Xialma — CS2 Stats

76561198308639946[U:1:348374218]Steam profile ↗✓ No bans

2,529Tracked matches18%Win rate2024Tracked since

1,949Hours in CS

CSDB Rating3.2 LearningSupport

CSDB Leaderboard#209137 of 259494 tracked

WingmanSilver III

Ladder ranks via Leetify

Rating over time

Premier CS Rating: 1,613 +543 23 Jun – 1 Jul · 6 days played

1,868Peak Premier in tracked matches

26Days played since 2026-06-23

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim32

Positioning32

Utility36

0–100 skill scores via Leetify.

Recent form

COLD32–64–4Last 10032%Win rateLLLLLLWLWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −2.1pp headshot accuracy · −74ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

0–5 · 0% win rate
Avg rating -0.06
Avg headshot accuracy 9%
Avg reaction 563ms

Last 10

3–7 · 30% win rate
Avg rating -0.04
Avg headshot accuracy 10%
Avg reaction 608ms

Last 20

4–16 · 20% win rate
Avg rating -0.04
Avg headshot accuracy 11%
Avg reaction 645ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim3.2

Utility3.6

Positioning3.2

Opening Duels0.3

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like ZywOo 76% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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. 661ms 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

Aim3.2

Positioning3.2

Utility3.6

Mechanics6.4

Opening Duels0.7

Win Impact0.0

Composite 3.2/10 (Learning), 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-0.04−0.02

first ⅓ avg -0.01 → last ⅓ avg -0.04

Reaction time656ms−2ms

first ⅓ avg 658ms → last ⅓ avg 656ms

Headshot accuracy12.4%−0.8%

first ⅓ avg 13.2% → last ⅓ avg 12.4%

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.

Personal bests

0.08Best match rating · 13–5 · ancient, 16 Jul →

29%Best headshot accuracy · 1–13 · dust2, 1 Jul →

453msFastest reaction time · 13–11 · ancient, 1 Jul →

13–3Biggest win · nuke, 17 Jul →

Across the last 100 tracked matches.

Highlights

3Longest win streak

L6Current streak

4–7In matches decided by ≤2 rounds

6Overtime games

Map breakdown

nukeBest map · 67% over 9infernoWeakest map · 13% over 8

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	31	7–24	23%	-0.03
mirage	C	16	6–10	38%	-0.03
nuke	S	9	6–3	67%	-0.02
anubis	C	9	4–5	44%	-0.02
inferno	D	8	1–7	13%	-0.05
ancient	C	8	3–5	38%	-0.01
cache	C	5	2–3	40%	-0.04
shelter	—	3	1–2	33%	-0.06
italy	—	3	0–3	0%	-0.08
fachwerk	—	2	0–2	0%	-0.08
train	—	2	0–2	0%	-0.03
eldorado	—	1	1–0	100%	0.08
overpass	—	1	0–1	0%	-0.07
boulder	—	1	0–1	0%	-0.09
office	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

84,677Lifetime kills

0.80K/D

6,774Matches

27.5%Match win rate

30.2%Headshot %

0.0%Shot accuracy

4,727MVPs

1,949Hours (in match)

3,482Bombs planted

421Bombs defused

Most-used weapons

AK-4717,043

M4A4 / M4A1-S12,293

AWP9,558

MAC-104,340

P904,036

MP73,905

Galil AR3,574

P2000 / USP-S2,906

SG 5532,487

SCAR-202,473

Lifetime map wins

14,708dust2

6,509inferno

2,935nuke

1,214vertigo

856train

791office

394italy

348ar_shoots

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.

12.5%Headshot accuracy

28.4%Accuracy (enemy spotted)

30.1%Spray accuracy

78.6%Counter-strafing

12.1°Preaim

661msReaction time

25.3%T opening success

35.6%CT opening success

0.48Enemies flashed / flash

2.3%Flash assists

3.89HE damage / grenade

7.87Flashes / 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 12.1158° — 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 12.4756% — below the 15% mark we flag
Aim Training →
Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4792 — below the 0.5 mark we flag
Grenade Lineups →

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.

13% win rate across 8 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
dust2	6–13	0.01	11%	31 Aug →
fachwerk	4–13	-0.04	8%	31 Aug →
shelter	7–13	-0.05	7%	31 Aug →
dust2	11–13	-0.06	9%	21 Aug →
italy	4–13	-0.14	11%	21 Aug →
dust2	7–13	-0.05	13%	15 Aug →
nuke	13–9	0.00	6%	15 Aug →
mirage	6–13	-0.08	11%	15 Aug →
eldorado	9–3	0.08	8%	15 Aug →
anubis	13–7	-0.03	20%	2 Aug →
dust2	10–13	-0.02	17%	2 Aug →
nuke	5–13	-0.05	10%	2 Aug →
overpass	11–13	-0.07	13%	2 Aug →
mirage	13–6	-0.06	11%	2 Aug →
train	3–13	-0.03	14%	2 Aug →
nuke	7–13	-0.06	18%	23 Jul →
cache	11–13	-0.06	9%	23 Jul →
inferno	8–13	-0.09	2%	23 Jul →
ancient	8–13	-0.01	15%	23 Jul →
dust2	8–13	-0.02	15%	22 Jul →
dust2	10–13	-0.05	20%	22 Jul →
dust2	3–13	-0.08	13%	22 Jul →
dust2	8–13	-0.00	16%	21 Jul →
mirage	8–13	0.01	11%	21 Jul →
dust2	15–15	-0.03	9%	21 Jul →
ancient	11–13	-0.05	16%	20 Jul →
dust2	1–13	-0.04	16%	20 Jul →
anubis	3–13	-0.07	21%	20 Jul →
dust2	16–13	-0.01	10%	20 Jul →
dust2	15–15	-0.04	11%	17 Jul →
nuke	13–7	-0.05	15%	17 Jul →
nuke	13–3	-0.04	3%	17 Jul →
mirage	11–13	-0.03	19%	17 Jul →
ancient	13–5	0.08	6%	16 Jul →
dust2	9–13	-0.04	11%	16 Jul →
mirage	4–13	-0.01	18%	16 Jul →
mirage	10–13	-0.04	7%	15 Jul →
inferno	4–13	-0.03	7%	15 Jul →
dust2	5–13	-0.02	13%	14 Jul →
inferno	7–13	-0.04	6%	14 Jul →
dust2	13–7	-0.00	6%	14 Jul →
dust2	6–13	-0.03	6%	14 Jul →
mirage	3–13	-0.04	14%	14 Jul →
anubis	3–13	-0.10	13%	14 Jul →
anubis	4–13	0.04	12%	13 Jul →
inferno	7–13	-0.08	27%	13 Jul →
inferno	8–13	-0.11	15%	12 Jul →
cache	13–9	0.00	14%	12 Jul →
dust2	6–13	-0.10	16%	12 Jul →
shelter	13–11	-0.06	6%	10 Jul →
fachwerk	5–13	-0.11	5%	10 Jul →
boulder	7–13	-0.09	10%	10 Jul →
dust2	10–13	-0.04	19%	10 Jul →
cache	14–16	-0.04	11%	10 Jul →
shelter	0–13	-0.08	8%	9 Jul →
dust2	13–8	-0.00	10%	9 Jul →
mirage	13–9	-0.01	16%	9 Jul →
anubis	6–13	0.06	9%	9 Jul →
mirage	13–8	-0.02	13%	9 Jul →
dust2	13–8	-0.00	17%	4 Jul →
ancient	1–7	-0.02	22%	4 Jul →
mirage	13–4	-0.01	8%	4 Jul →
mirage	12–12	-0.07	9%	4 Jul →
cache	6–13	-0.09	0%	3 Jul →
anubis	13–8	-0.05	22%	1 Jul →
dust2	1–13	-0.07	29%	1 Jul →
ancient	13–11	-0.09	4%	1 Jul →
mirage	13–4	0.02	11%	30 Jun →
dust2	2–13	-0.04	21%	30 Jun →
dust2	11–13	-0.03	28%	30 Jun →
dust2	10–13	-0.02	17%	30 Jun →
anubis	13–3	0.02	8%	30 Jun →
dust2	9–13	-0.03	12%	29 Jun →
italy	5–13	-0.04	9%	29 Jun →
mirage	8–13	-0.04	15%	29 Jun →
nuke	13–5	0.00	17%	29 Jun →
inferno	8–13	0.03	13%	29 Jun →
italy	7–13	-0.08	20%	28 Jun →
nuke	13–5	0.05	7%	28 Jun →
office	13–10	0.02	8%	28 Jun →
cache	13–6	-0.01	7%	28 Jun →
ancient	9–13	0.01	17%	28 Jun →
ancient	9–13	-0.06	11%	28 Jun →
anubis	13–10	-0.01	11%	26 Jun →
mirage	13–10	0.03	14%	26 Jun →
dust2	16–12	-0.00	13%	26 Jun →
train	9–13	-0.03	11%	25 Jun →
dust2	12–12	-0.02	13%	25 Jun →
mirage	4–13	-0.00	10%	25 Jun →
dust2	13–4	-0.02	26%	24 Jun →
dust2	9–13	-0.05	8%	24 Jun →
ancient	13–11	0.02	16%	24 Jun →
inferno	16–14	-0.01	18%	24 Jun →
nuke	13–10	-0.02	3%	24 Jun →
mirage	8–13	-0.08	15%	24 Jun →
dust2	11–5	0.04	11%	24 Jun →
dust2	9–13	0.02	15%	24 Jun →
anubis	6–13	-0.06	13%	23 Jun →
inferno	6–13	-0.08	6%	23 Jun →
nuke	9–13	-0.03	12%	23 Jun →