Annikajulia_ — CS2 Stats

FI76561199806106903[U:1:1845841175]Steam profile ↗✓ No bans

1,152Tracked matches50%Win rate2025Tracked since

1,088Hours in CS6Hrs last 2 wks

CSDB Rating2.5 LearningClutch Specialist

Ladder ranks via Leetify

Performance scores

Aim16

Positioning27

Utility47

0–100 skill scores via Leetify.

Recent form

HOT39–49–12Last 10039%Win rateLWWWWWWWLW

Last 10 vs previous 10: +60pp win rate · +0.02 avg rating · +1.6pp headshot accuracy · −35ms reaction

Win rate up 60pp 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

4–1 · 80% win rate
Avg rating -0.04
Avg headshot accuracy 16%
Avg reaction 681ms

Last 10

8–2 · 80% win rate
Avg rating -0.04
Avg headshot accuracy 15%
Avg reaction 673ms

Last 20

10–10 · 50% win rate
Avg rating -0.05
Avg headshot accuracy 14%
Avg reaction 690ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+5.7 against its own average).

Aim1.6

Utility4.7

Positioning2.7

Opening Duels0.0

Clutch10.0

Effective flashesLimited utility dependenceReliable in 1v1s

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 Twistzz 61% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 680ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 59% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim1.6

Positioning2.7

Utility4.7

Mechanics2.0

Opening Duels0.0

Win Impact5.0

Composite 2.5/10 (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-0.05−0.01

first ⅓ avg -0.04 → last ⅓ avg -0.05

Reaction time680ms+24ms

first ⅓ avg 657ms → last ⅓ avg 680ms

Headshot accuracy15.2%−3.1%

first ⅓ avg 18.3% → last ⅓ avg 15.2%

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

0.09Best match rating · 13–4 · inferno, 1 Oct →

39%Best headshot accuracy · 13–10 · anubis, 28 Sept →

484msFastest reaction time · 12–1 · nuke, 28 Sept →

13–0Biggest win · nuke, 16 Sept →

Across the last 100 tracked matches.

Highlights

7Longest win streak

4–4In matches decided by ≤2 rounds

Map breakdown

anubisBest map · 67% over 6ancientWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
nuke	C	17	7–10	41%	-0.04
mirage	C	16	7–9	44%	-0.05
inferno	D	10	3–7	30%	-0.04
dust2	C	10	4–6	40%	-0.03
vertigo	C	9	4–5	44%	-0.02
train	C	9	4–5	44%	-0.06
overpass	D	7	2–5	29%	-0.02
cache	D	6	2–4	33%	-0.05
ancient	D	6	1–5	17%	-0.05
anubis	S	6	4–2	67%	-0.02
office	—	4	1–3	25%	-0.03

Across the last 100 tracked matches.

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

Lifetime stats

15,560Lifetime kills

0.64K/D

1,491Matches

44.1%Match win rate

46.1%Headshot % · Top 50% of tracked players

0.0%Shot accuracy

1,185MVPs

507Hours (in match)

653Bombs planted

125Bombs defused

Most-used weapons

Galil AR4,050

M4A4 / M4A1-S3,814

AK-472,029

MP91,132

AUG811

FAMAS765

P2000 / USP-S678

Tec-9592

MAC-10379

Desert Eagle344

Lifetime map wins

1,553dust2

1,464inferno

1,376nuke

1,134train

973vertigo

357office

87italy

12lake

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

Faceit stats

Combat

1Matches

0%Win rate

0.93Avg K/D

67.1ADR

38%Headshot %

Clutches & streaks

100%1v1 clutch win

100%1v2 clutch win

0Longest win streak

Recent Faceit resultsLLLLL

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.

14.2%Headshot accuracy

29.2%Accuracy (enemy spotted)

30.1%Spray accuracy

59.1%Counter-strafing

14.3°Preaim

680msReaction time

24.6%T opening success

21.1%CT opening success

0.73Enemies flashed / flash

0.3%Flash assists

5.83HE damage / grenade

4.64Flashes / 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 14.2648° — 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 14.163% — below the 15% mark we flag
Aim Training →

Spend your practice time on Ancient

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.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	8–13	-0.07	12%	23 Oct →
mirage	12–2	-0.03	10%	23 Oct →
cache	13–3	-0.07	16%	23 Oct →
nuke	13–7	-0.02	17%	23 Oct →
vertigo	13–10	-0.01	26%	22 Oct →
mirage	13–10	-0.11	13%	22 Oct →
train	13–7	0.01	14%	21 Oct →
nuke	13–8	-0.04	16%	21 Oct →
office	6–13	-0.09	15%	17 Oct →
vertigo	13–11	-0.01	14%	16 Oct →
mirage	3–13	-0.05	5%	16 Oct →
ancient	1–13	-0.01	4%	16 Oct →
nuke	6–13	-0.07	13%	16 Oct →
mirage	8–13	-0.11	26%	16 Oct →
anubis	9–13	-0.06	13%	16 Oct →
train	13–7	-0.06	13%	16 Oct →
inferno	7–9	-0.16	16%	16 Oct →
overpass	2–6	0.02	33%	16 Oct →
mirage	3–13	-0.11	8%	11 Oct →
overpass	13–3	-0.01	5%	10 Oct →
nuke	12–12	-0.04	24%	10 Oct →
train	7–13	-0.04	18%	10 Oct →
ancient	8–13	-0.06	10%	10 Oct →
inferno	12–12	-0.02	12%	10 Oct →
mirage	13–3	-0.06	3%	10 Oct →
overpass	8–13	-0.08	14%	8 Oct →
vertigo	11–13	-0.03	9%	7 Oct →
ancient	12–12	-0.07	5%	5 Oct →
dust2	13–11	-0.01	16%	5 Oct →
cache	13–9	-0.01	17%	3 Oct →
vertigo	12–12	-0.02	22%	2 Oct →
dust2	0–13	-0.04	33%	2 Oct →
office	10–13	-0.04	29%	2 Oct →
nuke	13–6	-0.02	19%	2 Oct →
train	9–13	-0.04	20%	2 Oct →
mirage	1–13	-0.10	24%	2 Oct →
anubis	13–10	0.03	21%	2 Oct →
dust2	13–4	-0.00	14%	1 Oct →
nuke	4–13	-0.02	17%	1 Oct →
inferno	13–4	0.09	18%	1 Oct →
mirage	13–10	-0.03	14%	1 Oct →
cache	7–13	-0.01	33%	1 Oct →
anubis	13–3	0.05	17%	1 Oct →
dust2	6–13	-0.03	12%	1 Oct →
inferno	4–13	-0.01	31%	1 Oct →
nuke	2–13	-0.12	24%	30 Sept →
anubis	8–13	-0.05	20%	30 Sept →
train	6–13	-0.10	38%	29 Sept →
nuke	13–6	-0.08	11%	29 Sept →
mirage	13–2	-0.00	20%	29 Sept →
cache	12–12	-0.06	18%	28 Sept →
mirage	6–13	-0.06	12%	28 Sept →
office	13–10	0.02	11%	28 Sept →
inferno	13–5	-0.05	22%	28 Sept →
vertigo	13–5	0.01	16%	28 Sept →
anubis	13–10	-0.11	39%	28 Sept →
overpass	12–12	-0.02	24%	28 Sept →
nuke	12–1	0.04	10%	28 Sept →
anubis	13–5	0.05	16%	27 Sept →
train	11–13	-0.05	20%	27 Sept →
dust2	13–1	-0.06	7%	27 Sept →
cache	7–13	-0.10	8%	27 Sept →
overpass	8–13	-0.04	12%	27 Sept →
inferno	12–12	-0.03	6%	27 Sept →
mirage	7–13	-0.05	17%	27 Sept →
inferno	9–13	-0.06	5%	25 Sept →
dust2	10–13	-0.00	9%	25 Sept →
nuke	4–13	-0.00	22%	25 Sept →
nuke	9–13	-0.07	16%	24 Sept →
train	13–11	-0.12	11%	24 Sept →
vertigo	13–5	0.03	23%	23 Sept →
mirage	13–6	-0.04	11%	22 Sept →
overpass	9–13	-0.04	19%	21 Sept →
nuke	8–13	-0.08	18%	21 Sept →
ancient	13–8	-0.09	7%	21 Sept →
mirage	10–13	-0.05	11%	21 Sept →
dust2	9–13	-0.01	29%	20 Sept →
nuke	13–11	-0.04	22%	20 Sept →
vertigo	12–12	-0.05	25%	20 Sept →
dust2	11–13	-0.07	14%	19 Sept →
mirage	13–9	-0.01	20%	19 Sept →
nuke	12–12	-0.05	15%	19 Sept →
ancient	12–12	-0.00	18%	19 Sept →
dust2	10–13	0.01	32%	19 Sept →
cache	12–12	-0.08	16%	19 Sept →
ancient	10–13	-0.08	24%	18 Sept →
nuke	8–13	-0.05	26%	18 Sept →
train	2–13	-0.07	19%	18 Sept →
office	4–13	-0.00	25%	18 Sept →
mirage	6–13	-0.06	8%	18 Sept →
nuke	4–13	-0.07	27%	18 Sept →
dust2	13–9	-0.05	18%	18 Sept →
inferno	13–8	-0.06	11%	18 Sept →
overpass	13–4	0.02	15%	16 Sept →
vertigo	5–13	-0.01	24%	16 Sept →
inferno	12–12	0.01	16%	16 Sept →
nuke	13–0	0.04	22%	16 Sept →
mirage	9–13	-0.00	20%	16 Sept →
vertigo	5–13	-0.08	10%	16 Sept →
train	9–5	-0.06	8%	15 Sept →