MachineLearning's overall stats
| Stat | Total | Last 24h | Last 7d | Last 30d | ||||
|---|---|---|---|---|---|---|---|---|
| Battles | 14,707 | 0 | 69 | — | ||||
| Tier | 7.05 | — | 7.97 | — | ||||
| Wins | 7,007 | 47.64% | 0 | — | 33 | 47.83% | — | |
| Losses | 7,471 | 50.80% | 0 | — | 36 | 52.17% | — | |
| Draws | 229 | 1.56% | 0 | — | 0 | 0.00% | — | |
| Battles survived | 3,088 | 21.00% | 0 | — | 12 | 17.39% | — | |
| Tanks destroyed | 8,594 | 0.58 | 0 | — | 32 | 0.46 | — | |
| Destruction ratio | 0.74 | — | 0.56 | — | ||||
| Tanks spotted | 14,508 | 0.99 | 0 | — | 95 | 1.38 | — | |
| Damage dealt | 775.76 | — | 1,096.30 | — | ||||
| Base capture | 9,970 | 0.68 | 0 | — | 82 | 1.19 | — | |
| Base defense | 4,286 | 0.29 | 0 | — | 0 | 0.00 | — | |
| Experience | 558.02 | — | 697.49 | — | ||||
| Hit rate | 55.61% | — | 64.85% | — | ||||
| Personal rating | 4,489 | 0 | +5 | — | ||||
| World of Tanks Rating | 4,211 | 0 | +17 | — | ||||
| WN7 | 798.54 | — | 823.15 | — | ||||
| WN8 | 925.78 | — | 1,081.65 | — | ||||
| WNX | 836.67 | — | 993.93 | — | ||||
MachineLearning's WNX progression
Solid line is overall WNX (matches the Total column above), drifting slowly as new battles accumulate. Dashed line is per-session WNX, computed from the battles played since the previous snapshot. It shows hot and cold streaks. Line color follows the rating tier.
Tanks shaping MachineLearning's rating
🚀 Lifting the ratingWNX
Tanks that prop the overall up — dropping them would lower the rating.
- M40/M43Tier VIII· 398 battles1,645.64−20.85 if removed
- FV215b (183)Tier X· 313 battles1,193.46−10.88 if removed
- TortoiseTier IX· 153 battles1,397.23−8.13 if removed
- 8,8 cm Pak 43 JagdtigerTier VIII· 503 battles1,029.53−7.26 if removed
- AT 15Tier VIII· 221 battles1,265.05−6.96 if removed
⚓ Dragging the ratingWNX
Tanks that weigh the overall down — dropping them would raise the rating.
- AMX ELC bisTier V· 282 battles217.73+9.04 if removed
- T-44Tier VIII· 205 battles498.97+5.71 if removed
- ARL 44Tier VI· 124 battles284.26+4.71 if removed
- M4A1 ShermanTier V· 280 battles441.16+4.57 if removed
- AMX 40Tier IV· 107 battles100.32+4.18 if removed
MachineLearning's tanks (237)
| 527 | 967 | 46.11% | 759.84 | |
| 503 | 975 | 48.31% | 1,029.53 | |
| 398 | 1,346 | 50.50% | 1,645.64 | |
| 313 | 1,600 | 48.24% | 1,193.46 | |
| 282 | 177 | 44.68% | 217.73 | |
| 280 | 321 | 47.86% | 441.16 | |
| 263 | 472 | 47.15% | 664.34 | |
| 223 | 772 | 43.05% | 812.77 | |
| 221 | 1,118 | 49.32% | 1,265.05 | |
| 212 | 1,077 | 44.81% | 833.92 | |
| 205 | 588 | 38.54% | 498.97 | |
| 185 | 986 | 48.11% | 763.76 | |
| 180 | 668 | 45.56% | 680.74 | |
| 165 | 1,427 | 51.52% | 1,003.60 | |
| 163 | 447 | 49.08% | 656.66 | |
| 159 | 730 | 50.94% | 856.64 | |
| 155 | 1,018 | 44.52% | 794.09 | |
| 153 | 1,438 | 47.06% | 1,397.23 | |
| 149 | 554 | 46.98% | 634.49 | |
| 146 | 1,113 | 51.37% | 1,382.05 | |
| 144 | 700 | 38.19% | 887.92 | |
| 141 | 1,037 | 50.35% | 940.52 | |
| 140 | 1,126 | 55.71% | 1,404.34 | |
| 136 | 704 | 48.53% | 799.08 | |
| 135 | 1,504 | 51.11% | 1,161.58 | |
| 134 | 433 | 51.49% | 722.42 | |
| 133 | 455 | 47.37% | 601.14 | |
| 132 | 510 | 55.30% | 835.57 | |
| 129 | 137 | 58.91% | 215.19 | |
| 127 | 620 | 51.97% | 1,236.71 | |
| 124 | 395 | 37.10% | 284.26 | |
| 121 | 836 | 49.59% | 785.58 | |
| 121 | 1,004 | 53.72% | 1,041.06 | |
| 117 | 558 | 47.86% | 383.59 | |
| 117 | 1,303 | 52.14% | 1,119.37 | |
| 114 | 985 | 45.61% | 1,024.42 | |
| 112 | 437 | 47.32% | 601.18 | |
| 111 | 1,080 | 39.64% | 956.36 | |
| 110 | 902 | 52.73% | 1,124.31 | |
| 108 | 832 | 50.00% | 1,065.74 | |
| 107 | 147 | 49.53% | 100.32 | |
| 106 | 1,443 | 47.17% | 1,167.11 | |
| 105 | 269 | 52.38% | 354.40 | |
| 105 | 763 | 47.62% | 603.76 | |
| 103 | 775 | 58.25% | 1,572.87 | |
| 102 | 707 | 49.02% | 1,548.61 | |
| 102 | 644 | 43.14% | 818.66 | |
| 100 | 373 | 45.00% | 1,414.50 | |
| 99 | 1,136 | 49.49% | 953.71 | |
| 98 | 738 | 38.78% | 450.20 | |
| 97 | 539 | 40.21% | 605.22 | |
| 97 | 1,358 | 47.42% | 884.09 | |
| 94 | 655 | 43.62% | 915.45 | |
| 93 | 843 | 38.71% | 734.13 | |
| 91 | 447 | 53.85% | 657.89 | |
| 90 | 507 | 67.78% | 819.28 | |
| 89 | 771 | 49.44% | 1,160.79 | |
| 89 | 394 | 55.06% | 287.47 | |
| 89 | 1,212 | 41.57% | 919.58 | |
| 88 | 1,062 | 50.00% | 933.87 | |
| 88 | 905 | 56.82% | 666.82 | |
| 88 | 506 | 60.23% | 809.70 | |
| 87 | 466 | 51.72% | 434.46 | |
| 87 | 357 | 58.62% | 331.71 | |
| 84 | 1,227 | 50.00% | 1,250.81 | |
| 81 | 439 | 41.98% | 433.38 | |
| 81 | 145 | 45.68% | 50.23 | |
| 80 | 252 | 47.50% | 441.45 | |
| 80 | 1,138 | 36.25% | 802.71 | |
| 78 | 870 | 55.13% | 1,221.60 | |
| 78 | 904 | 43.59% | 649.83 | |
| 76 | 261 | 50.00% | 588.24 | |
| 76 | 1,276 | 47.37% | 908.28 | |
| 75 | 300 | 50.67% | 546.17 | |
| 74 | 483 | 39.19% | 812.65 | |
| 73 | 357 | 49.32% | 476.74 | |
| 72 | 598 | 43.06% | 731.17 | |
| 71 | 484 | 43.66% | 503.65 | |
| 70 | 1,015 | 47.14% | 973.72 | |
| 69 | 917 | 34.78% | 1,281.87 | |
| 68 | 605 | 39.71% | 335.91 | |
| 67 | 390 | 53.73% | 612.42 | |
| 67 | 1,139 | 40.30% | 1,121.12 | |
| 66 | 219 | 43.94% | 86.69 | |
| 66 | 549 | 46.97% | 733.44 | |
| 66 | 358 | 42.42% | 629.33 | |
| 66 | 772 | 36.36% | 605.67 | |
| 65 | 989 | 43.08% | 827.79 | |
| 63 | 543 | 55.56% | 1,211.41 | |
| 61 | 1,114 | 45.90% | 990.19 | |
| 57 | 956 | 45.61% | 841.88 | |
| 57 | 733 | 47.37% | 471.54 | |
| 56 | 938 | 35.71% | 1,168.41 | |
| 56 | 243 | 44.64% | 229.02 | |
| 56 | 1,305 | 48.21% | 1,012.21 | |
| 56 | 954 | 44.64% | 610.30 | |
| 55 | 708 | 47.27% | 898.47 | |
| 54 | 584 | 62.96% | 650.82 | |
| 52 | 382 | 46.15% | 636.33 | |
| 52 | 1,370 | 50.00% | 1,238.67 | |
| 52 | 390 | 40.38% | 852.45 | |
| 51 | 470 | 47.06% | 850.14 | |
| 51 | 370 | 50.98% | 497.39 | |
| 50 | 75 | 52.00% | 15.33 | |
| 50 | 628 | 46.00% | 1,080.84 | |
| 49 | 93 | 40.82% | 23.56 | |
| 49 | 1,281 | 40.82% | 1,564.95 | |
| 49 | 1,329 | 38.78% | 770.94 | |
| 49 | 1,251 | 51.02% | 860.21 | |
| 49 | 571 | 38.78% | 652.54 | |
| 48 | 333 | 54.17% | 633.05 | |
| 48 | 449 | 43.75% | 479.02 | |
| 48 | 568 | 41.67% | 369.81 | |
| 48 | 790 | 58.33% | 842.03 | |
| 47 | 1,453 | 44.68% | 1,028.53 | |
| 47 | 1,251 | 48.94% | 652.62 | |
| 45 | 1,343 | 42.22% | 570.57 | |
| 45 | 404 | 62.22% | 842.63 | |
| 43 | 936 | 58.14% | 1,061.27 | |
| 42 | 406 | 54.76% | 513.15 | |
| 42 | 799 | 57.14% | 1,514.30 | |
| 41 | 729 | 41.46% | 579.80 | |
| 40 | 68 | 47.50% | 8.41 | |
| 40 | 1,167 | 55.00% | 812.12 | |
| 39 | 256 | 43.59% | 390.27 | |
| 39 | 1,499 | 30.77% | 1,465.29 | |
| 38 | 154 | 47.37% | 113.97 | |
| 38 | 230 | 63.16% | 315.54 | |
| 38 | 478 | 47.37% | 710.69 | |
| 37 | 1,053 | 51.35% | 720.19 | |
| 37 | 124 | 56.76% | 34.39 | |
| 37 | 1,086 | 43.24% | 1,567.18 | |
| 37 | 1,006 | 45.95% | 1,033.23 | |
| 36 | 39 | 36.11% | 0.16 | |
| 34 | 118 | 52.94% | 23.32 | |
| 34 | 318 | 44.12% | 509.66 | |
| 33 | 1,330 | 57.58% | 1,005.10 | |
| 32 | 556 | 46.88% | 687.90 | |
| 31 | 759 | 45.16% | 483.04 | |
| 31 | 1,634 | 54.84% | 1,331.62 | |
| 29 | 190 | 34.48% | 249.69 | |
| 29 | 368 | 51.72% | 457.94 | |
| 28 | 1,146 | 32.14% | 905.69 | |
| 28 | 914 | 35.71% | 629.68 | |
| 27 | 590 | 44.44% | 570.46 | |
| 27 | 39 | 33.33% | 1.56 | |
| 26 | 1,403 | 46.15% | 936.60 | |
| 24 | 57 | 41.67% | 2.08 | |
| 24 | 340 | 41.67% | 1,251.06 | |
| 23 | 201 | 26.09% | 259.54 | |
| 23 | 656 | 43.48% | 482.94 | |
| 22 | 848 | 54.55% | 818.41 | |
| 22 | 1,171 | 59.09% | 1,863.33 | |
| 21 | 993 | 38.10% | 961.41 | |
| 20 | 66 | 45.00% | 17.94 | |
| 20 | 1,345 | 45.00% | 1,022.12 | |
| 19 | 1,231 | 47.37% | 1,309.90 | |
| 19 | 438 | 57.89% | 781.43 | |
| 18 | 143 | 27.78% | 255.57 | |
| 18 | 334 | 38.89% | 498.43 | |
| 16 | 426 | 50.00% | 362.30 | |
| 16 | 1,481 | 37.50% | 1,113.64 | |
| 16 | 835 | 50.00% | 611.68 | |
| 15 | 196 | 33.33% | 578.20 | |
| 15 | 310 | 40.00% | 163.85 | |
| 15 | 217 | 60.00% | 213.08 | |
| 14 | 1,295 | 42.86% | 1,391.01 | |
| 14 | 575 | 35.71% | 331.60 | |
| 13 | 109 | 53.85% | 42.70 | |
| 12 | 930 | 83.33% | 1,603.03 | |
| 12 | 108 | 33.33% | 217.54 | |
| 12 | 1,482 | 33.33% | 908.40 | |
| 11 | 363 | 36.36% | 382.55 | |
| 11 | 872 | 54.55% | — | |
| 11 | 821 | 54.55% | 731.21 | |
| 10 | 766 | 40.00% | 569.00 | |
| 10 | 1,311 | 60.00% | 1,058.01 | |
| 10 | 1,486 | 60.00% | 1,074.05 | |
| 9 | 30 | 44.44% | 1.58 | |
| 9 | 505 | 66.67% | 730.88 | |
| 8 | 51 | 12.50% | 1.80 | |
| 8 | 86 | 62.50% | 41.69 | |
| 8 | 83 | 50.00% | 32.32 | |
| 7 | 1,717 | 28.57% | 729.73 | |
| 7 | 64 | 42.86% | 27.83 | |
| 7 | 212 | 42.86% | 263.72 | |
| 7 | 439 | 28.57% | 999.09 | |
| 6 | 331 | 33.33% | 347.03 | |
| 6 | 66 | 66.67% | 0.27 | |
| 6 | 623 | 50.00% | 706.53 | |
| 6 | 103 | 66.67% | 125.72 | |
| 6 | 1,538 | 66.67% | — | |
| 6 | 373 | 16.67% | 432.69 | |
| 6 | 313 | 33.33% | 145.10 | |
| 6 | 624 | 33.33% | 391.70 | |
| 5 | 17 | 60.00% | 1.24 | |
| 5 | 576 | 60.00% | 439.26 | |
| 4 | 81 | 75.00% | 141.82 | |
| 4 | 36 | 50.00% | 0.00 | |
| 4 | 160 | 75.00% | 158.28 | |
| 4 | 255 | 50.00% | 163.01 | |
| 4 | 48 | 75.00% | 66.19 | |
| 4 | 1,538 | 75.00% | 1,194.64 | |
| 4 | 30 | 50.00% | 2.08 | |
| 3 | 80 | 66.67% | 54.05 | |
| 3 | 1,689 | 66.67% | 1,579.83 | |
| 3 | 99 | 66.67% | 296.63 | |
| 2 | 6 | 50.00% | 0.00 | |
| 2 | 0 | 0.00% | 2.08 | |
| 2 | 75 | 50.00% | 31.11 | |
| 2 | 80 | 100.00% | 29.69 | |
| 2 | 559 | 50.00% | 100.37 | |
| 2 | 1,318 | 100.00% | 625.88 | |
| 2 | 947 | 50.00% | 278.86 | |
| 2 | 966 | 100.00% | — | |
| 2 | 399 | 50.00% | — | |
| 2 | 26 | 50.00% | 0.00 | |
| 2 | 348 | 0.00% | 598.01 | |
| 2 | 750 | 50.00% | 1,171.30 | |
| 1 | 36 | 100.00% | 0.00 | |
| 1 | 56 | 0.00% | 2.08 | |
| 1 | 134 | 100.00% | 83.09 | |
| 1 | 33 | 100.00% | 0.00 | |
| 1 | 672 | 100.00% | 32.97 | |
| 1 | 0 | 0.00% | 0.00 | |
| 1 | 474 | 0.00% | 839.46 | |
| 1 | 1,004 | 100.00% | 453.29 | |
| 1 | 866 | 0.00% | 170.54 | |
| 1 | 2,778 | 0.00% | 2,099.92 | |
| 1 | 1,613 | 100.00% | 536.65 | |
| 1 | 186 | 0.00% | — | |
| 1 | 504 | 100.00% | — | |
| 1 | 83 | 0.00% | 2.08 | |
| 1 | 86 | 0.00% | 46.99 | |
| 1 | 74 | 100.00% | 42.36 | |
| 1 | 1,018 | 100.00% | 442.79 | |
| 1 | 122 | 100.00% | 105.20 |
MachineLearning's clans history
4 clans · 2y 9mo in clans