Expanding the research of "which countries have the most inflated elo"

With the help of claude sonnet 4.5 (that shortens the prototyping and testing time by a lot) I collected and analyzed the data of the u18 WCh from 2015 to 2019 as follow up of this article https://en.chessbase.com/post/which-countries-have-the-most-inflated-elo-chess-players. Why pre covid? Because then one cannot argue about possible inflation/deflation due to covid measures (IMO the covid rating lag ended around 2023). Additionally I considered the u18 WCh from 2023 to 2025 and the Grand swisses (2019, 2023, 2025). More tournaments may be added later. Of course in the WCh u18 there are likely the best young players of each country, so underrated if anything, but still it gives an idea which countries gain rating as a whole and which don't.

Result directly from the output

================================================================================
EXTRACTION SUMMARY
================================================================================
Total players extracted: 4543
Federations represented: 117
Tournaments covered: 40

Overall statistics:
  Average rating change: +1.01
  Players with gains: 2208 (48.6%)
  Players with losses: 2301 (50.6%)

Top 20 federations by player count:
  IND: 609 players
  RUS: 249 players
  ESP: 209 players
  GER: 198 players
  FRA: 168 players
  USA: 167 players
  ISL: 160 players
  None: 150 players
  CHN: 121 players
  ENG: 105 players
  NOR: 93 players
  UKR: 85 players
  ARM: 83 players
  ITA: 79 players
  KAZ: 75 players
  TUR: 75 players
  ISR: 73 players
  MEX: 71 players
  IRI: 69 players
  SWE: 68 players

 Analyzed 98 federations with 3+ players
 Analyzed 7 continents

==========================================================================================
RATING CHANGES BY CONTINENT
==========================================================================================
NOTE: 'Avg Change' and '% Gainers' are per tournament appearance, not per unique player.
      Same players appearing in multiple tournaments are counted separately.
      Focus on 'Total' change as the most meaningful metric (net rating flow).
------------------------------------------------------------------------------------------
Rank   Continent          Entries   Feds   Avg Change    Total        % Gainers
------------------------------------------------------------------------------------------
1      Asia               1153      28            +5.5       +6352       53.4%
2      Oceania            36        2            +21.3        +766       72.2%
3      Other              245       13            +2.5        +608       51.4%
4      North America      316       8             +1.1        +339       49.7%
5      Africa             71        13            +3.5        +250       50.7%
6      South America      195       10            -5.1        -988       40.5%
7      Europe             2527      44            -1.1       -2718       46.2%

==========================================================================================
ALL FEDERATIONS RANKED BY AVERAGE RATING CHANGE
==========================================================================================
NOTE: 'Avg Change' and '% Gainers' are per tournament appearance, not per unique player.
      Same players appearing in multiple tournaments are counted separately.
      Focus on 'Total' change as the most meaningful metric (net rating flow).
------------------------------------------------------------------------------------------
Rank   Fed    Entries   Avg Change    Total        % Gainers   Avg Rating
------------------------------------------------------------------------------------------
1      IND    609              +4.4       +2679       53.5%        2357
2      TPE    21              +42.5        +892       85.7%        1839
3      NOR    93               +9.1        +843       60.2%        2302
4      CHN    121              +6.6        +794       52.1%        2437
5      FID    50              +12.6        +628       66.0%        2444
6      GRE    39              +15.8        +616       56.4%        2308
7      RSA    26              +20.8        +542       53.8%        2035
8      SRI    20              +25.9        +518       65.0%        1971
9      ISL    160              +3.2        +511       50.0%        2144
10     MEX    71               +6.7        +475       49.3%        1603
11     AUS    31              +15.0        +464       67.7%        2219
12     MGL    36              +12.6        +453       50.0%        2324
13     UZB    60               +6.8        +407       65.0%        2401
14     MAS    16              +19.6        +314       62.5%        2080
15     NZL    5               +60.2        +301      100.0%        1790
16     TUR    75               +3.5        +264       52.0%        2340
17     CAN    60               +3.3        +200       60.0%        2148
18     VIE    16              +12.4        +198       62.5%        2442
19     ALB    6               +29.3        +176       66.7%        2118
20     PHI    13              +12.9        +168       84.6%        2325
21     ECU    6               +26.4        +159       66.7%        2148
22     LBN    3               +50.3        +151      100.0%        1882
23     SGP    23               +6.2        +144       47.8%        2330
24     EST    15               +9.1        +137       46.7%        2365
25     IRL    23               +5.7        +131       60.9%        2125
26     CRO    21               +6.2        +130       61.9%        2486
27     LAT    15               +7.7        +116       53.3%        2269
28     ALG    4               +25.8        +103      100.0%        2184
29     KEN    6               +16.1         +96       66.7%        1934
30     JPN    5               +17.9         +90       40.0%        1766
31     RUS    249              +0.4         +88       47.4%        2539
32     LUX    5               +17.2         +86       80.0%        1962
33     BUL    29               +2.6         +76       62.1%        2429
34     POR    10               +6.6         +66       50.0%        2148
35     TJK    5               +10.2         +51       60.0%        2283
36     HUN    66               +0.7         +49       47.0%        2450
37     MNE    20               +2.4         +47       45.0%        1931
38     FAI    7                +4.4         +31       57.1%        2131
39     KOS    5                +5.6         +28       20.0%        1971
40     KUW    3                +4.9         +15       66.7%        1830
41     GEO    56               +0.3         +15       44.6%        2349
42     MDA    16               +0.3          +5       37.5%        2388
43     KGZ    11               +0.5          +5       54.5%        1873
44     BEL    39               -0.0          -1       51.3%        2218
45     IOM    3                -0.9          -3       33.3%        2210
46     None   150              -0.0          -5       48.7%        2613
47     SRB    37               -0.2          -6       45.9%        2398
48     CHI    25               -0.2          -6       40.0%        2251
49     TKM    7                -1.8         -13       42.9%        2079
50     UKR    85               -0.2         -15       45.9%        2487
51     BLR    16               -1.0         -16       50.0%        2530
52     CRC    3                -6.3         -19       33.3%        2090
53     BAN    5                -4.9         -25       20.0%        2092
54     UAE    13               -2.0         -26       38.5%        2191
55     ENG    105              -0.3         -30       43.8%        2326
56     NGR    3               -11.1         -33       33.3%        2242
57     AZE    47               -0.7         -35       46.8%        2488
58     MRI    3               -13.3         -40       33.3%         552
59     SWE    68               -0.6         -42       44.1%        2331
60     INA    6                -7.6         -45       16.7%        2420
61     HKG    4               -11.5         -46       50.0%        1962
62     CUB    12               -4.0         -48       33.3%        2406
63     ANG    3               -18.0         -54       33.3%        2216
64     ARM    83               -0.7         -57       45.8%        2529
65     LTU    11               -5.4         -60       36.4%        2324
66     VEN    11               -6.1         -67       18.2%        2436
67     PAR    9                -7.9         -71       33.3%        2394
68     WLS    7               -11.1         -78       42.9%        2045
69     SCO    10               -8.4         -84       50.0%        2205
70     BIH    10               -8.7         -87       30.0%        2300
71     COL    24               -3.7         -89       41.7%        2269
72     KAZ    75               -1.4        -102       42.7%        2301
73     MAR    4               -27.3        -109       75.0%        2134
74     MKD    9               -12.3        -111       22.2%        2232
75     NED    64               -1.8        -117       53.1%        2427
76     CYP    6               -20.6        -124       66.7%        1745
77     IRI    69               -2.2        -154       46.4%        2503
78     CZE    33               -5.1        -168       42.4%        2410
79     NEP    4               -45.7        -183       25.0%        1870
80     SLO    31               -5.9        -184       41.9%        2378
81     URU    8               -24.5        -196       37.5%        1829
82     SVK    22               -9.0        -198       45.5%        2342
83     PER    25               -8.3        -208       44.0%        2302
84     ARG    57               -3.8        -216       43.9%        2368
85     EGY    15              -15.2        -228       26.7%        2439
86     USA    167              -1.4        -229       47.9%        2408
87     BRA    29               -8.6        -248       37.9%        2056
88     POL    67               -4.0        -269       44.8%        2454
89     AUT    39               -7.4        -289       33.3%        2374
90     FIN    14              -21.3        -299       42.9%        2001
91     SUI    31              -10.1        -312       29.0%        2275
92     DEN    42               -7.5        -315       50.0%        2231
93     ROU    49               -7.3        -356       40.8%        2413
94     ITA    79               -4.8        -380       41.8%        2260
95     FRA    168              -2.7        -451       40.5%        2408
96     ESP    209              -2.5        -519       48.3%        2348
97     ISR    73               -7.6        -555       32.9%        2443
98     GER    198              -5.1       -1010       41.9%        2372

================================================================================
 Saved 98 records to rating_analysis_results.csv
 Saved 4543 records to rating_data_raw.csv
================================================================================
Analysis complete!
Processed 4543 tournament entries from 40 tournaments
================================================================================

that is, this add support to my hypothesis that states more or less the following:

FIDE statistics from 2023-2025 indicate that India has between 32,000 and 75,000 active rated players. A massive proportion of these are Under-18 (U18) players. The Elo system has a known lag in tracking rapid improvement. A junior player might improve their skill by 200 Elo points in six months through intensive training. However, if they play only one rated tournament in that period, or—crucially—if they play primarily against other underrated juniors, their rating will not reflect this 200-point gain.

In the Indian ecosystem, underrated juniors largely compete against one another. Consider a tournament in Chennai where Player A (rated 1400, strength 1700) plays Player B (rated 1400, strength 1700). The game ends in a draw. The ratings remain 1400. Both players are essentially "smurfing"—carrying a rating far below their true strength. The "National" rating often diverges from the FIDE rating, creating a "heavy" pool where 1400 Elo requires 1700-level skill to maintain.

[...]
Recent analysis of global rating reliability has quantified this disparity. Research indicates that players from South Asia (dominated by India) are, on average, 150 to 250 Elo points underrated relative to a global skill baseline. Conversely, players from older, established European federations like Denmark are often overrated by ~162 points. (I wanted to double check those claims)

Europe (and to a lesser extent, the USA) serves as the "reserve currency" of the FIDE rating system. It has:

1. High Tournament Density: The vast majority of FIDE-rated Open tournaments occur in Europe.
2. Amateur Density: A large population of adult hobbyists who maintain ratings established decades ago.
3. Inflationary Tendency: Older players tend to lose strength faster than their rating decays (due to low K-factors and floors), effectively "storing" points that should have been lost.

When an underrated Indian junior travels to play in the Grand Swiss, Cappelle-la-Grande, or the Gibraltar Masters, they engage in what is essentially rating arbitrage.
The Transaction:

• The Matchup: An Indian Junior (Rated 2100, Strength 2350) vs. A German Amateur (Rated 2300, Strength 2250).
• The Prediction: The Elo formula predicts the German (2300) will score 76% against the 2100 opponent.
• The Reality: The Indian Junior is stronger. The match ends in a Draw or a Win for the Indian.
• The Consequences:
  • For the German: He loses significantly more points than he would losing to a peer. A draw might cost him rating points (since he was expected to win). A loss is catastrophic (-15 to -20 points depending on K-factor).
  • For the Indian: He gains massive points.
  • For the System: The German player is now rated 2280. He goes back to his local club and plays a peer rated 2280. He is still 2250 strength (one bad game didn't change his skill). He beats his peer. The peer loses points. The deflation spreads.

The points gained by the Indian junior are eventually taken back to India. Once there, they are likely lost to another underrated Indian junior. The points essentially vanish into the "black hole" of the deflationary Asian pool, never returning to the European ecosystem.

The mechanism driving the Asian Deflation (Geographic Isolation) is mathematically identical to the mechanism driving Rapid/Blitz Deflation (Format Isolation/Inactivity).

1. Isolation: Just as Chinese players don't play enough international games to normalize their ratings, top Grandmasters often don't play enough FIDE-rated Blitz tournaments to normalize their speed ratings. They play online (Speed Chess Championship, Titled Tuesday) which does not affect FIDE ratings.
2. Inertia: The K-factor (rating volatility) drops to 10 for elites. To gain 100 points, a player must massively outperform expectations over a long period. If they play only one Blitz tournament a year, their rating remains "frozen" in the past.
3. The "Heavy" Asset: This results in a player having a rating (e.g., 2600) that is far below their current skill level (e.g., 2800).

python code here .