Kondis — CS2 Stats

76561197997762233[U:1:37496505]✓ No bans

2,036Tracked matches62%Win rate2020Tracked since

CSDB Rating6.1 SolidPassive Rifler

Premier CS Rating18,569Purple band · top ~14.2% of ranked players (population est.)

FaceitLevel 8 · 1,642 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim81

Positioning45

Utility50

0–100 skill scores via Leetify.

Recent form

STEADY56–40–4Last 10056%Win rateWLWLWLWWWT

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

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim8.1

Aggression4.2

Utility5.0

Positioning4.5

Opening Duels0.8

Clutch3.2

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 88% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower 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

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.4° off target when enemies appear — placement, not flicking, is the bigger win available.

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim8.1

Positioning4.5

Utility5.0

Mechanics6.9

Opening Duels1.2

Win Impact9.0

Composite 6.1/10 (Solid), 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 rating0.02−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time540ms−32ms

first ⅓ avg 572ms → last ⅓ avg 540ms

Headshot accuracy12.3%−2.7%

first ⅓ avg 15.0% → last ⅓ avg 12.3%

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

0.21Best rating — inferno 13–3

13–1Biggest win — anubis

6Longest win streak

6–11In matches decided by ≤2 rounds

13Overtime games

Map breakdown

ancientBest map · 78% over 9vertigoWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
anubis	S	19	13–6	68%	0.01
nuke	C	17	7–10	41%	0.01
inferno	B	17	8–9	47%	0.02
mirage	B	13	7–6	54%	0.02
dust2	S	12	9–3	75%	0.03
ancient	S	9	7–2	78%	0.01
vertigo	D	6	2–4	33%	0.04
overpass	—	4	1–3	25%	-0.01
train	—	3	2–1	67%	-0.00

Across the last 100 tracked matches.

Vertigo is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Vertigo lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,535Matches

50%Win rate

1.11Avg K/D

77.1ADR

35%Headshot %

Clutches & streaks

36%1v1 clutch win

17%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	29	45%	1.15	16.4
Anubis	28	54%	1.45	15.8
Nuke	22	64%	1.08	14.9
Mirage	18	39%	0.91	15.6
Ancient	18	22%	0.90	14.2
Dust2	8	50%	0.95	15.1
Vertigo	8	50%	1.30	17.0
Train	7	43%	1.10	16.0

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.

12.1%Headshot accuracy

41.9%Accuracy (enemy spotted)

45.7%Spray accuracy

81.0%Counter-strafing

10.4°Preaim

540msReaction time

26.8%T opening success

39.3%CT opening success

0.55Enemies flashed / flash

5.8%Flash assists

11.61HE damage / grenade

5.64Flashes / 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.

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 12.147% — 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 26.8288% — below the 40% mark we flag

Spend your practice time on Vertigo

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

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Vertigo callouts & strategy →Vertigo grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–7	0.04	19%	19 Jun →
nuke	5–13	-0.02	11%	23 May →
mirage	13–5	0.09	9%	23 May →
nuke	8–13	-0.02	9%	23 May →
inferno	13–6	0.01	4%	23 May →
inferno	3–13	-0.10	0%	23 May →
mirage	13–10	-0.05	13%	22 May →
anubis	11–1	0.08	23%	22 May →
nuke	13–6	0.08	5%	22 May →
dust2	15–15	-0.01	15%	22 May →
ancient	13–8	0.03	14%	22 May →
dust2	11–13	-0.01	21%	22 May →
anubis	16–13	-0.04	7%	22 May →
ancient	13–10	0.04	7%	22 May →
overpass	4–13	-0.09	23%	22 May →
ancient	16–14	0.01	17%	22 May →
dust2	13–7	0.05	15%	22 May →
dust2	11–4	-0.01	15%	22 May →
overpass	8–13	-0.00	6%	22 May →
mirage	13–8	0.08	16%	22 May →
mirage	13–3	0.05	12%	22 May →
inferno	9–13	-0.01	12%	22 May →
ancient	4–13	-0.04	7%	22 May →
nuke	8–13	-0.01	5%	22 May →
overpass	8–13	-0.02	11%	22 May →
inferno	13–5	0.01	17%	22 May →
inferno	13–7	0.04	15%	21 May →
anubis	13–3	0.07	11%	21 May →
dust2	13–10	0.08	11%	21 May →
inferno	11–13	0.08	16%	21 May →
inferno	11–13	0.05	9%	21 May →
dust2	13–7	0.10	12%	21 May →
ancient	13–10	-0.01	20%	21 May →
overpass	16–13	0.08	10%	21 May →
nuke	11–13	-0.02	13%	21 May →
mirage	14–16	0.01	22%	21 May →
anubis	6–13	-0.04	7%	21 May →
mirage	9–13	-0.02	9%	21 May →
nuke	13–9	0.08	15%	21 May →
mirage	13–8	-0.07	15%	21 May →
dust2	13–3	0.00	13%	21 May →
inferno	13–11	0.04	13%	19 May →
anubis	13–8	-0.01	13%	19 May →
nuke	13–4	0.01	14%	14 Apr →
mirage	5–13	-0.02	12%	14 Apr →
nuke	13–4	0.00	12%	7 Oct →
ancient	13–10	-0.03	11%	25 Aug →
nuke	11–13	0.03	5%	27 Feb →
anubis	13–1	0.18	17%	11 Feb →
anubis	13–16	-0.02	9%	3 Feb →
anubis	5–13	-0.08	12%	29 Jan →
nuke	13–9	0.04	33%	27 Jan →
anubis	13–4	0.00	12%	18 Nov →
train	13–9	-0.04	15%	14 Nov →
train	13–4	0.00	25%	14 Nov →
train	11–13	0.03	21%	14 Nov →
dust2	2–13	-0.06	36%	14 Nov →
ancient	10–13	-0.03	9%	30 Aug →
nuke	13–16	-0.03	17%	30 Aug →
anubis	9–13	-0.08	14%	30 Aug →
mirage	3–13	0.04	20%	29 Aug →
ancient	13–9	0.04	17%	22 Aug →
nuke	11–13	-0.01	16%	21 Aug →
anubis	13–11	-0.00	15%	12 Aug →
inferno	10–13	0.02	16%	30 Jul →
dust2	13–11	0.01	32%	30 Jul →
anubis	13–6	0.04	7%	30 Jul →
vertigo	15–15	0.05	17%	30 Jul →
inferno	11–13	-0.01	13%	30 Jul →
nuke	13–6	0.03	8%	30 Jul →
nuke	11–13	-0.02	8%	29 Jul →
anubis	13–9	-0.02	21%	29 Jul →
vertigo	13–6	0.09	22%	29 Jul →
anubis	6–13	-0.02	14%	28 Jul →
dust2	13–5	0.02	25%	28 Jul →
inferno	10–13	-0.07	21%	28 Jul →
nuke	3–13	-0.05	11%	28 Jul →
inferno	13–1	-0.00	20%	28 Jul →
mirage	13–4	0.03	18%	28 Jul →
inferno	6–13	-0.03	13%	27 Jul →
vertigo	9–13	-0.00	12%	26 Jul →
anubis	13–11	0.08	4%	26 Jul →
nuke	15–15	0.02	14%	26 Jul →
inferno	13–11	0.16	16%	26 Jul →
anubis	5–13	0.04	12%	26 Jul →
mirage	13–2	0.05	22%	26 Jul →
dust2	16–12	0.10	17%	26 Jul →
vertigo	11–13	0.05	20%	26 Jul →
inferno	16–13	0.03	18%	26 Jul →
vertigo	15–15	0.04	16%	25 Jul →
inferno	6–13	-0.04	7%	25 Jul →
nuke	13–9	0.07	9%	25 Jul →
vertigo	13–10	0.01	17%	25 Jul →
anubis	13–8	0.01	18%	25 Jul →
mirage	12–16	0.04	9%	25 Jul →
inferno	13–3	0.21	14%	25 Jul →
ancient	13–7	0.04	18%	25 Jul →
dust2	13–8	0.04	13%	24 Jul →
mirage	9–13	0.01	12%	24 Jul →
anubis	13–8	0.02	13%	24 Jul →