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# RANK LEVEL SCORE nickname (playing from) medals boxes stops used crashes
2746 2733 7 347,792 France pascal (France) 14 32 0 167
2746 2733 7 347,792 France pascal (France) 14 32 0 167
2747 2734 7 347,734 Indonesia kasis (Indonesia) 14 32 9 308
2747 2734 7 347,734 Indonesia kasis (Indonesia) 14 32 9 308
2748 2735 7 347,699 China Zzz (China) 11 31 0 331
2748 2735 7 347,699 China Zzz (China) 11 31 0 331
2749 2736 7 347,662 Spain Alex (Spain) 15 32 15 233
2749 2736 7 347,662 Spain Alex (Spain) 15 32 15 233
2750 2737 7 347,611 Canada mama (Canada) 13 33 18 469
2750 2737 7 347,611 Canada mama (Canada) 13 33 18 469
2751 2738 7 347,588 Brazil kreidias (Brazil) 18 32 15 170
2751 2738 7 347,588 Brazil kreidias (Brazil) 18 32 15 170
2752 2739 7 347,557 United States Eric (United States) 19 32 15 264
2752 2739 7 347,557 United States Eric (United States) 19 32 15 264
2753 2740 7 347,533 India Vinod (India) 15 32 8 210
2753 2740 7 347,533 India Vinod (India) 15 32 8 210
2754 2741 7 347,456 Canada Eric (Canada) 17 32 12 273
2754 2741 7 347,456 Canada Eric (Canada) 17 32 12 273
2755 2742 7 347,422 France Mathieu (France) 14 31 18 233
2755 2742 7 347,422 France Mathieu (France) 14 31 18 233
2756 2743 7 347,412 France Pierroleskimo (France) 20 32 1 259
2756 2743 7 347,412 France Pierroleskimo (France) 20 32 1 259
2757 2744 7 347,400 United Kingdom magic (United Kingdom) 12 31 18 258
2757 2744 7 347,400 United Kingdom magic (United Kingdom) 12 31 18 258
2758 2745 7 347,322 China 朱江 (China) 18 32 13 287
2758 2745 7 347,322 China 朱江 (China) 18 32 13 287
2759 2746 7 347,313 United States hendog (United States) 19 32 3 170
2759 2746 7 347,313 United States hendog (United States) 19 32 3 170
2760 2747 7 347,257 United States Dadda (United States) 14 32 0 114
2760 2747 7 347,257 United States Dadda (United States) 14 32 0 114
2761 2748 7 347,244 Colombia Miguel (Colombia) 18 32 4 157
2761 2748 7 347,244 Colombia Miguel (Colombia) 18 32 4 157
2762 2749 7 347,241 Germany phip (Germany) 15 32 14 100
2762 2749 7 347,241 Germany phip (Germany) 15 32 14 100
2763 2750 7 347,218 Malaysia eve (Malaysia) 19 32 13 207
2763 2750 7 347,218 Malaysia eve (Malaysia) 19 32 13 207
2764 2751 7 347,119 United States Leo (United States) 15 32 15 812
2764 2751 7 347,119 United States Leo (United States) 15 32 15 812
2765 2752 7 347,055 India abhi (India) 16 32 10 195
2765 2752 7 347,055 India abhi (India) 16 32 10 195
2766 2753 7 347,037 Sweden Kent W (Sweden) 13 31 13 228
2766 2753 7 347,037 Sweden Kent W (Sweden) 13 31 13 228
2767 2754 7 347,025 Sweden Amenvafaan (Sweden) 14 32 6 179
2767 2754 7 347,025 Sweden Amenvafaan (Sweden) 14 32 6 179
2768 2755 7 346,870 Italy io (Italy) 11 33 18 224
2768 2755 7 346,870 Italy io (Italy) 11 33 18 224
2769 2756 7 346,815 Europe gianluca (Europe) 15 32 5 107
2769 2756 7 346,815 Europe gianluca (Europe) 15 32 5 107
2770 2757 7 346,664 Italy Ragonio (Italy) 16 32 0 280
2770 2757 7 346,664 Italy Ragonio (Italy) 16 32 0 280
2771 2758 7 346,645 China 冯韶华 (China) 17 32 13 280
2771 2758 7 346,645 China 冯韶华 (China) 17 32 13 280
2772 2759 7 346,626 United States Brairbre (United States) 17 32 12 187
2772 2759 7 346,626 United States Brairbre (United States) 17 32 12 187
2773 2760 7 346,618 Sweden mac (Sweden) 14 31 12 273
2773 2760 7 346,618 Sweden mac (Sweden) 14 31 12 273
2774 2761 7 346,570 Italy gabai (Italy) 16 32 11 157
2774 2761 7 346,570 Italy gabai (Italy) 16 32 11 157
2775 2762 7 346,442 Belgium jeremy (Belgium) 15 32 6 153
2775 2762 7 346,442 Belgium jeremy (Belgium) 15 32 6 153
2776 2763 7 346,429 France enker (France) 12 32 18 167
2776 2763 7 346,429 France enker (France) 12 32 18 167
2777 2764 7 346,399 Sweden dgb (Sweden) 19 32 5 239
2777 2764 7 346,399 Sweden dgb (Sweden) 19 32 5 239
2778 2765 7 346,217 Sweden bodilan (Sweden) 20 32 0 174
2778 2765 7 346,217 Sweden bodilan (Sweden) 20 32 0 174
2779 2766 7 346,170 Brazil luana (Brazil) 17 32 10 239
2779 2766 7 346,170 Brazil luana (Brazil) 17 32 10 239
2780 2767 7 346,102 United Kingdom Bear (United Kingdom) 21 31 14 681
2780 2767 7 346,102 United Kingdom Bear (United Kingdom) 21 31 14 681
2781 2768 7 346,035 India ashu (India) 16 32 17 397
2781 2768 7 346,035 India ashu (India) 16 32 17 397
2782 2769 7 345,994 Russian Federation сергей (Russian Federation) 13 32 15 203
2782 2769 7 345,994 Russian Federation сергей (Russian Federation) 13 32 15 203
2783 2770 7 345,954 United Kingdom phil (United Kingdom) 16 32 9 67
2783 2770 7 345,954 United Kingdom phil (United Kingdom) 16 32 9 67
2784 2771 7 345,932 Hong Kong pakho (Hong Kong) 15 32 12 206
2784 2771 7 345,932 Hong Kong pakho (Hong Kong) 15 32 12 206
2785 2772 7 345,829 Italy miki (Italy) 16 31 14 540
2785 2772 7 345,829 Italy miki (Italy) 16 31 14 540
2786 2773 7 345,808 Canada Latimiro (Canada) 19 32 0 187
2786 2773 7 345,808 Canada Latimiro (Canada) 19 32 0 187
2787 2774 7 345,792 United Kingdom mat (United Kingdom) 12 24 5 345
2787 2774 7 345,792 United Kingdom mat (United Kingdom) 12 24 5 345
2788 2775 7 345,747 Brazil viini (Brazil) 16 32 6 249
2788 2775 7 345,747 Brazil viini (Brazil) 16 32 6 249
2789 2776 7 345,746 Indonesia manshoezz (Indonesia) 19 32 10 274
2789 2776 7 345,746 Indonesia manshoezz (Indonesia) 19 32 10 274
2790 2777 7 345,738 unknown Danny (unknown) 18 31 5 191
2790 2777 7 345,738 unknown Danny (unknown) 18 31 5 191
2791 2778 7 345,687 Sweden simpa (Sweden) 11 32 2 258
2791 2778 7 345,687 Sweden simpa (Sweden) 11 32 2 258
2792 2779 7 345,500 Sweden per (Sweden) 16 32 18 274
2792 2779 7 345,500 Sweden per (Sweden) 16 32 18 274
2793 2780 7 345,436 France aliya (France) 18 32 8 140
2793 2780 7 345,436 France aliya (France) 18 32 8 140
2794 2781 7 345,433 Czech Republic Szymon (Czech Republic) 14 32 0 282
2794 2781 7 345,433 Czech Republic Szymon (Czech Republic) 14 32 0 282
2795 2782 7 345,422 Viet Nam dexter (Viet Nam) 15 32 13 147
2795 2782 7 345,422 Viet Nam dexter (Viet Nam) 15 32 13 147
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