About bots online

I had long conversation with AI about bots playing online not only cheating  people in short AI created pdf .If you want read and comment , without being rude 😁.

A Detailed Analysis of the Chess.com Rating System, Player Categories, and Bot Usage for

Extreme Skill Cases

1. Introduction

Chess.com uses Elo/Glicko-based ranking to stabilize win rates around 50% for normal players.

This document focuses on the 'Extreme Skill' group, such as smurfs, speedrunners, and Youtuber

experiments, and explains how bots are used to handle scenarios where human opponents are

insufficient.

2. Normal Players (Casual)

- Approximately 50% win rate.

- Normal matchmaking pools.

- Never matched with bots.

- Provisional rating adjusts quickly in early games to stabilize player skill perception.

3. Titled Players

- Includes GMs, IMs, FMs, CMs, WGM, etc.

- More flexible matchmaking and win rate tolerance.

- Sometimes face human or bot opponents based on pool needs.

- Used as anchors for rating stability and marketing purposes.

4. Extreme Skill / Smurf / Speedrunner Group

Characteristics:

- Very high skill but playing on a new or low-rated account.

- Often used for speedrun attempts or Youtuber experiments.

- Extreme disparity between real skill and provisional rating (., 2500 real skill starting at 100 Elo).

Problems in Normal Matchmaking:

- Very few human opponents exist at the appropriate skill level.

- Provisional rating system imposes a ceiling (~1600-1800) to stabilize pool perception.

- Win streaks would otherwise rapidly distort rating for new accounts.System Solution:

- Bots are introduced to simulate human opponents proportionally to the player's skill.

- Bots allow continuous rating growth without ceiling in this special mode.

- Normal players are unaffected; bots only appear for extreme skill cases.

- Player can maintain high win rate in practice or experiment without destabilizing casual pool.

Behavior Examples:

- Consistent streaks against simulated opponents.

- Opponents behaving like human players, but calibrated to prevent rating inflation in normal

matchmaking.

- Used to test strategies, openings, or for speedrun content.

5. Player Categories and Bot Usage Diagram

Diagram Explanation:

- Casual Players: normal matchmaking, no bots, ~50% win rate.

- Titled Players: flexible matchmaking, may face bots occasionally.

- Extreme Skill / Smurf / Speedrunners: bots introduced only when human opponents are

insufficient, no ceiling, rating grows naturally.

6. Conclusion

Bots on Chess.com exist **only for extreme skill cases** to handle scenarios where there are

insufficient human opponents.

This ensures fair gameplay for normal players, maintains rating stability, and allows high-skill

experiments or speedruns without artificially limiting rating growth.

It has begun

It not about bots it’s about system not only here, not only in chess .
That kind of systems here elo is like money and has to be balanced, it “promotes” ordinary people(50% win rate and if you have to much you will be punished until you go down to 50% .

Ah, da holy 50% win rate nobody can escape

I’m not saying nobody but statistically is like that,check your opponents if you are not titled player.

Last thing to mention:

50% win rate is like flip coins: tail,head random results not related to your knowledge .

To get proper elo here you need to start playing with

fide in real clubs and get real ratings otherwise you will be here like Don Kichot from M.Cervantes book.

I just dont understand why these 50% are considered some sacred value, it is simply one of the outcomes of a particular rating estimation algorithm, while you keep studying chess faster and better than your opponents do within the same chess community your win rate is higher than 50%

There is no such a thing as "proper elo" or "real elo", as a member of different chess communities you have different ratings that show your rank within these communities and are valid within these communities only, there is no absolute chess rating

In Elo it’s about inflation and deflation.

Explanation 

Elo Inflation and Why Non-Titled Players Are Deflated on Chess.com

1. What Elo inflation is

Elo inflation is the long-term upward drift of average ratings in a closed rating system, even when the true playing strength of the population does not increase at the same rate.

In practice:

• A rating like 2000 today does not represent the same percentile or strength it did years ago
• The rating scale loses its original meaning unless corrected

This effect is well documented in both FIDE and online chess platforms, and it is stronger online.

2. Why Elo inflation happens

a) Continuous influx of new players

• New players enter the system with a preset rating
• On average, they lose more points than they gain
• Those points move upward through the rating pool

b) Asymmetric player exit

• Lower-rated players quit more often
• High-rated players are more persistent
• Rating points remain trapped near the top

c) High game volume and fast time controls

• Online chess produces millions of games
• Variance and short time controls amplify rating noise

d) Knowledge inflation without scale recalibration

• Engines, databases, and training content raise average play
• The rating scale is not automatically rescaled

Result: rating mass accumulates at higher levels.

3. How rating inflation is corrected (in general)

Rating systems apply corrections system-wide, not per player.

1) K-factor reduction

• Lower K for higher ratings and established players
• Slows rating movement at the top

2) Lower starting ratings

• Fewer points injected into the system
• Often combined with provisional ratings

3) Global re-centering (deflation)

• Shifting the entire rating distribution downward
• Rare, but mathematically effective

4) Floors and caps

• Prevent extreme drops or gains
• Improve stability but distort distribution

5) Glicko / Glicko-2 systems

• Add rating deviation and volatility
• Misrated players move fast; stable ones move slowly
• Inflation becomes partially self-correcting

6) Separate rating pools

• Bullet, Blitz, Rapid are isolated
• Prevent cross-format rating leakage

4. Why Chess.com deflates 

non-titled players

This is the key question.

Titled players are the rating anchor

Grandmasters and other titled players:

• Have externally verified strength (FIDE, OTB play)
• Provide a fixed reference point for the rating scale

If non-titled players drift upward unchecked:

• They converge toward titled ratings
• Without equivalent real-world strength
• The scale loses meaning

Deflating non-titled players preserves the anchor.

Non-titled players generate almost all inflation

Statistically:

• ~99% of games are NT vs NT
• Most new accounts are non-titled
• Most abandoned accounts are non-titled

This group:

• Injects rating points
• Pushes them upward
• Creates inflation pressure

Titled players:

• Play fewer games
• Have lower K
• Are already tightly calibrated

Inflation is produced below, not at the top.

Rating protection for titled players is necessary

Chess.com:

• Verifies titles
• Runs prize tournaments
• Uses ratings for elite matchmaking

If a GM could lose large rating chunks to random 2300 NT players:

• The rating would become unreliable
• Competitive integrity would suffer

It is statistically safer to:

➡️ compress and deflate the mass

➡️ than destabilize the elite

Deflation is gradual, not punitive

Deflation does not mean:

• sudden rating cuts
• arbitrary losses

It means:

• smaller gains for wins
• larger losses for defeats
• slower upward movement

The player experiences:

• plateaus
• not crashes

All alternatives are worse

Other options:

• Deflate titled players → PR disaster
• Global rating reset → user backlash
• Let inflation run → rating meaningless

Deflating non-titled players is:

• the least visible
• the least disruptive
• the most statistically efficient solution

5. The hard truth

If you are not titled, the system treats you as part of the statistical mass, not as a calibration reference.

This is not punishment.

It is scale maintenance.

6. What this means in practice

• Above ~2000–2200 on Chess.com:
  • Rating gains increasingly reflect real skill
  • Not volume or variance
•  
• Stagnation ≠ regression
• Percentiles are more meaningful than raw Elo

If you want, next we can:

• model Chess.com’s deflation mathematically
• compare Chess.com vs Lichess numerically
• analyze whether a given rating climb is inflation-driven or skill-driven

That’s where rating system engineering really begins ♟️

One of the conclusion:

Unrated players are nesesery because of money,they can buy membership and keep the game alive,

but they are big problem for elo ratings(more than cheaters)

so they have to be under control like sheeps.

Another one is anty cheating system for unrated players is not nesesery if proper deflation algorithms working,

they will find cheaters(or generaly non ordinary players),

isloate them by using bots and let them play with strong opponents with low elo

(bots consume their elo and disappear and if non ordinary players are strong cheaters they will be banned and disappear together with selected bots).

There is different situation for titled players but this is another story.