11	4–7	36%	-0.03
anubis	C	10	4–6	40%	-0.02
ancient	B	6	3–3	50%	-0.02
train	—	4	0–4	0%	-0.05
cache	—	3	1–2	33%	-0.02
overpass	—	3	1–2	33%	-0.01
office	—	2	1–1	50%	0.03
vertigo	—	1	1–0	100%	-0.11

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (31% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

39,567Lifetime kills

0.82K/D

2,928Matches

32.2%Match win rate

32.7%Headshot %

15.9%Shot accuracy · Top 25% of tracked players

3,460MVPs

819Hours (in match)

1,747Bombs planted

315Bombs defused

Most-used weapons

AK-476,892

M4A4 / M4A1-S5,234

AWP4,611

Desert Eagle1,817

P2000 / USP-S1,694

Negev1,377

SSG 081,300

Glock-181,147

P901,064

UMP-45915

Lifetime map wins

5,735dust2

2,031inferno

694train

648nuke

602office

533vertigo

193cbble

125lake

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.

14.8%Headshot accuracy

31.9%Accuracy (enemy spotted)

34.9%Spray accuracy

79.4%Counter-strafing

10.7°Preaim

646msReaction time

29.8%T opening success

31.6%CT opening success

0.79Enemies flashed / flash

8.4%Flash assists

14.24HE damage / grenade

5.88Flashes / 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.

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 14.8475% — below the 15% mark we flag
Aim Training →
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 29.7817% — 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.

31% win rate across 16 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
ancient	7–13	-0.02	17%	26 Aug →
anubis	10–13	-0.01	10%	26 Aug →
nuke	7–13	-0.02	8%	26 Aug →
mirage	1–13	-0.05	9%	26 Aug →
dust2	16–12	-0.04	13%	24 Aug →
ancient	1–13	-0.11	15%	24 Aug →
dust2	8–13	-0.06	30%	24 Aug →
dust2	7–13	-0.09	26%	23 Aug →
cache	13–9	-0.03	14%	23 Aug →
mirage	13–2	-0.01	14%	23 Aug →
cache	5–13	-0.03	9%	22 Aug →
mirage	6–13	-0.02	15%	22 Aug →
train	11–13	-0.03	20%	13 Aug →
mirage	13–5	-0.04	21%	20 May →
vertigo	13–8	-0.11	19%	20 May →
cache	9–13	-0.01	11%	20 May →
inferno	11–1	-0.03	11%	13 Apr →
mirage	11–13	-0.06	16%	13 Apr →
mirage	13–2	0.05	17%	13 Apr →
dust2	6–13	-0.13	11%	13 Apr →
mirage	8–13	-0.02	23%	12 Apr →
nuke	13–9	-0.10	10%	12 Apr →
office	6–13	-0.10	9%	10 Apr →
mirage	6–13	-0.08	10%	9 Apr →
anubis	13–10	-0.11	5%	9 Apr →
mirage	9–13	-0.07	18%	3 Apr →
inferno	4–13	-0.03	9%	3 Apr →
mirage	4–13	-0.05	14%	3 Apr →
dust2	13–11	0.02	20%	30 Mar →
mirage	10–13	-0.08	16%	30 Mar →
nuke	11–13	-0.06	7%	30 Mar →
ancient	6–13	-0.03	6%	30 Mar →
mirage	2–13	-0.03	10%	27 Mar →
inferno	10–13	-0.10	14%	27 Mar →
dust2	13–5	0.01	3%	24 Mar →
dust2	13–5	-0.01	26%	24 Mar →
mirage	5–13	-0.05	12%	22 Mar →
inferno	6–13	-0.05	10%	22 Mar →
dust2	13–3	0.05	21%	20 Mar →
anubis	9–13	-0.05	11%	20 Mar →
nuke	13–3	-0.03	20%	20 Mar →
mirage	16–12	-0.02	13%	20 Mar →
inferno	6–13	-0.06	14%	10 Mar →
inferno	7–13	-0.04	15%	10 Mar →
train	11–13	-0.07	11%	9 Mar →
inferno	13–10	-0.07	5%	9 Mar →
anubis	13–11	0.01	21%	9 Mar →
train	7–13	-0.05	9%	9 Mar →
dust2	13–10	-0.03	12%	6 Mar →
inferno	15–15	-0.05	19%	6 Mar →
ancient	16–14	-0.06	4%	6 Mar →
nuke	6–13	-0.00	19%	1 Mar →
train	12–12	-0.04	10%	1 Mar →
overpass	10–13	-0.04	14%	27 Feb →
dust2	12–6	0.02	19%	27 Feb →
mirage	11–13	-0.03	7%	25 Feb →
inferno	6–13	-0.04	14%	25 Feb →
ancient	13–5	-0.01	6%	20 Feb →
mirage	9–13	-0.08	14%	20 Feb →
inferno	13–10	-0.06	18%	20 Feb →
dust2	13–7	-0.01	22%	20 Feb →
dust2	13–11	-0.05	14%	19 Feb →
anubis	13–8	0.01	20%	19 Feb →
dust2	1–13	-0.05	6%	21 Dec →
nuke	5–13	-0.09	10%	20 Dec →
mirage	12–12	-0.05	17%	20 Dec →
anubis	9–13	-0.04	16%	20 Dec →
inferno	10–13	-0.11	5%	18 Dec →
anubis	10–13	-0.06	8%	10 Dec →
anubis	13–4	0.11	13%	10 Dec →
dust2	10–13	0.00	13%	8 Dec →
nuke	9–13	-0.02	4%	8 Dec →
inferno	0–13	-0.07	5%	8 Dec →
nuke	7–13	-0.06	6%	8 Dec →
mirage	13–2	0.01	16%	8 Dec →
inferno	7–13	-0.04	16%	7 Dec →
dust2	13–11	-0.01	21%	7 Dec →
mirage	8–13	-0.05	14%	6 Dec →
inferno	11–3	-0.06	6%	6 Dec →
dust2	5–13	-0.05	16%	6 Dec →
dust2	11–13	-0.04	5%	2 Dec →
office	13–5	0.15	17%	2 Dec →
overpass	13–11	0.03	14%	2 Dec →
nuke	2–7	0.02	20%	25 Nov →
nuke	13–2	0.07	18%	25 Nov →
nuke	13–7	0.00	21%	24 Nov →
overpass	4–13	-0.02	22%	24 Nov →
inferno	13–3	0.03	18%	19 Nov →
mirage	13–11	-0.02	16%	16 Nov →
dust2	13–16	0.00	15%	15 Nov →
mirage	13–11	0.04	18%	10 Nov →
mirage	13–9	-0.03	18%	10 Nov →
inferno	7–13	-0.09	11%	27 Oct →
anubis	4–13	-0.05	6%	27 Oct →
mirage	10–13	-0.03	4%	17 Oct →
mirage	13–8	0.01	9%	17 Oct →
dust2	6–2	-0.03	13%	6 Oct →
anubis	12–12	-0.00	11%	6 Oct →
ancient	13–1	0.12	11%	6 Oct →
dust2	3–13	-0.06	21%	5 Oct →