esaag

esaag — CS2 Stats

AU76561198039485101[U:1:79219373]Steam profile ↗

2,080Tracked matches60%Win rate2020Tracked since
4,409Hours in CS
CSDB Rating4.7 Developing
FaceitLevel 9 · 1,888 ELOTop 20.7% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=218), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 10 medianvs Level 10
Headshot rate52.4%52.8%meets
Shot accuracy16.2%13.7%above
Kill/death ratio0.831.080.25 short
Match win rate42.7%49.2%6.5% short

This profile matches the typical Level 10 player on 2 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGesaagFACEITLevel 9 · 1,888 ELOSTANDINGTop 20.7% of rankedcsdb.gg/stats

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Performance scores

Aim58
Positioning41
Utility47

0–100 skill scores via Leetify.

Recent form

STEADY5248Last 10052%Win rateWWLWWLLLWW

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

Aim5.8
Aggression5.2
Utility4.7
Positioning4.1
Opening Duels1.9
Clutch3.4

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

NiKo

Plays most like NiKo 85% playstyle similarity

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

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. 597ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.8
Positioning4.1
Utility4.7
Mechanics4.2
Opening Duels1.9
Win Impact8.3

Composite 4.7/10 (Developing), 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 rating-0.00+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.00
Reaction time602ms+10ms
first ⅓ avg 592ms → last ⅓ avg 602ms
Headshot accuracy17.4%−0.1%
first ⅓ avg 17.4% → last ⅓ avg 17.4%

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.

Highlights

0.08Best rating — inferno 13–7
131Biggest win — nuke
5Longest win streak
W2Current streak
79In matches decided by ≤2 rounds
14Overtime games

Map breakdown

nukeBest map · 57% over 23trainWeakest map · 43% over 7
MapGradePlayedRecordWin rateAvg rating
nukeA23131057%0.00
ancientB22101245%-0.01
infernoB22111150%0.00
anubisB158753%0.01
overpassB84450%-0.01
trainC73443%0.01
dust2220100%-0.01
jura110100%-0.06

Across the last 100 tracked matches.

Lifetime stats

144,520Lifetime kills
0.83K/D
5,234Matches
42.7%Match win rate
52.4%Headshot % · Top 25% of tracked players
16.2%Shot accuracy · Top 25% of tracked players
11,254MVPs
4,409Hours (in match)
2,600Bombs planted
1,068Bombs defused

Most-used weapons

AK-4763,903
AWP7,655
FAMAS2,581
MAC-102,440
Knife2,091

Lifetime map wins

10,811inferno
6,969nuke
2,839vertigo
2,689train
1,182dust2
179cbble
123assault
123lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

2,162Matches
50%Win rate
0.99Avg K/D
81.0ADR
45%Headshot %

Clutches & streaks

37%1v1 clutch win
21%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Ancient26948%1.0416.1
Nuke18152%1.0716.1
Anubis16645%1.0416.1
Inferno15550%1.0215.4
Vertigo6247%0.9914.7
Overpass5852%1.0317.1
Train5254%0.9915.8
Mirage1250%1.0515.3

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.

17.4%Headshot accuracy
35.0%Accuracy (enemy spotted)
41.0%Spray accuracy
68.9%Counter-strafing
11.4°Preaim
597msReaction time
32.6%T opening success
42.3%CT opening success
0.55Enemies flashed / flash
7.9%Flash assists
10.35HE damage / grenade
4.48Flashes / 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. 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 32.5667% — below the 40% mark we flag

Spend your practice time on Train

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

43% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
ancient13–10-0.0322%10 Jun
overpass13–50.0117%4 May
inferno7–13-0.066%12 Apr
anubis13–110.0620%5 Apr
inferno13–70.0817%21 Mar
ancient14–16-0.036%15 Mar
anubis3–13-0.0311%12 Mar
ancient13–16-0.0116%7 Mar
nuke13–10.0426%2 Mar
nuke13–110.0126%24 Feb
anubis9–130.0115%3 Feb
dust213–6-0.0622%2 Feb
dust213–100.0420%2 Feb
nuke6–130.0121%10 Jan
overpass13–80.0210%2 Jan
inferno13–60.006%2 Jan
overpass13–90.0015%28 Dec
overpass15–19-0.0219%15 Dec
inferno13–40.0118%4 Dec
overpass10–130.0120%4 Dec
ancient10–13-0.0514%11 Nov
train9–130.0537%20 Oct
nuke13–6-0.0821%15 Oct
ancient13–60.0527%15 Oct
overpass13–9-0.0420%15 Oct
inferno6–13-0.0911%13 Oct
train13–50.0219%13 Oct
nuke13–3-0.0618%13 Oct
ancient13–80.019%13 Oct
ancient10–130.0217%6 Oct
nuke9–13-0.0315%28 Sept
ancient13–8-0.0116%28 Sept
overpass20–22-0.0316%18 Sept
overpass5–13-0.0323%22 Jul
inferno19–150.0615%8 Jul
anubis14–16-0.0414%10 Jun
nuke13–100.0324%9 Jun
inferno13–8-0.0217%9 Jun
anubis7–130.0227%9 Jun
ancient6–130.0627%9 Jun
inferno11–130.0117%9 Jun
ancient2–130.0022%9 Jun
nuke13–100.0319%9 Jun
anubis13–30.0726%9 Jun
jura13–7-0.0647%9 Jun
inferno6–130.0012%6 Jun
nuke13–70.0415%6 Jun
inferno11–130.0527%5 Jun
nuke13–10-0.0121%1 Jun
ancient7–130.0122%31 May
nuke4–130.0139%30 May
anubis7–130.0127%30 May
inferno9–13-0.0319%30 May
ancient13–90.0212%29 May
nuke11–130.0211%29 May
inferno16–130.0418%29 May
anubis13–50.0115%27 May
nuke9–130.0211%27 May
inferno10–13-0.039%27 May
inferno9–13-0.078%27 May
train6–130.0511%27 May
nuke2–13-0.1110%27 May
ancient14–160.0013%26 May
anubis22–190.0219%26 May
ancient11–13-0.0116%26 May
anubis13–70.0411%26 May
inferno10–130.0214%25 May
ancient13–5-0.0220%25 May
nuke13–80.0116%25 May
nuke6–130.0221%24 May
ancient13–110.0114%23 May
nuke13–100.0521%23 May
ancient14–16-0.0120%23 May
nuke13–80.0424%23 May
inferno13–110.0522%22 May
anubis8–13-0.0420%22 May
train13–7-0.0127%22 May
anubis13–16-0.0517%22 May
ancient8–13-0.0719%21 May
train9–13-0.0313%21 May
anubis13–10-0.0219%21 May
inferno4–13-0.0819%21 May
ancient13–110.0220%21 May
anubis13–4-0.0010%20 May
ancient13–50.0214%20 May
inferno13–10-0.0224%20 May
nuke8–130.0027%19 May
inferno22–200.0017%19 May
nuke13–100.033%18 May
train13–9-0.0219%18 May
anubis13–70.0819%17 May
nuke13–60.0519%17 May
ancient1–13-0.133%17 May
inferno13–16-0.0014%17 May
train8–13-0.025%17 May
nuke9–130.0111%16 May
ancient13–10-0.0525%16 May
inferno13–90.0322%15 May
nuke5–13-0.0518%15 May
inferno16–140.0214%14 May

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →