League:
Season:
Division:
Group:
Player:
1Vique17+20612
Spilt: 8
Seier: 6
Uavgjort: 0
Tap: 2
Score: 3712 - 3506
Fra: KENYA
2GauravT96+21610
Spilt: 8
Seier: 5
Uavgjort: 0
Tap: 3
Score: 3721 - 3505
Fra: The Good Place
3MontyBojangles+7510
Spilt: 8
Seier: 5
Uavgjort: 0
Tap: 3
Score: 3546 - 3471
4Wolcoul-279
Spilt: 8
Seier: 4
Uavgjort: 1
Tap: 3
Score: 3107 - 3134
5shenanigan5+898
Spilt: 8
Seier: 4
Uavgjort: 0
Tap: 4
Score: 3517 - 3428
Fra: England
6Gaks000-2348
Spilt: 8
Seier: 4
Uavgjort: 0
Tap: 4
Score: 3450 - 3684
7heteroskedasticity+56
Spilt: 8
Seier: 3
Uavgjort: 0
Tap: 5
Score: 3499 - 3494
Fra: Essex
8Trottie-1835
Spilt: 8
Seier: 2
Uavgjort: 1
Tap: 5
Score: 3023 - 3206
9Gilliant2019-1474
Spilt: 8
Seier: 2
Uavgjort: 0
Tap: 6
Score: 3679 - 3826
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Matches
| Kamp |
Resultat |
| HETEROSKEDASTICITY | |
| heteroskedasticity – Gaks000 | 355 – 443 |
| heteroskedasticity – shenanigan5 | 401 – 454 |
| heteroskedasticity – GauravT96 | 457 – 366 |
| heteroskedasticity – Wolcoul | 437 – 461 |
| heteroskedasticity – Gilliant2019 | 485 – 416 |
| heteroskedasticity – Vique17 | 460 – 486 |
| heteroskedasticity – Trottie | 506 – 450 |
| heteroskedasticity – MontyBojangles | 398 – 418 |
| |
| GAKS000 | |
| Gaks000 – heteroskedasticity | 443 – 355 |
| Gaks000 – shenanigan5 | 390 – 530 |
| Gaks000 – GauravT96 | 409 – 536 |
| Gaks000 – Wolcoul | 482 – 452 |
| Gaks000 – Gilliant2019 | 504 – 411 |
| Gaks000 – Vique17 | 429 – 569 |
| Gaks000 – Trottie | 420 – 368 |
| Gaks000 – MontyBojangles | 373 – 463 |
| |
| SHENANIGAN5 | |
| shenanigan5 – heteroskedasticity | 454 – 401 |
| shenanigan5 – Gaks000 | 530 – 390 |
| shenanigan5 – GauravT96 | 335 – 427 |
| shenanigan5 – Wolcoul | 432 – 447 |
| shenanigan5 – Gilliant2019 | 431 – 430 |
| shenanigan5 – Vique17 | 503 – 401 |
| shenanigan5 – Trottie | 431 – 483 |
| shenanigan5 – MontyBojangles | 401 – 449 |
| |
| GAURAVT96 | |
| GauravT96 – heteroskedasticity | 366 – 457 |
| GauravT96 – Gaks000 | 536 – 409 |
| GauravT96 – shenanigan5 | 427 – 335 |
| GauravT96 – Wolcoul | 523 – 300 |
| GauravT96 – Gilliant2019 | 449 – 651 |
| GauravT96 – Vique17 | 422 – 447 |
| GauravT96 – Trottie | 497 – 438 |
| GauravT96 – MontyBojangles | 501 – 468 |
| |
| WOLCOUL | |
| Wolcoul – heteroskedasticity | 461 – 437 |
| Wolcoul – Gaks000 | 452 – 482 |
| Wolcoul – shenanigan5 | 447 – 432 |
| Wolcoul – GauravT96 | 300 – 523 |
| Wolcoul – Gilliant2019 | 507 – 448 |
| Wolcoul – Vique17 | 494 – 365 |
| Wolcoul – Trottie | 0 – 0 |
| Wolcoul – MontyBojangles | 446 – 447 |
| |
| GILLIANT2019 | |
| Gilliant2019 – heteroskedasticity | 416 – 485 |
| Gilliant2019 – Gaks000 | 411 – 504 |
| Gilliant2019 – shenanigan5 | 430 – 431 |
| Gilliant2019 – GauravT96 | 651 – 449 |
| Gilliant2019 – Wolcoul | 448 – 507 |
| Gilliant2019 – Vique17 | 397 – 468 |
| Gilliant2019 – Trottie | 484 – 431 |
| Gilliant2019 – MontyBojangles | 442 – 551 |
| |
| VIQUE17 | |
| Vique17 – heteroskedasticity | 486 – 460 |
| Vique17 – Gaks000 | 569 – 429 |
| Vique17 – shenanigan5 | 401 – 503 |
| Vique17 – GauravT96 | 447 – 422 |
| Vique17 – Wolcoul | 365 – 494 |
| Vique17 – Gilliant2019 | 468 – 397 |
| Vique17 – Trottie | 495 – 424 |
| Vique17 – MontyBojangles | 481 – 377 |
| |
| TROTTIE | |
| Trottie – heteroskedasticity | 450 – 506 |
| Trottie – Gaks000 | 368 – 420 |
| Trottie – shenanigan5 | 483 – 431 |
| Trottie – GauravT96 | 438 – 497 |
| Trottie – Wolcoul | 0 – 0 |
| Trottie – Gilliant2019 | 431 – 484 |
| Trottie – Vique17 | 424 – 495 |
| Trottie – MontyBojangles | 429 – 373 |
| |
| MONTYBOJANGLES | |
| MontyBojangles – heteroskedasticity | 418 – 398 |
| MontyBojangles – Gaks000 | 463 – 373 |
| MontyBojangles – shenanigan5 | 449 – 401 |
| MontyBojangles – GauravT96 | 468 – 501 |
| MontyBojangles – Wolcoul | 447 – 446 |
| MontyBojangles – Gilliant2019 | 551 – 442 |
| MontyBojangles – Vique17 | 377 – 481 |
| MontyBojangles – Trottie | 373 – 429 |
| |
heteroskedasticity355
Gaks000443
heteroskedasticity401
shenanigan5454
heteroskedasticity457
GauravT96366
heteroskedasticity437
Wolcoul461
heteroskedasticity485
Gilliant2019416
heteroskedasticity460
Vique17486
heteroskedasticity506
Trottie450
heteroskedasticity398
MontyBojangles418
Gaks000443
heteroskedasticity355
Gaks000504
Gilliant2019411
Gaks000373
MontyBojangles463
shenanigan5454
heteroskedasticity401
shenanigan5335
GauravT96427
shenanigan5431
Gilliant2019430
shenanigan5401
MontyBojangles449
GauravT96366
heteroskedasticity457
GauravT96427
shenanigan5335
GauravT96449
Gilliant2019651
GauravT96501
MontyBojangles468
Wolcoul461
heteroskedasticity437
Wolcoul507
Gilliant2019448
Wolcoul446
MontyBojangles447
Gilliant2019416
heteroskedasticity485
Gilliant2019411
Gaks000504
Gilliant2019430
shenanigan5431
Gilliant2019651
GauravT96449
Gilliant2019448
Wolcoul507
Gilliant2019397
Vique17468
Gilliant2019484
Trottie431
Gilliant2019442
MontyBojangles551
Vique17486
heteroskedasticity460
Vique17468
Gilliant2019397
Vique17481
MontyBojangles377
Trottie450
heteroskedasticity506
Trottie431
Gilliant2019484
Trottie429
MontyBojangles373
MontyBojangles418
heteroskedasticity398
MontyBojangles463
Gaks000373
MontyBojangles449
shenanigan5401
MontyBojangles468
GauravT96501
MontyBojangles447
Wolcoul446
MontyBojangles551
Gilliant2019442
MontyBojangles377
Vique17481
MontyBojangles373
Trottie429