Whiteold — CS2 Stats

76561198158029024[U:1:197763296]Steam profile ↗✓ No bans

3,414Tracked matches70%Win rate2020Tracked since

CSDB Rating5.8 SolidHybrid Rifler

CSDB Leaderboard#19134 of 20454 tracked

FaceitLevel 9 · 1,797 ELOTop 20.7% of ranked FACEIT players

Ladder ranks via Leetify

Rating over time

1,797Peak Faceit ELO on CSDB

1Days observed since 2026-08-28

Faceit ELO

At peak — 1,797
Next: Level 10 at 2,001 — 204 to go
Reached: Level 9 · Level 8 · Level 7 · Level 6
Level 9 first seen 2026-08-28
Level 8 first seen 2026-08-28

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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Performance scores

Aim68

Positioning48

Utility69

0–100 skill scores via Leetify.

Recent form

HOT57–38–5Last 10057%Win rateWWWLWWWWWW

Last 10 vs previous 10: +30pp win rate · +0.04 avg rating

Player DNA

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

Aim6.8

Aggression5.2

Utility6.9

Positioning4.8

Opening Duels1.8

Clutch4.0

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 90% playstyle similarity

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

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

Reaction time. 561ms 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

Aim6.8

Positioning4.8

Utility6.9

Mechanics6.1

Opening Duels1.8

Win Impact10.0

Composite 5.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.01

Reaction time568ms−83ms

first ⅓ avg 651ms → last ⅓ avg 568ms

Headshot accuracy20.2%+0.8%

first ⅓ avg 19.4% → last ⅓ avg 20.2%

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

0.17Best rating — nuke 13–3

13–0Biggest win — mirage

9Longest win streak

W3Current streak

12–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

ancientBest map · 75% over 16infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	28	19–9	68%	0.02
dust2	B	22	11–11	50%	-0.00
ancient	S	16	12–4	75%	-0.00
inferno	D	15	5–10	33%	-0.00
cache	A	7	4–3	57%	-0.02
overpass	A	5	3–2	60%	0.00
anubis	—	4	1–3	25%	-0.01
nuke	—	3	2–1	67%	0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

3,278Matches

50%Win rate

0.95Avg K/D

74.3ADR

47%Headshot %

Clutches & streaks

40%1v1 clutch win

20%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	487	52%	1.00	14.7
Dust2	254	43%	0.94	14.3
Inferno	205	56%	0.92	14.8
Ancient	176	47%	0.90	14.3
Anubis	110	44%	0.96	14.9
Nuke	59	46%	0.81	13.4
Vertigo	56	52%	0.93	14.4
Overpass	40	52%	0.85	14.6

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.

19.7%Headshot accuracy

33.6%Accuracy (enemy spotted)

33.5%Spray accuracy

77.2%Counter-strafing

9.9°Preaim

561msReaction time

30.1%T opening success

44.5%CT opening success

0.68Enemies flashed / flash

9.8%Flash assists

12.50HE damage / grenade

12.12Flashes / 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 30.0818% — 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.

33% win rate across 15 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	13–8	0.10	20%	28 Aug →
dust2	13–4	0.07	30%	28 Aug →
dust2	9–2	0.09	42%	28 Aug →
inferno	11–13	-0.05	21%	26 Aug →
inferno	13–11	0.05	24%	26 Aug →
mirage	13–11	0.01	16%	25 Aug →
dust2	13–6	-0.01	24%	24 Aug →
dust2	13–11	0.01	18%	23 Aug →
mirage	13–4	0.02	16%	23 Aug →
mirage	16–14	-0.01	32%	23 Aug →
inferno	19–15	-0.01	25%	21 Aug →
mirage	16–14	-0.03	20%	21 Aug →
inferno	19–17	-0.01	18%	21 Aug →
dust2	2–13	-0.04	8%	18 Aug →
mirage	9–13	-0.06	14%	18 Aug →
dust2	13–9	-0.03	28%	14 Aug →
ancient	14–16	0.03	24%	14 Aug →
mirage	13–4	0.07	13%	11 Aug →
ancient	16–13	-0.04	10%	11 Aug →
dust2	12–16	-0.03	15%	6 Aug →
anubis	10–13	0.01	22%	6 Aug →
ancient	5–13	-0.03	26%	1 Aug →
ancient	13–9	0.00	27%	29 Jul →
nuke	8–13	-0.06	16%	29 Jul →
inferno	5–13	0.02	19%	27 Jul →
cache	13–9	0.06	16%	27 Jul →
ancient	13–10	-0.03	11%	27 Jul →
mirage	13–7	-0.01	11%	26 Jul →
dust2	13–11	0.02	14%	26 Jul →
mirage	13–4	0.07	17%	25 Jul →
inferno	16–13	-0.01	19%	25 Jul →
dust2	13–3	0.10	28%	25 Jul →
inferno	11–13	-0.01	22%	18 Jul →
mirage	11–13	-0.02	17%	17 Jul →
dust2	6–13	0.05	21%	16 Jul →
dust2	6–13	-0.09	20%	14 Jul →
ancient	13–8	0.02	17%	14 Jul →
dust2	11–13	-0.00	22%	13 Jul →
cache	5–13	-0.08	17%	13 Jul →
ancient	13–4	0.04	10%	13 Jul →
mirage	15–15	0.02	19%	13 Jul →
mirage	13–10	-0.00	18%	12 Jul →
anubis	12–12	0.01	14%	11 Jul →
nuke	13–3	0.17	17%	11 Jul →
inferno	6–13	0.04	11%	11 Jul →
cache	12–12	-0.05	21%	11 Jul →
mirage	13–7	0.05	29%	11 Jul →
mirage	6–13	0.05	29%	11 Jul →
ancient	13–10	0.02	20%	10 Jul →
mirage	13–8	0.03	32%	10 Jul →
inferno	12–12	0.00	15%	10 Jul →
cache	13–9	-0.04	17%	10 Jul →
inferno	9–13	-0.03	17%	9 Jul →
mirage	3–13	-0.02	24%	9 Jul →
mirage	13–2	0.10	30%	9 Jul →
inferno	8–13	-0.06	14%	9 Jul →
cache	13–7	-0.03	18%	9 Jul →
ancient	13–11	-0.00	22%	9 Jul →
ancient	10–13	-0.01	19%	8 Jul →
cache	13–9	-0.00	10%	8 Jul →
overpass	13–9	-0.02	19%	4 Jul →
mirage	10–13	0.01	21%	4 Jul →
inferno	13–1	0.09	21%	4 Jul →
mirage	13–0	0.09	14%	4 Jul →
anubis	5–13	-0.10	15%	1 Jul →
ancient	16–14	0.01	23%	1 Jul →
anubis	13–6	0.03	13%	30 Jun →
mirage	6–13	0.02	20%	30 Jun →
inferno	9–13	0.05	25%	30 Jun →
dust2	5–13	-0.07	15%	29 Jun →
mirage	13–9	0.00	25%	29 Jun →
dust2	9–13	-0.02	16%	29 Jun →
dust2	13–11	-0.05	17%	26 Jun →
dust2	11–13	-0.00	27%	23 Jun →
mirage	13–8	0.03	15%	23 Jun →
mirage	13–8	0.06	17%	5 Jun →
inferno	5–13	-0.02	32%	5 Jun →
dust2	13–9	-0.04	14%	5 Jun →
ancient	13–8	-0.00	20%	5 Jun →
overpass	13–10	-0.03	10%	5 Jun →
dust2	13–11	-0.01	31%	21 May →
inferno	6–13	-0.11	10%	21 May →
mirage	13–6	0.00	19%	21 May →
cache	12–12	-0.01	18%	21 May →
nuke	13–7	0.07	21%	21 May →
ancient	16–13	-0.01	10%	10 May →
ancient	13–8	-0.02	32%	10 May →
dust2	11–13	0.03	29%	27 Apr →
overpass	12–16	-0.02	21%	20 Apr →
mirage	13–8	-0.04	10%	14 Apr →
ancient	13–6	0.00	14%	6 Apr →
mirage	13–10	-0.05	14%	6 Apr →
mirage	20–22	-0.03	24%	28 Mar →
mirage	12–16	0.01	20%	27 Mar →
dust2	13–11	0.02	25%	27 Mar →
overpass	13–4	0.06	11%	18 Mar →
overpass	6–13	0.03	20%	17 Mar →
dust2	7–13	-0.06	14%	17 Mar →
dust2	7–13	0.04	20%	11 Mar →
ancient	8–13	-0.00	22%	11 Mar →