Tohtori Toleranssi — CS2 Stats

76561198403715565[U:1:443449837]Steam profile ↗✓ No bans

693Tracked matches53%Win rate2020Tracked since

CSDB Rating5.3 DevelopingAggressive Rifler

Premier CS Rating9,356Light Blue band · top ~58% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim75

Positioning57

Utility25

0–100 skill scores via Leetify.

Recent form

HOT46–53–1Last 10046%Win rateWWWLWWWWLW

Last 10 vs previous 10: +60pp win rate · +0.03 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.5

Aggression7.0

Utility2.5

Positioning5.7

Opening Duels3.2

Clutch3.4

Limited utility dependence

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 ropz 87% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

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

Reaction time. 631ms 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

Aim7.5

Positioning5.7

Utility2.5

Mechanics8.1

Opening Duels3.2

Win Impact6.1

Composite 5.3/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 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 time626ms−139ms

first ⅓ avg 764ms → last ⅓ avg 626ms

Headshot accuracy28.9%−2.2%

first ⅓ avg 31.1% → last ⅓ avg 28.9%

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

0.14Best rating — ancient 13–6

13–2Biggest win — nuke

5Longest win streak

W3Current streak

5–12In matches decided by ≤2 rounds

13Overtime games

Map breakdown

trainBest map · 75% over 8ancientWeakest map · 33% over 12

Map	Grade	Played	Record	Win rate	Avg rating
nuke	C	37	16–21	43%	-0.01
mirage	B	17	9–8	53%	0.01
ancient	D	12	4–8	33%	0.02
dust2	B	11	5–6	45%	0.01
train	S	8	6–2	75%	0.00
anubis	—	4	2–2	50%	0.02
overpass	—	4	0–4	0%	-0.03
vertigo	—	4	3–1	75%	0.01
inferno	—	3	1–2	33%	0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

617Matches

51%Win rate

1.13Avg K/D

82.4ADR

62%Headshot %

Clutches & streaks

37%1v1 clutch win

19%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	122	48%	1.01	14.3
Vertigo	84	70%	1.38	17.8
Ancient	75	43%	1.12	15.4
Nuke	64	53%	1.05	15.6
Anubis	62	53%	1.17	16.5
Dust2	62	45%	0.99	15.3
Inferno	27	52%	1.08	14.9
Train	21	57%	1.02	15.8

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.

29.8%Headshot accuracy

30.7%Accuracy (enemy spotted)

30.2%Spray accuracy

86.6%Counter-strafing

9.6°Preaim

631msReaction time

35.3%T opening success

50.0%CT opening success

0.26Enemies flashed / flash

1.4%Flash assists

10.88HE damage / grenade

4.01Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.2632 — below the 0.5 mark we flag
Grenade Lineups →
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 35.3338% — below the 40% mark we flag

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.

33% win rate across 12 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
mirage	13–7	0.06	26%	23 Jul →
mirage	13–4	0.10	35%	8 Mar →
anubis	13–10	0.00	16%	8 Mar →
mirage	3–13	-0.06	21%	8 Mar →
ancient	13–4	0.07	36%	22 Feb →
mirage	16–12	0.01	22%	22 Feb →
mirage	16–14	-0.00	24%	17 Feb →
nuke	13–10	0.10	50%	12 Feb →
overpass	14–16	-0.01	25%	12 Feb →
dust2	13–8	0.02	31%	11 Feb →
inferno	13–7	0.05	37%	11 Feb →
nuke	8–13	0.01	23%	11 Feb →
ancient	6–13	0.01	28%	11 Feb →
mirage	6–13	0.08	27%	11 Feb →
mirage	6–13	-0.05	26%	9 Feb →
nuke	6–13	-0.03	46%	9 Feb →
dust2	13–11	0.13	21%	5 Feb →
mirage	5–13	-0.06	15%	5 Feb →
dust2	6–13	-0.07	21%	4 Feb →
dust2	9–13	-0.06	24%	1 Feb →
nuke	13–10	-0.02	16%	31 Jan →
mirage	8–13	-0.01	32%	31 Jan →
dust2	13–10	0.04	24%	28 Jan →
mirage	10–13	0.03	46%	28 Jan →
ancient	13–6	0.14	36%	28 Jan →
nuke	13–11	0.01	44%	28 Jan →
nuke	10–13	-0.02	38%	28 Jan →
ancient	13–5	0.08	34%	28 Jan →
nuke	20–22	-0.02	37%	25 Jan →
mirage	13–8	-0.02	32%	25 Jan →
nuke	11–13	0.05	32%	25 Jan →
nuke	13–5	-0.05	7%	22 Jan →
vertigo	11–3	0.01	21%	22 Jan →
nuke	10–13	-0.02	11%	22 Jan →
nuke	9–13	-0.06	20%	20 Jan →
nuke	13–7	-0.01	36%	20 Jan →
inferno	6–13	-0.05	36%	20 Jan →
mirage	13–7	0.10	16%	20 Jan →
dust2	13–3	0.06	25%	15 Jan →
nuke	5–13	-0.08	8%	14 Jan →
nuke	15–15	0.01	27%	14 Jan →
ancient	14–16	-0.05	30%	14 Jan →
train	16–13	0.03	28%	14 Jan →
mirage	13–8	0.05	27%	14 Jan →
anubis	13–9	0.01	28%	12 Jan →
train	16–13	-0.03	22%	12 Jan →
nuke	13–5	0.05	47%	12 Jan →
nuke	3–13	-0.02	21%	11 Jan →
mirage	13–7	0.01	23%	8 Jan →
ancient	5–13	0.03	27%	8 Jan →
nuke	13–9	0.04	37%	7 Jan →
nuke	8–13	-0.00	50%	7 Jan →
ancient	8–13	-0.04	35%	7 Jan →
inferno	14–16	0.01	34%	6 Jan →
train	13–6	0.07	49%	6 Jan →
dust2	16–12	0.00	25%	6 Jan →
dust2	9–10	-0.01	54%	6 Jan →
nuke	13–4	-0.03	32%	6 Jan →
nuke	11–13	-0.05	28%	18 Dec →
mirage	13–8	0.00	33%	17 Dec →
train	13–10	0.04	38%	16 Dec →
nuke	12–16	-0.01	42%	16 Dec →
train	13–11	-0.04	30%	15 Dec →
overpass	11–13	-0.00	37%	11 Dec →
ancient	9–13	0.04	26%	4 Dec →
dust2	7–13	-0.06	15%	27 Nov →
nuke	13–11	0.03	37%	20 Nov →
overpass	4–13	-0.00	26%	20 Nov →
overpass	3–13	-0.09	11%	11 Nov →
train	13–6	-0.06	22%	23 Sept →
nuke	4–13	-0.06	25%	22 Jan →
ancient	13–8	0.01	37%	18 Jan →
nuke	13–7	0.08	35%	15 Jan →
train	5–13	0.05	35%	11 Jan →
ancient	0–13	-0.07	19%	5 Jan →
vertigo	6–13	-0.03	30%	4 Jan →
mirage	11–13	-0.01	37%	23 Dec →
dust2	11–13	-0.02	24%	21 Dec →
nuke	11–13	0.02	36%	21 Dec →
mirage	10–13	0.00	33%	14 Dec →
nuke	5–7	-0.11	67%	13 Dec →
nuke	8–3	0.06	80%	13 Dec →
vertigo	13–7	0.03	24%	9 Dec →
anubis	10–13	0.00	24%	9 Dec →
ancient	4–13	-0.05	26%	8 Dec →
vertigo	16–12	0.05	26%	3 Dec →
train	9–13	-0.05	48%	30 Nov →
nuke	1–12	-0.07	24%	30 Nov →
nuke	13–8	0.01	28%	28 Nov →
dust2	13–16	0.10	37%	28 Nov →
anubis	10–13	0.07	26%	27 Nov →
nuke	5–9	-0.00	15%	1 Nov →
ancient	5–13	0.03	29%	8 Oct →
nuke	6–13	-0.08	25%	23 Jul →
nuke	13–10	-0.03	27%	19 Jul →
nuke	13–3	-0.05	58%	10 Jul →
nuke	13–2	0.06	26%	10 Jul →
nuke	9–12	-0.01	27%	4 Jul →
nuke	13–2	0.12	18%	2 Jul →
nuke	2–13	-0.08	20%	29 Jun →