Mitoma

Mitoma — CS2 Stats

76561199568303445[U:1:1608037717]Steam profile ↗✓ No bans

374Tracked matches43%Win rate2024Tracked since
CSDB Rating5.1 DevelopingAll-Rounder
FaceitLevel 6 · 1,200 ELOTop 54.0% of ranked FACEIT players
Ladder ranks via Leetify
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CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. Today is the first observation — history builds from here and cannot be backfilled. Come back after the next session and the change shows above.

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CSDB.GGMitomaFACEITLevel 6 · 1,200 ELOSTANDINGTop 54.0% of rankedcsdb.gg/stats

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Performance scores

Aim69
Positioning53
Utility53

0–100 skill scores via Leetify.

Recent form

COLD51481Last 10051%Win rateLWLWWLLLLL

Last 10 vs previous 10: −30pp win rate · −0.02 avg rating · −4.0pp headshot accuracy · −38ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 32 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 9%
  • Avg reaction 616ms

Last 10

  • 37 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 9%
  • Avg reaction 595ms

Last 20

  • 911 · 45% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 11%
  • Avg reaction 613ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-RounderNo style dimension stands clear of the others in this profile.

Aim6.9
Utility5.3
Positioning5.3
Opening Duels3.8
Clutch3.6

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

jL

Plays most like jL 92% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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. 598ms 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
Positioning5.3
Utility5.3
Mechanics8.1
Opening Duels2.8
Win Impact2.8

Composite 5.1/10 (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 rating-0.01−0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time596ms+3ms
first ⅓ avg 593ms → last ⅓ avg 596ms
Headshot accuracy10.4%−1.2%
first ⅓ avg 11.7% → last ⅓ avg 10.4%

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.

Personal bests

0.15Best match rating · 13–1 · inferno, 14 Jan
39%Best headshot accuracy · 13–1 · inferno, 28 May
328msFastest reaction time · 0–13 · inferno, 29 Aug
13–0Biggest win · mirage, 21 Jun

Across the last 100 tracked matches.

Highlights

6Longest win streak
1111In matches decided by ≤2 rounds
14Overtime games

Map breakdown

anubisBest map · 71% over 7infernoWeakest map · 40% over 25
MapGradePlayedRecordWin rateAvg rating
mirageA27171063%-0.00
infernoC25101540%-0.01
dust2B24121250%-0.01
ancientB115645%-0.03
anubisS75271%0.04
nuke21150%-0.04
train21150%0.02
fistmap1010%-0.03
vertigo1010%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 25). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

353Matches
51%Win rate
1.00Avg K/D
73.5ADR
34%Headshot %

Clutches & streaks

38%1v1 clutch win
21%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage10149%0.9512.8
Dust29653%1.0414.3
Inferno6447%1.0815.4
Anubis3361%1.1014.7
Ancient3145%0.7912.3
Vertigo1173%1.0916.6
Train743%1.0419.3
Nuke743%0.9315.1

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.

10.6%Headshot accuracy
36.8%Accuracy (enemy spotted)
37.2%Spray accuracy
86.2%Counter-strafing
9.2°Preaim
598msReaction time
37.4%T opening success
45.3%CT opening success
0.65Enemies flashed / flash
4.1%Flash assists
7.73HE damage / grenade
17.66Flashes / 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 10.6155% — 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 37.4389% — 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.

40% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
dust219–22-0.0110%6 Jun
nuke16–14-0.0213%4 Jun
mirage11–130.065%28 May
mirage13–11-0.019%25 May
inferno16–120.039%24 May
mirage4–13-0.0910%22 May
inferno11–13-0.0310%13 May
dust28–13-0.044%30 Mar
inferno9–130.0212%28 Feb
ancient9–13-0.0812%27 Feb
ancient7–130.0315%27 Feb
dust213–80.0111%23 Feb
mirage13–11-0.0124%20 Feb
dust29–130.008%18 Feb
mirage11–13-0.0716%18 Feb
dust213–70.0313%15 Feb
anubis13–70.089%13 Feb
dust28–13-0.0214%13 Feb
mirage16–14-0.037%11 Feb
dust213–20.0618%3 Feb
mirage13–50.049%3 Feb
dust213–110.007%1 Feb
inferno10–13-0.0314%1 Feb
ancient3–13-0.039%31 Jan
mirage13–50.019%23 Dec
inferno13–60.0420%16 Dec
dust211–13-0.087%8 Dec
mirage5–13-0.0510%8 Dec
dust29–13-0.035%5 Sept
inferno0–13-0.040%29 Aug
mirage13–80.006%29 Aug
nuke11–13-0.078%29 Jun
anubis13–11-0.0213%28 Jun
inferno1–13-0.055%28 Jun
inferno5–120.006%27 Jun
dust27–7-0.110%27 Jun
dust213–60.0813%22 Jun
mirage13–00.1115%21 Jun
inferno13–7-0.0018%21 Jun
inferno13–10.0139%28 May
inferno12–12-0.0311%23 May
mirage3–13-0.0413%2 Mar
mirage13–7-0.055%25 Feb
ancient16–12-0.0310%25 Feb
inferno3–13-0.043%25 Feb
inferno9–130.0417%21 Feb
dust213–100.0110%21 Feb
mirage13–30.0011%20 Feb
fistmap14–16-0.0312%20 Feb
inferno13–110.019%18 Feb
anubis13–70.1314%18 Feb
dust213–3-0.085%15 Feb
train19–22-0.0015%14 Feb
mirage13–70.0113%14 Feb
mirage14–16-0.0210%11 Feb
anubis13–50.0719%11 Feb
anubis13–60.0313%11 Feb
inferno10–13-0.014%8 Feb
inferno13–10-0.0712%8 Feb
dust24–13-0.0815%2 Feb
ancient13–8-0.0414%25 Jan
anubis10–13-0.011%25 Jan
dust213–110.0310%24 Jan
mirage13–16-0.0112%24 Jan
dust28–130.0210%24 Jan
mirage13–80.1023%24 Jan
mirage13–70.0616%24 Jan
anubis11–130.0311%21 Jan
inferno10–13-0.0410%19 Jan
ancient9–13-0.0313%19 Jan
mirage13–7-0.0310%19 Jan
dust27–13-0.0823%18 Jan
ancient13–80.0014%18 Jan
ancient13–6-0.026%18 Jan
inferno10–13-0.0313%18 Jan
dust28–130.0116%18 Jan
inferno13–8-0.0413%17 Jan
mirage9–13-0.0515%17 Jan
ancient13–7-0.047%16 Jan
inferno13–10.1520%14 Jan
mirage13–80.097%14 Jan
inferno13–5-0.018%14 Jan
dust213–90.0616%13 Jan
train13–60.0414%13 Jan
inferno11–130.0311%12 Jan
dust213–16-0.076%12 Jan
dust213–8-0.0326%11 Jan
mirage15–190.007%9 Jan
mirage13–11-0.039%3 Jan
inferno12–16-0.0514%2 Jan
vertigo3–13-0.0411%25 Dec
ancient9–130.019%24 Dec
dust29–13-0.0616%23 Dec
mirage16–14-0.0314%19 Dec
ancient14–16-0.0511%19 Dec
dust213–10.044%18 Dec
mirage13–10-0.047%18 Dec
inferno13–100.006%17 Dec
mirage8–13-0.0311%17 Dec
inferno11–13-0.0311%16 Dec

Match data via Leetify.

Recent teammates

Milestones

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