TESLA TO THE MOON

TESLA TO THE MOON — CS2 Stats

76561198126032712[U:1:165766984]Steam profile ↗✓ No bans

2,085Tracked matches46%Win rate2020Tracked since
3,302Hours in CS0Hrs last 2 wks
CSDB Rating4.8 DevelopingPositional Player
FaceitLevel 6Top 54.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 21 Sep 2026 (15 days ago). Ranks are recorded once per day this page is viewed.

+2Tracked matches · now 2,085
0.0ppWin rate · 46.4% → 46.4%

Rating over time

Premier CS Rating: 17,535 +877 19 Feb – 1 Jul · 31 days played
15,93519,682peak 19,68219 Feb1 Jul
19,682Peak Premier in tracked matches
51Days played since 2026-01-30

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches4——
Win rate50%——
K/D1.07——
Headshot %45%——

Measured 2 Sep 2026 → 6 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 6 among CSDB-tracked players (n=12,879), 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 6 medianLevel 7 medianvs Level 7
Headshot rate38.0%44.8%45.7%7.7% short
Shot accuracy16.9%12.4%12.7%above
Kill/death ratio1.011.031.050.04 short
Match win rate48.8%45.2%45.7%above

This profile matches the typical Level 7 player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 7 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGTESLA TO THE MOONFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim60
Positioning48
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY47–48–5Last 10047%Win rateLWTWWWTLLW

Last 10 vs previous 10: 0pp win rate · −0.02 avg rating · −2.0pp headshot accuracy · −49ms 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

  • 3–1–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 20%
  • Avg reaction 569ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 603ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 627ms

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: Positional Player — Positioning stands above the rest of this profile (+2 against its own average).

Aim6.0
Utility4.5
Positioning4.8
Opening Duels1.9
Clutch0.0

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 88% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 652ms 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

Aim6.0
Positioning4.8
Utility4.5
Mechanics5.4
Opening Duels1.5
Win Impact3.8

Composite 4.8/10 (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-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time645ms+8ms
first ⅓ avg 637ms → last ⅓ avg 645ms
Headshot accuracy17.8%−1.0%
first ⅓ avg 18.8% → last ⅓ avg 17.8%

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

0.11Best match rating · 13–5 · dust2, 12 Mar →
75%Best headshot accuracy · 0–5 · dust2, 3 Apr →
438msFastest reaction time · 13–7 · inferno, 22 Sept →
13–3Biggest win · mirage, 25 Aug →

Across the last 100 tracked matches.

Highlights

10Longest win streak
12–7In matches decided by ≤2 rounds
9Overtime games

Map breakdown

infernoBest map · 71% over 21ancientWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
dust2B3817–2145%-0.01
infernoS2115–671%-0.00
mirageC166–1038%-0.04
ancientD144–1029%-0.02
anubisB63–350%-0.03
nuke—31–233%-0.01
overpass—10–10%0.02
cache—11–0100%0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

91,900Lifetime kills
1.01K/D
4,948Matches
48.8%Match win rate · Top 25% of Level 6 players
38.0%Headshot %
16.9%Shot accuracy · Top 25% of Level 6 players
10,744MVPs
2,168Hours (in match)
4,477Bombs planted
795Bombs defused

Most-used weapons

AWP25,512
AK-4722,300
FAMAS2,391
Tec-91,613
MAC-101,575

Lifetime map wins

27,061inferno
12,425dust2
649nuke
308vertigo
248train
68cbble
54office
28safehouse

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

Faceit stats

Combat

154Matches
55%Win rate
1.12Avg K/D
64.9ADR
37%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWLWL

MapMatchesWin rateAvg K/DAvg kills
Ancient20%0.8414.5
Inferno1100%0.9314.0
Mirage1100%0.6210.0

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.

18.4%Headshot accuracy
35.0%Accuracy (enemy spotted)
35.2%Spray accuracy
74.2%Counter-strafing
9.6°Preaim
652msReaction time
34.5%T opening success
37.2%CT opening success
0.56Enemies flashed / flash
5.0%Flash assists
8.33HE damage / grenade
5.86Flashes / 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 34.5424% — 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.

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust23–13-0.0530%22 Sept →
inferno13–70.0415%22 Sept →
dust212–12-0.0316%19 Sept →
dust213–110.0425%19 Sept →
ancient13–70.0313%25 Aug →
mirage13–3-0.0610%25 Aug →
inferno15–15-0.0316%7 Aug →
dust29–13-0.0225%28 Jul →
ancient1–6-0.060%28 Jul →
anubis13–6-0.044%28 Jul →
mirage3–130.0126%24 Jul →
ancient16–130.0314%24 Jul →
inferno4–13-0.0229%24 Jul →
dust211–13-0.0215%14 Jul →
dust213–9-0.0111%9 Jul →
inferno13–10-0.0210%1 Jul →
mirage11–13-0.0419%1 Jul →
dust27–13-0.0113%1 Jul →
mirage13–8-0.0014%30 Jun →
mirage13–110.0825%30 Jun →
mirage7–13-0.047%27 Jun →
mirage13–90.0014%27 Jun →
dust27–13-0.0436%26 Jun →
dust213–6-0.0317%25 Jun →
ancient1–13-0.0827%25 Jun →
inferno13–8-0.0334%25 Jun →
anubis8–130.0113%24 Jun →
dust211–13-0.0623%24 Jun →
anubis7–13-0.0118%23 Jun →
mirage5–13-0.0933%23 Jun →
inferno13–8-0.0410%22 Jun →
mirage2–13-0.0424%22 Jun →
inferno13–8-0.043%22 Jun →
mirage5–13-0.048%22 Jun →
inferno13–30.0714%21 Jun →
dust27–13-0.054%21 Jun →
dust28–13-0.052%21 Jun →
dust25–13-0.0311%16 Jun →
mirage13–11-0.0412%16 Jun →
inferno13–11-0.0322%7 Jun →
anubis6–13-0.0513%7 Jun →
dust213–110.0524%6 Jun →
dust29–13-0.0118%5 Jun →
mirage16–13-0.0412%5 Jun →
ancient11–13-0.0318%4 Jun →
overpass6–130.0230%3 Jun →
ancient2–9-0.0429%3 Jun →
ancient5–130.0413%2 Jun →
dust215–150.0011%2 Jun →
anubis13–11-0.079%2 Jun →
ancient11–130.0217%1 Jun →
nuke13–11-0.0111%29 May →
ancient13–11-0.0121%29 May →
dust215–150.0134%28 May →
nuke3–130.0429%28 May →
dust210–130.0111%27 May →
mirage6–13-0.042%19 May →
inferno2–30.0316%18 May →
dust210–13-0.0411%18 May →
dust213–9-0.0317%16 May →
cache13–100.0226%16 May →
ancient8–130.0218%16 May →
nuke4–13-0.0619%16 May →
inferno13–40.0618%5 May →
dust213–100.0516%5 May →
inferno13–90.0119%5 May →
inferno10–13-0.0224%21 Apr →
ancient5–13-0.0917%21 Apr →
dust213–10-0.0325%17 Apr →
inferno10–13-0.0516%17 Apr →
dust210–130.0723%3 Apr →
mirage0–13-0.0917%3 Apr →
mirage4–13-0.0727%3 Apr →
dust20–5-0.0175%3 Apr →
dust213–11-0.0317%27 Mar →
ancient4–13-0.0818%27 Mar →
anubis13–8-0.0224%21 Mar →
dust213–6-0.0219%21 Mar →
inferno13–60.0219%20 Mar →
dust21–7-0.0410%20 Mar →
inferno8–13-0.0417%18 Mar →
dust213–50.1122%12 Mar →
dust213–90.0129%2 Mar →
dust23–130.096%2 Mar →
dust213–7-0.0714%28 Feb →
dust29–13-0.0516%27 Feb →
inferno13–7-0.008%27 Feb →
ancient13–10-0.0415%27 Feb →
dust213–110.0420%25 Feb →
inferno13–110.028%20 Feb →
dust213–90.0013%20 Feb →
inferno13–10-0.017%19 Feb →
dust213–5-0.0118%16 Feb →
inferno13–110.017%15 Feb →
dust213–4-0.0319%15 Feb →
dust216–120.0220%6 Feb →
dust215–150.0321%6 Feb →
inferno16–120.0417%2 Feb →
mirage5–13-0.0612%30 Jan →
ancient14–160.0123%30 Jan →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.