Kananpoikajr — CS2 Stats

76561198066485483[U:1:106219755]

1,228Tracked matches50%Win rate2020Tracked since

CSDB Rating5.7 SolidClutch Specialist

Premier CS Rating26,367Top 25% of 819 CSDB-tracked playersRed band · top ~2.3% of ranked players (population est.)

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim60

Positioning47

Utility72

0–100 skill scores via Leetify.

Recent form

STEADY54–40–6Last 10054%Win rateWLLLLWLWWW

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim6.0

Aggression5.2

Utility7.2

Positioning4.7

Opening Duels0.8

Clutch10.0

Strong CT-side openerReliable 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.

Your pro match

Plays most like NiKo 86% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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

T-side openings. Opening success drops from 42% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 622ms 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

Aim6.0

Positioning4.7

Utility7.2

Mechanics6.4

Opening Duels1.5

Win Impact5.0

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.00

Reaction time602ms−30ms

first ⅓ avg 632ms → last ⅓ avg 602ms

Headshot accuracy15.2%−0.7%

first ⅓ avg 15.9% → 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.

Highlights

0.19Best rating — inferno 13–2

13–1Biggest win — overpass

8Longest win streak

10–10In matches decided by ≤2 rounds

11Overtime games

Map breakdown

mirageBest map · 88% over 8infernoWeakest map · 46% over 26

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	26	12–14	46%	0.01
cache	B	15	7–8	47%	0.01
ancient	B	14	7–7	50%	-0.00
dust2	B	12	6–6	50%	-0.02
overpass	S	12	9–3	75%	0.03
nuke	B	10	5–5	50%	-0.00
mirage	S	8	7–1	88%	0.03
anubis	—	3	1–2	33%	0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (46% over 26). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,886Matches

50%Win rate

1.18Avg K/D

71.2ADR

34%Headshot %

Clutches & streaks

80%1v1 clutch win

60%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	11	18%	0.94	15.1
Ancient	11	27%	0.84	11.8
Mirage	8	38%	0.83	15.9
Overpass	7	43%	0.90	13.1
Anubis	3	33%	1.10	16.7
Cache	3	100%	0.92	13.7
Nuke	2	100%	0.75	11.5
Dust2	1	0%	0.88	14.0

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.

15.2%Headshot accuracy

34.6%Accuracy (enemy spotted)

40.3%Spray accuracy

78.8%Counter-strafing

11.2°Preaim

622msReaction time

24.9%T opening success

41.9%CT opening success

0.69Enemies flashed / flash

14.1%Flash assists

12.87HE damage / grenade

8.59Flashes / 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
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 24.855% — 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.

46% win rate across 26 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
mirage	13–4	0.07	21%	27 Aug →
ancient	5–13	-0.08	15%	16 Aug →
inferno	9–13	-0.01	14%	14 Aug →
dust2	2–13	-0.02	20%	14 Aug →
nuke	11–13	0.01	21%	14 Aug →
cache	13–2	-0.03	4%	10 Aug →
inferno	11–13	0.03	17%	6 Aug →
nuke	16–14	-0.00	13%	6 Aug →
dust2	16–14	-0.00	18%	3 Aug →
inferno	13–8	-0.01	9%	3 Aug →
cache	9–13	0.05	8%	26 Jul →
cache	13–11	0.01	22%	23 Jul →
inferno	14–16	-0.02	11%	23 Jul →
cache	13–10	-0.01	15%	23 Jul →
inferno	10–13	0.04	13%	21 Jul →
nuke	2–0	-0.03	0%	21 Jul →
cache	11–13	0.11	20%	17 Jul →
cache	13–10	-0.03	13%	14 Jul →
dust2	10–13	-0.07	21%	14 Jul →
dust2	13–10	0.04	15%	12 Jul →
mirage	13–8	0.03	12%	12 Jul →
nuke	13–3	0.02	23%	12 Jul →
mirage	18–22	-0.01	12%	7 Jul →
ancient	7–13	-0.02	10%	4 Jul →
dust2	13–11	-0.03	10%	4 Jul →
inferno	10–13	0.00	18%	4 Jul →
ancient	4–13	-0.05	9%	29 Jun →
inferno	13–4	0.07	21%	29 Jun →
overpass	13–4	-0.03	15%	24 Jun →
dust2	10–13	-0.03	28%	24 Jun →
dust2	10–13	-0.02	20%	5 Jun →
ancient	11–13	-0.02	9%	5 Jun →
nuke	13–7	0.03	27%	5 Jun →
ancient	13–3	0.06	19%	4 Jun →
dust2	15–15	-0.05	11%	4 Jun →
inferno	13–11	0.02	13%	1 Jun →
dust2	13–11	-0.01	10%	1 Jun →
nuke	7–13	0.02	11%	1 Jun →
overpass	11–13	0.01	5%	25 May →
inferno	3–13	-0.03	19%	25 May →
overpass	13–1	0.05	7%	21 May →
inferno	13–11	-0.01	22%	21 May →
ancient	13–7	-0.04	13%	21 May →
mirage	13–8	-0.02	22%	19 May →
inferno	13–8	-0.02	18%	19 May →
dust2	6–13	-0.09	3%	19 May →
cache	13–11	0.03	14%	17 May →
inferno	7–13	-0.00	16%	17 May →
cache	2–13	-0.02	16%	12 May →
cache	12–12	0.02	16%	12 May →
ancient	13–11	0.12	13%	12 May →
inferno	11–13	0.02	14%	10 May →
cache	12–12	0.05	15%	5 May →
cache	13–10	0.03	20%	5 May →
cache	13–7	0.03	22%	29 Apr →
cache	11–13	-0.06	16%	29 Apr →
cache	6–13	-0.01	20%	29 Apr →
cache	6–13	-0.02	10%	29 Apr →
dust2	16–13	0.04	18%	28 Apr →
inferno	10–13	-0.05	10%	28 Apr →
ancient	15–15	-0.00	21%	27 Apr →
dust2	13–9	0.03	16%	27 Apr →
nuke	8–13	-0.02	15%	27 Apr →
mirage	13–2	0.06	20%	22 Apr →
inferno	10–13	0.03	17%	22 Apr →
overpass	13–5	0.05	23%	18 Apr →
ancient	13–6	-0.03	9%	18 Apr →
nuke	10–13	-0.05	12%	15 Apr →
anubis	6–13	-0.02	11%	15 Apr →
overpass	13–8	0.05	28%	13 Apr →
inferno	13–8	0.01	25%	13 Apr →
overpass	13–9	0.13	13%	10 Apr →
inferno	8–13	-0.01	24%	10 Apr →
anubis	13–9	0.04	19%	10 Apr →
inferno	9–13	-0.04	11%	10 Apr →
mirage	13–10	0.03	30%	7 Apr →
ancient	13–8	-0.01	21%	7 Apr →
inferno	13–10	-0.00	11%	7 Apr →
mirage	13–5	0.01	13%	6 Apr →
overpass	13–6	-0.00	17%	31 Mar →
inferno	13–5	-0.02	10%	31 Mar →
ancient	13–8	0.09	10%	28 Mar →
nuke	13–9	-0.00	15%	28 Mar →
inferno	4–13	-0.07	14%	28 Mar →
inferno	16–13	0.02	19%	27 Mar →
nuke	15–15	-0.02	8%	27 Mar →
overpass	15–15	-0.01	12%	26 Mar →
ancient	13–7	0.02	11%	26 Mar →
inferno	11–13	0.02	12%	26 Mar →
overpass	6–13	-0.04	16%	24 Mar →
mirage	13–4	0.06	20%	19 Mar →
overpass	13–6	0.09	8%	19 Mar →
inferno	13–2	0.19	13%	19 Mar →
anubis	11–13	-0.00	10%	18 Mar →
ancient	6–13	0.00	22%	18 Mar →
overpass	13–6	0.02	17%	17 Mar →
inferno	13–10	0.02	17%	17 Mar →
ancient	13–16	-0.07	18%	17 Mar →
inferno	13–5	0.04	17%	14 Mar →
overpass	13–5	0.03	23%	13 Mar →