Replay Analysis Part 5: Nation

Welcome to Part 5 of my Replay Analysis where I analyse tens of thousands of replays sent to me by you!

Thank you to those of you who have recently sent me more replays. I now have around 90,000 of them, but because this part of the analysis was already being written when you sent me the replays, the total number of replays analysed for this part is 66,849. Of those, 50,253 were Standard, Random Battles, which are the only replays to be analysed.

All of the new replays will be used after Part 6: Range, as I am already part way through writing that too. After part 6, I will return to everything from “phase 1” with updated values and continuity. If you would like to send me your replays, thank you! You can find details here.


Of the 50,253 Standard, Random Battles, 29,475 were played on the EU Region and 20,778 on NA.

U.S.A was the most popular nation, with 21.61% of all battles, and Czechoslovakia the least popular with only 1.85% of all battles.

Nation by Server - Click to Expand


How do I define Matchmaking Spread? - Click to expand

There are six possible spreads: -2, -1, -1/+1, =, +1 and +2. At all times during the analysis, -2 means in the replay analysed, the player was bottom tier by two; -1: bottom tier by one; -1/+1: mid tier; =: same tier; +1: top tier by one; and +2: top tier by two. For example, -2 could mean the player was in their Tier 8 vehicle matched with Tier 9's and 10's and = could mean the player was in their Tier 6 vehicle matched with only Tier 6's.

By coincidence, there are six main colors in XVM: Red, Orange, Yellow, Green, Cyan and Purple. In the infographics, the spreads will be colored the same for continuity: -2: Red, -1: Orange, -1/+1: Yellow, =: Green, +1: Cyan and +2: Purple.

Unique Conditions

In Random Battles, it is not possible for:

  • Tier 1 to be +1
  • Tier 1, 2, and 3 to be -2, -1/+1, or +2
  • Tier 10 to be -1 or -1/+1
  • Tier 9 and 10 to be -2

Low tiers do not play on every map. Wargaming change the map rotation every so often and don't shout about it, making it very difficult to separate these battles from the data. However, I feel this is not vitally important, as the focus is likely to be on Tier 6 and above.

The least common spread for each nation was:

  • China: +2 (26.73% of all Chinese Battles were of +2 Spread)
  • Czechoslovakia: +2 (8.48%)
  • France: +2 (7.50%)
  • Germany: -1 / +1 (6.57%)
  • Italy: +2 (7.18%)
  • Japan: -2 (8.95%)
  • Poland: +2 (7.32%)
  • Sweden: +2 (9.81%)
  • U.K.: -1 / +1 (7.50%)
  • U.S.A: -2 (5.87%)
  • U.S.S.R: -1 / +1 (6.64%)

Equal matchmaking was the most common for all Nations:

  • China: 29.22% (of all Chinese Battles were of Equal Spread)
  • Czechoslovakia: 26.18%
  • France: 35.42%
  • Germany: 35.08%
  • Italy: 31.80%
  • Japan: 35.01%
  • Poland: 33.82%
  • Sweden: 27.22%
  • U.K.: 35.95%
  • U.S.A: 36.22%
  • U.S.S.R: 41.84%

I find the least common data very interesting. At this stage we must consider the impact Tier 10 SPG's have on the data. As I've pointed out in previous parts of this analysis, a considerable amount of submitted replays were from the NA region in Tier 10 SPG's. Whilst this doesn't effect the data if we're not looking at SPG data, it does effect results like this. It is not possible for Tier 10 to be in a battle with -1 /+1, -1 or -2 spread, and when we consider most Tier 10 battles were in SPG's, we can see how the spread may not show a true value for SPG's overall. So, when we see the least common Spreads for Germany, U.S.A and U.S.S.R being Spreads that are not possible in Tier 10 SPG's, we can understand that these results may not be a true representation for that nation. However, the least common spread for Japan was -2 (8.95% of all Japanese Battles were of -2 spread) - Japan does not have SPG's, so this Nation stands out among the rest.

If we transpose the data, putting the Spread first, the least common Nation for each spread was:

  • -2: Czechoslovakia (1.60% of all -2 Spread Battles were in Czechoslovakian Vehicles)
  • -1: Poland (1.90%)
  • -1 / +1: Poland (1.40%)
  • =: Czechoslovakia (1.37%)
  • +1: Poland (1.01%)
  • +2: Poland (0.87%)

And the most common Nation for each spread:

  • -2: U.S.S.R (18.71% of all -2 Spread Battles were in Soviet Vehicles)
  • -1: Germany (21.80%)
  • -1 / +1: U.S.A (20.17%)
  • =: U.S.A (22.14%)
  • +1: Germany (26.20%)
  • +2: U.S.A: (36.51%)

The most common data supports the argument surrounding Tier 10 SPG's.


The most common Nation for each Tier was:

  1. Germany (52.38% of all Tier 1 Battles were in German vehicles)
  2. U.S.A (53.74%)
  3. Germany (52.62%)
  4. Germany (74.39%)
  5. Germany (46.86%)
  6. U.S.S.R (29.87%)
  7. Germany (26.26%)
  8. Germany (16.16%)
  9. U.S.A (24.25%)
  10. U.S.A (33.18%)

The least common Nation for each Tier was:

  1. China and U.S.S.R (equally, 4.76% of all Tier 1 Battles were in Chinese Vehicles and 4.76% of all Tier 1 Battles were in Soviet Vehicles)
  2. Japan (3.40%)
  3. Czechoslovakia (0.15%)
  4. France (0.73%)
  5. Poland (0.35%)
  6. Italy (0.25%)
  7. Japan (1.33%)
  8. Czechoslovakia (1.38%)
  9. Poland (0.58%)
  10. China (0.39%)

If we transpose the data to put the Nation first, The most common Tier for each Nation was:

  • China: Tier 8 (51.37% of all Chinese Battles were at Tier 8)
  • Czechoslovakia: Tier 9 (35.62%)
  • France: Tier 8 (35.27%)
  • Germany: Tier 10 (35.39%)
  • Italy: Tier 8 (68.88%)
  • Japan: Tier 10 (34.21%)
  • Poland: Tier 8 (61.12%)
  • Sweden: Tier 9 (32.70%)
  • U.K.: Tier 10 (33.17%)
  • U.S.A.: Tier 10 (54.23%)
  • U.S.S.R: Tier 10 (44.99%)

And the least common Tier for each Nation (ignoring Tier 1-5) was:

  • China: Tier 10 (2.59% of all Chinese Battles were at Tier 10)
  • Czechoslovakia: Tier 6 (9.12%)
  • France: Tier 7 (6.10%)
  • Germany: Tier 6 (4.75%)
  • Italy: Tier 6 (0.91%)
  • Japan: Tier 7 (3.82%)
  • Poland: Tier 6 (5.33%)
  • Sweden: Tier 7 (6.19%)
  • U.K.: Tier 7 (4.93%)
  • U.S.A: Tier 6 (5.93%)
  • U.S.S.R.: Tier 7 (2.52%)

When it comes to looking at map data, the heatmap is better represented as a percentage of the Nation's total games:

Using the heatmap we can see the outliers with the most and least common maps, but we can break it down further on a per nation / per map basis:

The most common map for each Nation was:

  • China: Serene Coast (3.69% of all Chinese Battles were on Serene Coast)
  • Czechoslovakia: Glacier (4.20%)
  • France: Live Oaks (3.44%)
  • Germany: Mines (4.78%)
  • Italy: Highway (4.12%)
  • Japan: Live Oaks (4.07%)
  • Poland: Live Oaks (4.07%)
  • Sweden: Fjords (3.52%)
  • U.K.: Abbey (4.51%)
  • U.S.A.: Mountain Pass (3.63%)
  • U.S.S.R.: Mountain Pass (3.75%)

The least common map for each Nation was:

  • China: Himmelsdorf (1.56% of all Chinese Battles were on Himmelsdorf)
  • Czechoslovakia: Berlin (1.10%)
  • France: Himmelsdorf (1.44%)
  • Germany: Berlin (0.97%)
  • Italy: Ensk (1.07%)
  • Japan: Berlin (1.02%)
  • Poland: Ghost Town (1.08%)
  • Sweden: Himmelsdorf (1.34%)
  • U.K.: Pearl River (1.63%)
  • U.S.A.: Berlin (0.91%)
  • U.S.S.R.: Berlin (1.39%)

If we transpose the data, putting the Map first, the most common Nation for each Map was:

  • Abbey: Germany (22.62% of all Battles on Abbey were in German vehicles)
  • Airfield: U.S.A (24.10%)
  • Berlin: U.S.S.R (17.11%)
  • Cliff: U.S.A (24.38%)
  • El Hallouf: U.S.A (22.51%)
  • Empire's Border: Germany (18.97%)
  • Ensk: Germany (31.10%)
  • Erlenberg: U.S.A (22.75%)
  • Fisherman's Bay: U.S.A (22.18%)
  • Fjords: U.S.A (24.58%)
  • Ghost Town: U.S.A (20.20%)
  • Glacier: U.S.A (22.25%)
  • Highway: U.S.A (21.68%)
  • Himmelsdorf: U.S.A (23.56%)
  • Karelia: Germany (21.71%)
  • Kharkov: U.S.S.R (21.52%)
  • Lakeville: Germany (27.46%)
  • Live Oaks: U.S.A (22.58%)
  • Malinovka: Germany (20.19%)

  • Mannerheim Line: Germany (26.68%)
  • Mines: Germany (31.37%)
  • Minsk: Germany (21.38%)
  • Mountain Pass: U.S.A (24.00%)
  • Murovanka: U.S.A (23.33%)
  • Overlord: U.S.A (23.03%)
  • Paris: U.S.A (23.84%)
  • Pearl River: U.S.S.R (20.60%)
  • Pilsen: U.S.A (19.78%)
  • Prohorovka: U.S.A (22.53%)
  • Redshire: U.S.A (21.64%)
  • Ruinberg: Germany: (28.42%)
  • Sand River: U.S.A (23.19%)
  • Serene Coast: U.S.A (22.29%)
  • Siegfried Line: U.S.A (22.76%)
  • Steppes: Germany (27.16%)
  • Studzianki: U.S.A (20.86%)
  • Tundra: U.S.A (24.61%)
  • Westfield: U.S.A (24.26%)

And the least common Nation for each Map was:

  • Abbey: Japan (1.33% of all Battles on Abbey were in German vehicles)
  • Airfield: Czechoslovakia (1.58%)
  • Berlin: Czechoslovkia (1.40%)
  • Cliff: Poland (1.55%)
  • El Hallouf: Poland (0.91%)
  • Empire's Border: Japan (1.65%)
  • Ensk: Poland (1.06%)
  • Erlenberg: Poland (1.47%)
  • Fisherman's Bay: Poland (1.28%)
  • Fjords: Poland (1.35%)
  • Ghost Town: Poland (0.99%)
  • Glacier: U.S.A Poland (1.30%)
  • Highway: Poland (1.54%)
  • Himmelsdorf: Japan (1.54%)
  • Karelia: Poland (1.47%)
  • Kharkov: Poland (1.46%)
  • Lakeville: Germany Czechoslovakia (1.01%)
  • Live Oaks: Poland (1.89%)
  • Malinovka: Poland (1.02%)

  • Mannerheim Line: Poland (1.75%)
  • Mines: Japan (1.51%)
  • Minsk: Czechoslovakia (1.22%)
  • Mountain Pass: Italy (1.48%)
  • Murovanka: Japan (1.82%)
  • Overlord: Poland (1.13%)
  • Paris: Czechoslovakia (1.81%)
  • Pearl River: Czechoslovakia (1.74%)
  • Pilsen: Poland (1.56%)
  • Prohorovka: Poland (1.23%)
  • Redshire: Poland (1.28%)
  • Ruinberg: Poland (1.18%)
  • Sand River: Poland (1.21%)
  • Serene Coast: Japan (1.43%)
  • Siegfried Line: Poland (1.51%)
  • Steppes: Poland (1.19%)
  • Studzianki: Poland (1.11%)
  • Tundra: Poland (0.89%)
  • Westfield: Poland (1.37%)


The Range is better visualised if we rank the table from lowest to highest:

Let's explore the four most common ranges: -8, -9, +8 and +9.

Czechoslovakia was the most likely to have a Range of -8 (6.42% of all Czechoslovakian battles were of -8 Range), whereas Japan was the least likely (4.77%).

Poland was the most likely to have a Range of -9 (6.71% of all Polish battles were of -9 Range), whereas Czechoslovakia was the least likely (4.69%).

Japan was the most likely to have a Range of +8 (6.52% of all Japanese battles were of +8 Range), whereas Czechoslovakia was the least likely (4.86%).

Czechoslovakia was the most likely to have a Range of +9 (7.29% of all Czechoslovakian battles were of +9 Range), whereas Japan was the least likely (4.77%).


The most common duration for each nation was:

  • China: 5 (21.91% of all Chinese battles lasted 5 minutes)
  • Czechoslovakia: 6 (21.01%)
  • France: 6 (24.18%)
  • Germany: 6 (23.85%)
  • Italy: 6 (25.94%)
  • Japan: 6 (24.48%)
  • Poland: 5 (21.82%) and 6 (21.82%)
  • Sweden: 6 (24.56%)
  • U.K.: 6 (22.87%)
  • U.S.A.: 6 (21.83%)
  • U.S.S.R.: 6 (23.38%)

The least common duration for each nation (excluding 3 minute battles) was:

  • China: 13 (0.93% of all Chinese battles lasted 13 minutes)
  • Czechoslovakia: 14 (1.04%)
  • France: 14 (1.23%)
  • Germany: 14 (1.23%)
  • Italy: 13 (0.62%)
  • Japan: 14 (0.79%)
  • Poland: 15 (0.72%)
  • Sweden: 14 (0.91%)
  • U.K.: 14 (0.93%)
  • U.S.A.: 14 (1.28%)
  • U.S.S.R.: 14 (1.01%)

If we transpose the data to put the duration first, we can see the most common nation for each battle duration was:

  1. Germany (24.06% of all 3 minute battles were in German vehicles)
  2. Germany (22.66%)
  3. Germany (22.85%)
  4. U.S.A (23.04%)
  5. U.S.A (25.23%)
  6. U.S.A (25.78%)
  7. U.S.A (26.80%)

  1. U.S.A (26.80%)
  2. U.S.A (27.49%)
  3. U.S.A (28.71%)
  4. U.S.A (27.82%)
  5. U.S.A (27.43%)
  6. U.S.A (29.14%)

And the least common nation for each battle duration:

  1. Japan (0.75% of all 3 minute battles were in Japanese vehicles)
  2. Poland (1.40%)
  3. Poland (1.45%)
  4. Poland (1.12%)
  5. Poland (1.10%)
  6. Poland (1.41%)
  7. Poland (1.04%)

  1. Poland (0.58%)
  2. Poland (1.07%)
  3. Poland (1.24%)
  4. Italy (1.01%)
  5. Japan (1.25%) and Poland (1.25%)
  6. Poland (0.43%)

Let's explore the three most common battle durations: 5, 6 and 7 minutes.

China was the most likely to have a five minute battle (21.91% of all Chinese battles lasted five minutes), whereas U.S.A was the least likely (16.57%).

Italy was the most likely to have a six minute battle (25.94% of all Italian battles lasted six minutes), whereas Czechoslovakia was the least likely (21.01%).

China was the most likely to have a seven minute battle (20.32% of all Chinese battles lasted seven minutes), whereas Italy was the least likely (17.21%).


Czechoslovakia had the highest victory rate of 53.13%, whereas U.K. had the lowest of 48.81%. They each had the lowest and highest loss rate respectively (45.49% and 49.94%). U.S.A had the highest draw rate (1.72%) whereas Poland had the lowest (0.72%).


Finally, we have the Nation of the vehicle which was featured in the replay. As I was adding the class data, I thought it would be interesting to also take a brief look at the Nation, to see if there is anything that correlates. Part 5 of the Replay Analysis will cover all areas with the focus on the Nation. This data was previously published in Part 4: Vehicle Class.

With a focus on Tier 6 and above, due to the lowest Tiers being almost exclusively Light Tanks...

The most common Nation for each Vehicle class was:

  • Heavy: U.S.S.R. (29.45% of all Tier 6 or above Heavy Tank battles were in U.S.S.R. vehicles)
  • Medium: U.S.S.R. (17.50%)
  • Light: France (35.39%)
  • Tank Destroyer: U.S.A. (25.78%)
  • SPG: U.S.A. (42.27%)

The least common Nation for each Vehicle class was:

  • Heavy: Italy (1.23% of all Tier 6 or above Heavy Tank battles were in Italian vehicles)
  • Medium: Czechoslovakia (4.23%)
  • Light: U.K. (5.18%)
  • Tank Destroyer: France (0.19%)
  • SPG: France (5.19%)

I find the least common data interesting, specifically for Heavy Tanks. Italian Heavies entered the game in update 1.11.1 at the end of January 2021, seven months before the Czechoslovakian Heavies (update 1.14, August 2021). The majority of the 66,000+ replays sent to me were sent in December 2021, not five months since 1.14, but Italian Heavies are still the least common Heavy Tank. In fact, the Czechoslovakian Heavies are the fifth least common (seventh most common) Heavy Tank to be played. The second, third and fourth least common are Poland (1.63% of all Tier 6 or above Heavy Tank battles were in Polish vehicles), Japan (2.89%) and China (4.99%) respectively.

If we transpose the data, putting the Nation first, we can see the most common vehicle class for each Nation:

  • China: Medium (38.13% of all replays, where the player was driving a Tier 6 or above Chinese Medium Tank)
  • Czechoslovakia: Medium (52.38%)
  • France: Medium (36.22%)
  • Germany: SPG (48.40%)
  • Italy: Medium (93.01%)
  • Japan: Medium (78.41%)
  • Poland: Medium (83.61%)
  • Sweden: Tank Destroyer (41.23%)
  • U.K.: SPG (39.57%)
  • U.S.A.: (63.07%)
  • U.S.S.R.: SPG (35.92%)

And the least common vehicle class for each Nation:

  • China: Tank Destroyer (12.87% of all replays, where the player was driving a Tier 6 or above Chinese Tank Destroyer)
  • Czechoslovakia: Heavy (47.62%)
  • France: Tank Destroyer (0.28%)
  • Germany: Light (6.34%)
  • Italy: Heavy (6.99%)
  • Japan: Heavy (21.59%)
  • Poland: Heavy (16.39%)
  • Sweden: Heavy (24.00%)
  • U.K.: Light (6.67%)
  • U.S.A.: Light (5.05%)
  • U.S.S.R.: Light (7.60%)

This concludes Part 5 of my Replay Analysis. Thank you to those who have sent me more replays since the initial call - hopefully we can break the 100,000 milestone soon! I am still struggling with how to represent the Range, but will find a way soon. It's likely this analysis will slow down for the next month or two as I finish this year at university. After Part 6, I aim to return to the beginning to re-publish everything in one report, to include the most recent replays I have been sent, but also for continuity. I feel there are areas of this entire analysis which have been far stronger than others, so the re-write will hopefully help there. It's proven to be a gargantuan project so far (10,000+ words and 109 infographics!), so I want the re-write to be done properly. I'll also be spending a bit of time to educate myself more in statistics - I would like to provide indicators of significance, with the evidence - t tests and such.

Thank you

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