PeruvianWidePeek — CS2 Stats

76561198147174894[U:1:186909166]

961Tracked matches48%Win rate2020Tracked since

CSDB Rating5.6 SolidHybrid Rifler

Premier CS Rating17,913Purple band · top ~16.8% of ranked players (population est.)

FaceitLevel 6Top 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim69

Positioning52

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY45–51–4Last 10045%Win rateWWLWLWLWLL

Last 10 vs previous 10: +20pp win rate · -0.01 avg rating

Player DNA

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

Aim6.9

Aggression6.0

Utility4.8

Positioning5.2

Opening Duels1.3

Clutch2.0

Strong T-side opener

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 87% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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

CT openings. Opening success drops from 43% on T to 27% on CT — first contacts on the defending side are being lost.

Reaction time. 583ms 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

Aim6.9

Positioning5.2

Utility4.8

Mechanics7.5

Opening Duels1.6

Win Impact4.4

Composite 5.6/10 (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+0.02

first ⅓ avg 0.00 → last ⅓ avg 0.02

Reaction time580ms−33ms

first ⅓ avg 613ms → last ⅓ avg 580ms

Headshot accuracy18.9%−4.4%

first ⅓ avg 23.3% → last ⅓ avg 18.9%

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

0.23Best rating — nuke 9–5

13–1Biggest win — overpass

6Longest win streak

W2Current streak

7–5In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 75% over 8anubisWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	27	13–14	48%	0.01
mirage	C	20	8–12	40%	-0.00
inferno	C	17	6–11	35%	0.02
anubis	D	8	2–6	25%	-0.02
nuke	S	8	6–2	75%	0.07
ancient	B	6	3–3	50%	0.02
overpass	—	4	3–1	75%	0.02
train	—	3	2–1	67%	0.01
office	—	2	0–2	0%	0.03
vertigo	—	2	0–2	0%	0.00
cache	—	1	1–0	100%	0.08
alpine	—	1	1–0	100%	0.03
jura	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

43Matches

63%Win rate

1.22Avg K/D

78.4ADR

50%Headshot %

Clutches & streaks

30%1v1 clutch win

19%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	14	43%	0.95	15.1
Dust2	11	82%	1.08	15.4
Vertigo	6	50%	1.03	18.7
Nuke	3	67%	1.60	19.3
Anubis	2	50%	0.84	13.5
Ancient	2	100%	1.74	21.5
Inferno	2	50%	1.23	18.0

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.

18.5%Headshot accuracy

32.7%Accuracy (enemy spotted)

35.6%Spray accuracy

83.5%Counter-strafing

10.0°Preaim

583msReaction time

43.1%T opening success

27.4%CT opening success

0.60Enemies flashed / flash

6.9%Flash assists

8.49HE damage / grenade

6.74Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 27.448% — below the 40% mark we flag

Spend your practice time on Anubis

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–7	0.08	16%	21 Aug →
overpass	13–6	0.05	24%	29 Mar →
inferno	9–13	-0.02	13%	28 Mar →
dust2	13–9	0.04	18%	24 Mar →
anubis	14–16	-0.05	5%	22 Mar →
mirage	13–8	-0.02	14%	21 Mar →
dust2	8–13	0.02	22%	21 Mar →
anubis	13–7	0.02	16%	20 Mar →
mirage	9–13	0.05	13%	20 Mar →
dust2	7–13	0.02	15%	20 Mar →
nuke	13–8	0.02	14%	19 Mar →
inferno	13–4	-0.07	30%	19 Mar →
mirage	2–13	-0.01	11%	19 Mar →
dust2	3–13	-0.00	27%	19 Mar →
nuke	8–13	0.08	20%	18 Mar →
dust2	6–13	0.06	22%	17 Mar →
mirage	13–2	0.04	17%	17 Mar →
dust2	12–12	0.11	15%	17 Mar →
mirage	10–13	-0.01	25%	16 Mar →
inferno	11–13	0.03	12%	16 Mar →
dust2	13–9	0.09	16%	16 Mar →
dust2	13–3	0.06	23%	16 Mar →
overpass	13–1	0.05	21%	14 Mar →
dust2	11–13	-0.00	23%	13 Mar →
office	9–13	-0.04	26%	12 Mar →
overpass	10–13	-0.02	25%	11 Mar →
dust2	13–11	0.04	20%	11 Mar →
dust2	13–7	0.01	14%	11 Mar →
nuke	13–1	0.04	33%	11 Mar →
inferno	2–9	-0.06	23%	11 Mar →
nuke	10–13	-0.00	18%	11 Mar →
dust2	13–7	-0.01	15%	11 Mar →
office	9–13	0.11	20%	10 Mar →
alpine	13–9	0.03	19%	10 Mar →
mirage	6–13	0.06	23%	10 Mar →
dust2	13–9	0.06	24%	10 Mar →
inferno	5–13	0.02	12%	9 Mar →
mirage	13–9	0.05	21%	9 Mar →
dust2	5–13	-0.03	28%	9 Mar →
mirage	8–13	-0.06	11%	9 Mar →
inferno	13–7	0.06	27%	9 Mar →
mirage	9–13	-0.06	16%	8 Mar →
dust2	6–13	-0.03	22%	8 Mar →
ancient	8–13	0.07	14%	8 Mar →
dust2	13–5	0.04	11%	8 Mar →
ancient	9–13	0.06	13%	8 Mar →
dust2	9–13	-0.03	21%	8 Mar →
inferno	8–13	0.14	21%	7 Mar →
train	13–11	-0.01	11%	7 Mar →
nuke	13–9	-0.01	20%	7 Mar →
mirage	16–14	0.07	15%	6 Mar →
anubis	13–4	0.04	15%	6 Mar →
overpass	13–8	0.02	29%	6 Mar →
inferno	13–7	0.10	17%	3 Mar →
dust2	3–13	-0.01	17%	7 Feb →
dust2	7–13	-0.00	21%	1 Jan →
mirage	11–13	-0.01	17%	29 Nov →
dust2	4–13	-0.01	25%	22 Nov →
mirage	13–6	0.01	11%	21 Nov →
inferno	5–9	0.05	37%	15 Nov →
dust2	13–7	-0.05	22%	14 Nov →
mirage	10–13	-0.02	23%	14 Nov →
nuke	9–5	0.23	32%	14 Nov →
dust2	12–12	-0.02	23%	14 Nov →
dust2	13–9	0.05	23%	14 Nov →
ancient	8–13	-0.05	15%	16 Sept →
dust2	16–14	-0.06	16%	10 Jul →
mirage	8–13	-0.03	26%	7 Jul →
inferno	13–8	0.04	25%	6 Jul →
vertigo	12–12	-0.01	28%	23 Jun →
inferno	13–4	0.09	33%	23 Jun →
train	16–14	0.05	20%	16 Jun →
inferno	7–13	-0.03	35%	16 Jun →
mirage	13–7	-0.07	11%	13 Jun →
mirage	8–13	-0.06	23%	13 Jun →
inferno	10–13	0.07	37%	13 Jun →
jura	1–5	-0.02	29%	7 Jun →
inferno	6–1	-0.03	0%	7 Jun →
ancient	13–8	-0.00	21%	7 Jun →
mirage	13–11	0.07	15%	5 Jun →
vertigo	5–13	0.02	22%	5 Jun →
dust2	13–7	0.01	16%	31 May →
anubis	8–13	-0.00	20%	30 May →
mirage	8–13	-0.00	19%	30 May →
ancient	13–11	-0.04	16%	30 May →
dust2	6–13	-0.07	17%	27 May →
anubis	11–13	0.01	26%	24 May →
nuke	4–0	0.09	63%	23 May →
anubis	5–13	-0.06	47%	23 May →
anubis	7–13	-0.07	24%	23 May →
inferno	15–15	-0.00	19%	22 May →
anubis	7–13	-0.04	23%	22 May →
nuke	13–3	0.10	22%	21 May →
inferno	4–13	-0.01	13%	21 May →
train	10–13	-0.02	20%	21 May →
mirage	13–9	-0.03	6%	21 May →
ancient	13–4	0.09	28%	21 May →
inferno	9–13	0.06	22%	21 May →
mirage	6–13	-0.02	31%	20 May →
dust2	13–10	-0.03	16%	20 May →