♞Totilas ♘

♞Totilas ♘ — CS2 Stats

76561198052071835[U:1:91806107]Steam profile ↗✓ No bans

98Tracked matches41%Win rate2020Tracked since
CSDB Rating4.0 DevelopingSupport
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 12,666 +1,515 4 Feb – 3 Jul · 20 days played
9,36013,697peak 13,6974 Feb3 Jul
13,697Peak Premier in tracked matches
63Days played since 2020-09-29

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim48
Positioning37
Utility54

0–100 skill scores via Leetify.

Recent form

STEADY36–48–7Last 9140%Win rateLWLLWLWWLL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −0.7pp headshot accuracy · +16ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 12%
  • Avg reaction 628ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 634ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 625ms

Newest first, from the last 91 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+3 against its own average).

Aim4.8
Utility5.4
Positioning3.7
Opening Duels0.7
Clutch0.0

Effective flashesLimited 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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

NiKo

Plays most like NiKo 76% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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. 629ms 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

Aim4.8
Positioning3.7
Utility5.4
Mechanics4.7
Opening Duels0.5
Win Impact2.1

Composite 4.0/10 (Developing), 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 rating-0.02+0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time628ms−39ms
first ⅓ avg 667ms → last ⅓ avg 628ms
Headshot accuracy11.3%+1.3%
first ⅓ avg 9.9% → last ⅓ avg 11.3%

Rolling 5-match average across the last 91 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.14Best match rating · 13–3 · anubis, 17 Jul →
31%Best headshot accuracy · 13–9 · cache, 3 Jun →
406msFastest reaction time · 8–13 · inferno, 24 Jul →
13–2Biggest win · inferno, 3 Apr →

Across the last 91 tracked matches.

Highlights

3Longest win streak
8–5In matches decided by ≤2 rounds
37Overtime games

Map breakdown

ancientBest map · 73% over 11anubisWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
infernoA169–756%0.01
dust2D164–1225%-0.03
nukeC125–742%-0.01
mirageD123–925%-0.01
ancientS118–373%-0.02
cacheB115–645%-0.04
anubisD61–517%0.01
overpassD51–420%-0.03
vertigo—10–10%-0.09
train—10–10%0.00

Across the last 91 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

37Matches
43%Win rate
0.93Avg K/D
102.2ADR
26%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
5Longest win streak

Recent Faceit resultsWWLLW

MapMatchesWin rateAvg K/DAvg kills
Cache10%0.8517.0
Dust21100%2.4422.0

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.

11.3%Headshot accuracy
34.3%Accuracy (enemy spotted)
34.2%Spray accuracy
71.1%Counter-strafing
9.6°Preaim
629msReaction time
22.3%T opening success
33.8%CT opening success
0.72Enemies flashed / flash
3.7%Flash assists
10.29HE damage / grenade
4.67Flashes / 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.

  1. 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 11.3465% — below the 15% mark we flag

    Aim Training →
  2. 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 22.3296% — 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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke5–13-0.0017%30 Aug →
ancient16–14-0.0310%26 Jul →
cache9–13-0.079%24 Jul →
nuke11–13-0.0111%24 Jul →
nuke13–10-0.0811%24 Jul →
anubis11–13-0.034%24 Jul →
nuke13–11-0.027%24 Jul →
ancient13–10-0.057%24 Jul →
inferno8–13-0.067%24 Jul →
inferno5–130.0215%22 Jul →
anubis13–30.1416%17 Jul →
mirage13–16-0.0619%16 Jul →
mirage9–13-0.0310%3 Jul →
ancient13–11-0.004%3 Jul →
overpass11–13-0.0017%24 Jun →
cache6–13-0.0413%24 Jun →
cache5–2-0.100%24 Jun →
ancient16–13-0.039%23 Jun →
overpass15–15-0.079%21 Jun →
dust25–13-0.069%21 Jun →
inferno13–11-0.0312%21 Jun →
inferno13–80.0213%21 Jun →
mirage13–11-0.0110%21 Jun →
dust211–130.0516%18 Jun →
inferno8–13-0.0112%7 Jun →
ancient7–13-0.029%7 Jun →
vertigo0–13-0.0915%7 Jun →
inferno9–60.0913%7 Jun →
mirage10–130.0217%6 Jun →
inferno6–130.0819%4 Jun →
cache13–9-0.0231%3 Jun →
cache4–13-0.0211%3 Jun →
anubis15–15-0.0011%31 May →
inferno10–130.0219%31 May →
dust23–13-0.134%29 May →
dust24–13-0.0322%26 May →
dust22–13-0.0522%25 May →
anubis7–13-0.0421%19 May →
nuke8–130.0014%17 May →
ancient13–11-0.0515%17 May →
ancient13–100.019%17 May →
dust215–15-0.0418%13 May →
mirage8–130.018%13 May →
inferno12–3-0.0223%28 Apr →
overpass2–13-0.0825%7 Apr →
mirage10–130.019%4 Apr →
mirage15–15-0.0211%3 Apr →
inferno13–20.0116%3 Apr →
train8–120.0016%5 Nov →
dust213–70.0116%29 Oct →
inferno10–130.008%12 May →
dust22–13-0.0514%1 May →
nuke13–9-0.0210%10 Apr →
overpass9–130.1012%5 Apr →
anubis5–13-0.0514%12 Feb →
ancient15–15-0.0311%10 Feb →
ancient13–110.067%7 Feb →
anubis6–130.0515%5 Feb →
inferno13–90.029%4 Feb →
mirage13–70.0117%28 Jan →
ancient16–140.0219%27 Jan →
ancient6–13-0.0614%21 Jan →
inferno16–10-0.0012%2 Apr →
cache16–7-0.1018%2 Apr →
mirage9–16-0.075%28 Mar →
cache16–7-0.0411%28 Mar →
dust216–8-0.0010%27 Mar →
dust23–16-0.073%27 Mar →
overpass16–13-0.099%22 Mar →
inferno10–16-0.047%22 Mar →
cache7–16-0.0710%22 Mar →
nuke15–150.0410%28 Feb →
dust24–90.0412%19 Jan →
inferno16–8-0.0412%16 Sept →
nuke16–130.069%15 Sept →
dust216–8-0.029%13 Sept →
dust212–160.0112%12 Sept →
nuke15–15-0.029%9 Sept →
nuke16–7-0.0119%6 Sept →
dust211–16-0.089%3 Sept →
inferno16–100.0413%21 Aug →
dust214–16-0.053%12 Jun →
nuke8–16-0.017%26 May →
mirage10–160.0110%26 May →
dust216–9-0.038%24 May →
nuke12–16-0.095%19 May →
mirage10–160.029%14 May →
cache16–120.0813%10 May →
mirage16–130.009%2 Jan →
cache8–160.0015%12 Nov →
cache6–160.008%29 Sept →

Match data via Leetify.

Recent teammates

Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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