Official Event Results
2024 Hill Country Turkey Trot
Event Date
11/28/2024
Races
1
Result Rows
400
Split Rows
800
Entered
400
Finishers
400
Fastest Time
16:40
Average Time
34:02
| Place | Race No | Name | Gender | Division | Time | Chip Time | Pace | City | State | Details |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 63 | Male | 19-29 | 00:16:40.1 | 00:16:35.7 | |||||
| 2 | 11 | Male | 19-29 | 00:17:01.8 | 00:16:58.2 | |||||
| 3 | 310 | Male | 14-18 | 00:17:18.7 | 00:17:13.7 | |||||
| 4 | 371 | Male | 40-49 | 00:17:57.5 | 00:17:51.4 | |||||
| 5 | 494 | Male | 10-13 | 00:17:56.3 | 00:17:51.7 | |||||
| 6 | 470 | Male | 40-49 | 00:18:03.5 | 00:17:56.6 | |||||
| 7 | 488 | Male | 14-18 | 00:18:37.3 | 00:18:31.2 | |||||
| 8 | 45 | Male | 14-18 | 00:18:47.7 | 00:18:43.1 | |||||
| 9 | 326 | Male | 14-18 | 00:18:56.7 | 00:18:48.8 | |||||
| 10 | 146 | Male | 14-18 | 00:19:08.6 | 00:19:01.3 | |||||
| 11 | 114 | Male | 14-18 | 00:19:08.8 | 00:19:05.0 | |||||
| 12 | 487 | Female | 19-29 | 00:19:12.3 | 00:19:05.7 | |||||
| 13 | 405 | Male | 14-18 | 00:19:12.0 | 00:19:05.8 | |||||
| 14 | 265 | Male | 19-29 | 00:19:15.2 | 00:19:07.6 | |||||
| 15 | 339 | Male | 40-49 | 00:19:19.7 | 00:19:15.7 | |||||
| 16 | 43 | Male | 40-49 | 00:19:22.5 | 00:19:16.1 | |||||
| 17 | 257 | Male | 50-59 | 00:19:40.6 | 00:19:35.2 | |||||
| 18 | 24 | Male | 10-13 | 00:19:42.4 | 00:19:37.7 | |||||
| 19 | 229 | Male | 14-18 | 00:19:49.2 | 00:19:42.9 | |||||
| 20 | 77 | Male | 14-18 | 00:19:51.5 | 00:19:44.0 | |||||
| 21 | 320 | Male | 14-18 | 00:20:07.0 | 00:19:59.3 | |||||
| 22 | 74 | Male | 19-29 | 00:20:21.6 | 00:20:15.3 | |||||
| 23 | 85 | Male | 14-18 | 00:20:27.6 | 00:20:19.3 | |||||
| 24 | 473 | Male | 50-59 | 00:20:29.1 | 00:20:21.1 | |||||
| 25 | 363 | Female | 10-13 | 00:20:35.6 | 00:20:31.8 | |||||
| 26 | 18 | Male | 40-49 | 00:20:39.9 | 00:20:34.5 | |||||
| 27 | 364 | Female | 10-13 | 00:20:40.6 | 00:20:36.5 | |||||
| 28 | 255 | Female | 19-29 | 00:20:45.6 | 00:20:37.2 | |||||
| 29 | 70 | Female | 14-18 | 00:21:04.1 | 00:20:52.8 | |||||
| 30 | 79 | Male | 30-39 | 00:21:10.3 | 00:21:01.1 | |||||
| 31 | 454 | Female | 19-29 | 00:21:19.2 | 00:21:06.6 | |||||
| 32 | 76 | Male | 19-29 | 00:21:21.0 | 00:21:11.2 | |||||
| 33 | 144 | Female | 19-29 | 00:21:18.6 | 00:21:12.5 | |||||
| 34 | 411 | Female | 19-29 | 00:21:22.6 | 00:21:14.2 | |||||
| 35 | 41 | Male | 50-59 | 00:21:21.9 | 00:21:14.6 | |||||
| 36 | 69 | Male | 19-29 | 00:21:20.3 | 00:21:14.6 | |||||
| 37 | 60 | Male | 50-59 | 00:21:29.3 | 00:21:19.3 | |||||
| 38 | 464 | Female | 10-13 | 00:21:26.3 | 00:21:19.4 | |||||
| 39 | 13 | Female | 19-29 | 00:21:26.9 | 00:21:19.5 | |||||
| 40 | 75 | Male | 50-59 | 00:21:42.7 | 00:21:35.2 | |||||
| 41 | 256 | Female | 14-18 | 00:21:53.3 | 00:21:44.4 | |||||
| 42 | 337 | Female | 19-29 | 00:22:01.3 | 00:21:50.2 | |||||
| 43 | 78 | Male | 40-49 | 00:22:10.3 | 00:21:57.2 | |||||
| 44 | 231 | Male | 30-39 | 00:22:03.8 | 00:21:57.3 | |||||
| 45 | 140 | Male | 19-29 | 00:22:22.7 | 00:22:10.1 | |||||
| 46 | 305 | Male | 14-18 | 00:22:32.1 | 00:22:21.9 | |||||
| 47 | 218 | Male | 14-18 | 00:22:34.6 | 00:22:26.6 | |||||
| 48 | 329 | Male | 10-13 | 00:22:44.0 | 00:22:32.2 | |||||
| 49 | 481 | Male | 14-18 | 00:22:40.5 | 00:22:33.0 | |||||
| 50 | 53 | Female | 10-13 | 00:22:41.1 | 00:22:37.2 | |||||
| 51 | 359 | Male | 14-18 | 00:23:58.4 | 00:22:38.3 | |||||
| 52 | 56 | Female | 40-49 | 00:22:50.3 | 00:22:39.7 | |||||
| 53 | 57 | Male | 10-13 | 00:22:50.8 | 00:22:39.9 | |||||
| 54 | 52 | Male | 10-13 | 00:22:45.9 | 00:22:42.1 | |||||
| 55 | 317 | Male | 10-13 | 00:22:54.6 | 00:22:49.5 | |||||
| 56 | 372 | Male | 19-29 | 00:24:02.3 | 00:22:50.0 | |||||
| 57 | 228 | Male | 14-18 | 00:24:03.8 | 00:22:51.6 | |||||
| 58 | 6 | Male | 40-49 | 00:23:12.7 | 00:22:55.0 | |||||
| 59 | 344 | Unknown | UK | 00:23:05.1 | 00:22:55.9 | |||||
| 60 | 25 | Male | 10-13 | 00:23:01.5 | 00:22:57.6 | |||||
| 61 | 482 | Male | 10-13 | 00:23:05.4 | 00:22:57.9 | |||||
| 62 | 390 | Male | 19-29 | 00:23:30.8 | 00:23:02.7 | |||||
| 63 | 476 | Male | UK | 00:23:21.6 | 00:23:09.1 | |||||
| 64 | 235 | Female | 30-39 | 00:23:35.1 | 00:23:17.7 | |||||
| 65 | 458 | Male | UK | 00:23:30.8 | 00:23:18.5 | |||||
| 66 | 202 | Male | 10-13 | 00:23:35.6 | 00:23:20.3 | |||||
| 67 | 236 | Female | 14-18 | 00:23:37.6 | 00:23:28.7 | |||||
| 68 | 431 | Female | 14-18 | 00:23:40.1 | 00:23:30.3 | |||||
| 69 | 433 | Male | 60-99 | 00:23:52.1 | 00:23:38.9 | |||||
| 70 | 368 | Male | 10-13 | 00:23:57.4 | 00:23:41.6 | |||||
| 71 | 54 | Female | 40-49 | 00:23:54.5 | 00:23:45.6 | |||||
| 72 | 36 | Male | 10-13 | 00:24:08.0 | 00:23:53.3 | |||||
| 73 | 334 | Male | 30-39 | 00:24:08.3 | 00:23:55.6 | |||||
| 74 | 341 | Unknown | UK | 00:24:05.3 | 00:23:57.2 | |||||
| 75 | 130 | Male | 19-29 | 00:24:45.1 | 00:24:01.1 | |||||
| 76 | 416 | Male | 60-99 | 00:24:18.6 | 00:24:06.9 | |||||
| 77 | 437 | Male | 30-39 | 00:24:20.3 | 00:24:07.2 | |||||
| 78 | 333 | Male | 7 – 9 Years old | 00:24:07.6 | 00:24:07.6 | |||||
| 79 | 49 | Male | 50-59 | 00:24:18.0 | 00:24:09.8 | |||||
| 80 | 308 | Male | 40-49 | 00:24:47.5 | 00:24:13.1 | |||||
| 81 | 68 | Male | 19-29 | 00:24:45.0 | 00:24:23.5 | |||||
| 82 | 453 | Male | 50-59 | 00:24:39.2 | 00:24:25.3 | |||||
| 83 | 332 | Male | 14-18 | 00:24:35.3 | 00:24:31.2 | |||||
| 84 | 478 | Male | 10-13 | 00:24:46.5 | 00:24:31.6 | |||||
| 85 | 354 | Male | 10-13 | 00:24:46.2 | 00:24:32.2 | |||||
| 86 | 283 | Male | 19-29 | 00:26:59.8 | 00:24:35.9 | |||||
| 87 | 479 | Male | 50-59 | 00:24:43.3 | 00:24:37.0 | |||||
| 88 | 445 | Female | 14-18 | 00:24:44.0 | 00:24:37.6 | |||||
| 89 | 477 | Male | 40-49 | 00:24:56.4 | 00:24:38.0 | |||||
| 90 | 15 | Male | 14-18 | 00:25:31.0 | 00:24:42.4 | |||||
| 91 | 384 | Male | 40-49 | 00:25:27.6 | 00:24:48.2 | |||||
| 92 | 288 | Male | 40-49 | 00:25:12.8 | 00:24:49.0 | |||||
| 93 | 381 | Male | 14-18 | 00:25:09.2 | 00:24:53.2 | |||||
| 94 | 59 | Male | 10-13 | 00:25:10.2 | 00:24:59.3 | |||||
| 95 | 435 | Male | 14-18 | 00:25:30.1 | 00:25:00.7 | |||||
| 96 | 73 | Female | 14-18 | 00:25:11.8 | 00:25:02.0 | |||||
| 97 | 444 | Female | 14-18 | 00:25:14.0 | 00:25:04.7 | |||||
| 98 | 480 | Female | 50-59 | 00:25:18.1 | 00:25:09.9 | |||||
| 99 | 99 | Male | 19-29 | 00:29:36.3 | 00:25:10.3 | |||||
| 100 | 451 | Female | 30-39 | 00:25:30.8 | 00:25:10.7 | |||||
| 101 | 208 | Male | 14-18 | 00:26:49.6 | 00:25:11.1 | |||||
| 102 | 141 | Female | 10-13 | 00:25:26.2 | 00:25:15.4 | |||||
| 103 | 95 | Male | 30-39 | 00:27:32.7 | 00:25:24.8 | |||||
| 104 | 5 | Male | 14-18 | 00:26:19.8 | 00:25:29.4 | |||||
| 105 | 46 | Female | 40-49 | 00:25:56.6 | 00:25:32.0 | |||||
| 106 | 373 | Male | 19-29 | 00:26:46.3 | 00:25:32.2 | |||||
| 107 | 436 | Male | 10-13 | 00:26:02.3 | 00:25:33.6 | |||||
| 108 | 72 | Male | 30-39 | 00:26:11.2 | 00:25:37.1 | |||||
| 109 | 351 | Male | 50-59 | 00:26:03.2 | 00:25:43.5 | |||||
| 110 | 238 | Female | 40-49 | 00:26:31.5 | 00:25:44.3 | |||||
| 111 | 149 | Female | 30-39 | 00:26:06.9 | 00:25:45.0 | |||||
| 112 | 281 | Male | 10-13 | 00:25:51.6 | 00:25:46.1 | |||||
| 113 | 379 | Male | 50-59 | 00:26:23.6 | 00:25:52.6 | |||||
| 114 | 209 | Male | 40-49 | 00:27:43.7 | 00:25:53.0 | |||||
| 115 | 426 | Female | 10-13 | 00:26:15.1 | 00:25:54.6 | |||||
| 116 | 400 | Male | 10-13 | 00:26:05.5 | 00:25:57.5 | |||||
| 117 | 422 | Male | UK | 00:26:20.9 | 00:25:57.9 | |||||
| 118 | 104 | Male | 10-13 | 00:26:14.5 | 00:25:58.5 | |||||
| 119 | 383 | Male | 10-13 | 00:26:06.6 | 00:26:01.5 | |||||
| 120 | 366 | Female | 40-49 | 00:26:08.2 | 00:26:01.6 | |||||
| 121 | 89 | Male | 10-13 | 00:26:08.0 | 00:26:02.6 | |||||
| 122 | 365 | Male | 7 – 9 Years old | 00:26:08.1 | 00:26:02.8 | |||||
| 123 | 391 | Male | 19-29 | 00:26:34.5 | 00:26:05.9 | |||||
| 124 | 100 | Male | 30-39 | 00:26:09.7 | 00:26:09.7 | |||||
| 125 | 287 | Male | 40-49 | 00:26:23.7 | 00:26:10.5 | |||||
| 126 | 230 | Male | 50-59 | 00:26:28.8 | 00:26:13.9 | |||||
| 127 | 133 | Male | 19-29 | 00:27:13.1 | 00:26:17.0 | |||||
| 128 | 47 | Male | 14-18 | 00:26:46.5 | 00:26:22.4 | |||||
| 129 | 282 | Male | 19-29 | 00:28:51.4 | 00:26:27.3 | |||||
| 130 | 107 | Male | 40-49 | 00:27:30.3 | 00:26:38.7 | |||||
| 131 | 260 | Female | 50-59 | 00:27:11.7 | 00:26:46.7 | |||||
| 132 | 360 | Male | 40-49 | 00:27:41.4 | 00:26:48.0 | |||||
| 133 | 358 | Female | 40-49 | 00:27:42.3 | 00:26:49.3 | |||||
| 134 | 34 | Female | 30-39 | 00:27:08.0 | 00:26:54.2 | |||||
| 135 | 386 | Female | 50-59 | 00:27:38.0 | 00:26:59.1 | |||||
| 136 | 29 | Female | 40-49 | 00:28:22.1 | 00:27:05.5 | |||||
| 137 | 468 | Male | 50-59 | 00:27:35.5 | 00:27:09.1 | |||||
| 138 | 135 | Male | 30-39 | 00:27:58.5 | 00:27:09.7 | |||||
| 139 | 410 | Female | 10-13 | 00:27:19.6 | 00:27:10.0 | |||||
| 140 | 50 | Male | UK | 00:28:09.1 | 00:27:11.7 | |||||
| 141 | 268 | Female | 14-18 | 00:28:35.3 | 00:27:13.2 | |||||
| 142 | 446 | Male | 7 – 9 Years old | 00:27:23.5 | 00:27:13.4 | |||||
| 143 | 293 | Female | 30-39 | 00:27:42.3 | 00:27:15.2 | |||||
| 144 | 132 | Female | 50-59 | 00:28:02.6 | 00:27:17.5 | |||||
| 145 | 131 | Female | 19-29 | 00:28:02.8 | 00:27:19.3 | |||||
| 146 | 438 | Male | 10-13 | 00:27:37.3 | 00:27:26.9 | |||||
| 147 | 388 | Male | 50-59 | 00:27:39.1 | 00:27:29.7 | |||||
| 148 | 491 | Female | 10-13 | 00:28:30.7 | 00:27:31.1 | |||||
| 149 | 370 | Female | 14-18 | 00:27:48.3 | 00:27:31.7 | |||||
| 150 | 93 | Male | 30-39 | 00:28:57.3 | 00:27:36.0 | |||||
| 151 | 90 | Female | 30-39 | 00:28:57.7 | 00:27:36.4 | |||||
| 152 | 201 | Male | 19-29 | 00:28:09.7 | 00:27:37.6 | |||||
| 153 | 254 | Male | 10-13 | 00:28:08.3 | 00:27:50.4 | |||||
| 154 | 139 | Female | 7 – 9 Years old | 00:27:59.5 | 00:27:53.2 | |||||
| 155 | 493 | Female | UK | 00:28:18.8 | 00:27:56.8 | |||||
| 156 | 489 | Female | 10-13 | 00:28:18.1 | 00:27:57.1 | |||||
| 157 | 377 | Female | 50-59 | 00:28:34.3 | 00:28:03.9 | |||||
| 158 | 109 | Male | 40-49 | 00:28:42.4 | 00:28:11.9 | |||||
| 159 | 58 | Male | 40-49 | 00:28:24.1 | 00:28:13.1 | |||||
| 160 | 55 | Male | 7 – 9 Years old | 00:28:23.8 | 00:28:14.9 | |||||
| 161 | 309 | Male | 40-49 | 00:29:30.6 | 00:28:24.5 | |||||
| 162 | 280 | Male | 10-13 | 00:31:39.3 | 00:28:25.2 | |||||
| 163 | 490 | Female | 40-49 | 00:29:25.8 | 00:28:27.9 | |||||
| 164 | 342 | Unknown | UK | 00:29:11.4 | 00:28:31.0 | |||||
| 165 | 375 | Female | 7 – 9 Years old | 00:28:45.8 | 00:28:33.8 | |||||
| 166 | 469 | Female | UK | 00:29:07.1 | 00:28:42.8 | |||||
| 167 | 42 | Female | 14-18 | 00:29:13.0 | 00:28:43.2 | |||||
| 168 | 403 | Male | 50-59 | 00:29:09.7 | 00:28:45.8 | |||||
| 169 | 404 | Male | 10-13 | 00:29:10.1 | 00:28:46.7 | |||||
| 170 | 113 | Female | 7 – 9 Years old | 00:29:17.8 | 00:28:49.9 | |||||
| 171 | 428 | Male | 10-13 | 00:29:09.3 | 00:28:51.4 | |||||
| 172 | 38 | Female | UK | 00:29:32.7 | 00:28:58.3 | |||||
| 173 | 115 | Female | 30-39 | 00:29:28.6 | 00:29:00.3 | |||||
| 174 | 71 | Male | 14-18 | 00:29:32.3 | 00:29:03.7 | |||||
| 175 | 234 | Male | 10-13 | 00:30:30.3 | 00:29:07.9 | |||||
| 176 | 237 | Male | 40-49 | 00:29:28.6 | 00:29:10.0 | |||||
| 177 | 32 | Female | 10-13 | 00:30:28.8 | 00:29:11.4 | |||||
| 178 | 30 | Female | 40-49 | 00:30:28.8 | 00:29:12.7 | |||||
| 179 | 147 | Male | 40-49 | 00:30:36.0 | 00:29:15.7 | |||||
| 180 | 297 | Female | 19-29 | 00:30:32.1 | 00:29:15.9 | |||||
| 181 | 418 | Male | 14-18 | 00:29:40.3 | 00:29:20.8 | |||||
| 182 | 369 | Female | 14-18 | 00:29:41.7 | 00:29:25.5 | |||||
| 183 | 399 | Male | 10-13 | 00:33:31.0 | 00:29:26.0 | |||||
| 184 | 226 | Male | 50-59 | 00:33:29.8 | 00:29:27.7 | |||||
| 185 | 33 | Male | 40-49 | 00:30:05.3 | 00:29:34.5 | |||||
| 186 | 316 | Male | 40-49 | 00:30:33.3 | 00:29:36.5 | |||||
| 187 | 385 | Male | 30-39 | 00:30:22.6 | 00:29:42.4 | |||||
| 188 | 434 | Female | 60-99 | 00:30:06.3 | 00:29:51.3 | |||||
| 189 | 105 | Male | 10-13 | 00:30:08.8 | 00:29:53.1 | |||||
| 190 | 26 | Male | 40-49 | 00:31:15.1 | 00:29:53.9 | |||||
| 191 | 271 | Female | 30-39 | 00:31:19.8 | 00:29:56.2 | |||||
| 192 | 270 | Male | 30-39 | 00:31:20.6 | 00:29:56.8 | |||||
| 193 | 296 | Male | 19-29 | 00:31:11.6 | 00:29:59.0 | |||||
| 194 | 279 | Female | 10-13 | 00:30:24.3 | 00:30:02.5 | |||||
| 195 | 240 | Male | 14-18 | 00:30:58.8 | 00:30:03.3 | |||||
| 196 | 382 | Male | 14-18 | 00:30:17.8 | 00:30:03.9 | |||||
| 197 | 88 | Female | 10-13 | 00:30:29.5 | 00:30:05.3 | |||||
| 198 | 412 | Male | 40-49 | 00:30:48.2 | 00:30:06.5 | |||||
| 199 | 278 | Female | 10-13 | 00:30:28.8 | 00:30:07.3 | |||||
| 200 | 219 | Female | 19-29 | 00:34:09.5 | 00:30:08.6 | |||||
| 201 | 285 | Female | 14-18 | 00:30:44.2 | 00:30:12.5 | |||||
| 202 | 290 | Female | 14-18 | 00:30:49.6 | 00:30:18.5 | |||||
| 203 | 300 | Female | 7 – 9 Years old | 00:30:53.8 | 00:30:19.3 | |||||
| 204 | 94 | Female | 30-39 | 00:31:58.0 | 00:30:37.8 | |||||
| 205 | 253 | Male | 50-59 | 00:31:10.1 | 00:30:43.1 | |||||
| 206 | 2 | Female | 40-49 | 00:31:51.8 | 00:30:43.2 | |||||
| 207 | 319 | Male | 50-59 | 00:31:21.6 | 00:30:44.1 | |||||
| 208 | 289 | Female | 10-13 | 00:31:09.3 | 00:30:44.6 | |||||
| 209 | 353 | Male | 10-13 | 00:31:00.8 | 00:30:46.5 | |||||
| 210 | 37 | Male | 40-49 | 00:31:36.6 | 00:30:47.4 | |||||
| 211 | 251 | Female | 50-59 | 00:31:27.8 | 00:30:49.7 | |||||
| 212 | 259 | Female | 30-39 | 00:31:19.8 | 00:30:50.9 | |||||
| 213 | 9 | Male | 60-99 | 00:31:52.1 | 00:30:51.6 | |||||
| 214 | 463 | Male | 14-18 | 00:31:11.9 | 00:30:56.1 | |||||
| 215 | 4 | Male | 40-49 | 00:32:50.9 | 00:31:06.6 | |||||
| 216 | 450 | Female | 50-59 | 00:31:48.7 | 00:31:13.3 | |||||
| 217 | 313 | Female | 19-29 | 00:32:22.4 | 00:31:21.8 | |||||
| 218 | 62 | Female | 14-18 | 00:32:23.1 | 00:31:25.3 | |||||
| 219 | 84 | Male | 10-13 | 00:32:29.3 | 00:31:27.6 | |||||
| 220 | 456 | Male | 30-39 | 00:32:40.3 | 00:31:31.7 | |||||
| 221 | 83 | Female | 40-49 | 00:32:04.8 | 00:31:32.3 | |||||
| 222 | 129 | Female | 6 & Under | 00:32:41.8 | 00:31:33.6 | |||||
| 223 | 263 | Female | 40-49 | 00:32:35.3 | 00:31:33.6 | |||||
| 224 | 248 | Male | 40-49 | 00:33:03.3 | 00:31:45.7 | |||||
| 225 | 467 | Male | 30-39 | 00:32:26.3 | 00:31:59.7 | |||||
| 226 | 367 | Male | 10-13 | 00:33:26.8 | 00:32:15.8 | |||||
| 227 | 225 | Female | 40-49 | 00:33:14.3 | 00:32:16.4 | |||||
| 228 | 299 | Male | 10-13 | 00:32:50.5 | 00:32:16.6 | |||||
| 229 | 269 | Male | 19-29 | 00:34:44.1 | 00:32:18.9 | |||||
| 230 | 82 | Male | 60-99 | 00:32:54.0 | 00:32:21.1 | |||||
| 231 | 246 | Female | 14-18 | 00:33:45.0 | 00:32:27.8 | |||||
| 232 | 338 | Male | 19-29 | 00:32:41.8 | 00:32:31.6 | |||||
| 233 | 298 | Female | 19-29 | 00:33:09.3 | 00:32:36.3 | |||||
| 234 | 387 | Female | 30-39 | 00:33:15.7 | 00:32:36.3 | |||||
| 235 | 48 | Male | 10-13 | 00:32:43.2 | 00:32:37.7 | |||||
| 236 | 396 | Male | 40-49 | 00:36:42.2 | 00:32:38.0 | |||||
| 237 | 401 | Female | 50-59 | 00:33:30.6 | 00:32:47.2 | |||||
| 238 | 252 | Female | 30-39 | 00:34:19.7 | 00:32:53.3 | |||||
| 239 | 443 | Female | 30-39 | 00:34:19.3 | 00:32:53.6 | |||||
| 240 | 249 | Male | 50-59 | 00:33:51.8 | 00:33:06.3 | |||||
| 241 | 321 | Male | 14-18 | 00:33:46.2 | 00:33:08.6 | |||||
| 242 | 303 | Male | 10-13 | 00:34:11.9 | 00:33:09.5 | |||||
| 243 | 406 | Female | 40-49 | 00:33:43.0 | 00:33:12.0 | |||||
| 244 | 407 | Male | 10-13 | 00:33:26.5 | 00:33:16.9 | |||||
| 245 | 86 | Male | 19-29 | 00:34:20.7 | 00:33:22.4 | |||||
| 246 | 142 | Male | 60-99 | 00:35:29.1 | 00:33:28.0 | |||||
| 247 | 101 | Female | 7 – 9 Years old | 00:34:44.2 | 00:33:31.9 | |||||
| 248 | 322 | Male | 10-13 | 00:33:35.5 | 00:33:31.9 | |||||
| 249 | 128 | Male | 7 – 9 Years old | 00:34:41.1 | 00:33:32.2 | |||||
| 250 | 455 | Female | 30-39 | 00:34:40.9 | 00:33:32.3 | |||||
| 251 | 23 | Female | 10-13 | 00:34:12.5 | 00:33:37.9 | |||||
| 252 | 138 | Male | 19-29 | 00:38:10.8 | 00:33:37.9 | |||||
| 253 | 472 | Female | UK | 00:38:11.1 | 00:33:38.8 | |||||
| 254 | 27 | Female | 10-13 | 00:35:02.7 | 00:33:45.3 | |||||
| 255 | 81 | Male | 60-99 | 00:35:00.3 | 00:33:46.8 | |||||
| 256 | 374 | Female | 40-49 | 00:33:59.3 | 00:33:46.9 | |||||
| 257 | 28 | Female | 10-13 | 00:35:04.3 | 00:33:48.2 | |||||
| 258 | 420 | Male | UK | 00:35:55.6 | 00:33:55.1 | |||||
| 259 | 343 | Unknown | UK | 00:35:14.2 | 00:34:00.4 | |||||
| 260 | 233 | Male | 30-39 | 00:34:38.3 | 00:34:02.6 | |||||
| 261 | 232 | Female | 7 – 9 Years old | 00:34:39.1 | 00:34:04.0 | |||||
| 262 | 121 | Female | UK | 00:35:01.3 | 00:34:08.9 | |||||
| 263 | 221 | Male | 7 – 9 Years old | 00:34:16.8 | 00:34:11.3 | |||||
| 264 | 1 | Male | 40-49 | 00:34:35.1 | 00:34:11.5 | |||||
| 265 | 415 | Female | 30-39 | 00:36:17.8 | 00:34:12.7 | |||||
| 266 | 264 | Male | 40-49 | 00:35:09.0 | 00:34:12.7 | |||||
| 267 | 492 | Male | UK | 00:35:02.8 | 00:34:14.4 | |||||
| 268 | 417 | Male | 30-39 | 00:36:20.4 | 00:34:15.2 | |||||
| 269 | 12 | Female | 14-18 | 00:35:48.8 | 00:34:21.4 | |||||
| 270 | 127 | Female | 19-29 | 00:35:11.6 | 00:34:25.0 | |||||
| 271 | 120 | Male | UK | 00:35:25.3 | 00:34:32.1 | |||||
| 272 | 243 | Female | 10-13 | 00:35:52.6 | 00:34:32.2 | |||||
| 273 | 122 | Female | UK | 00:35:25.8 | 00:34:32.6 | |||||
| 274 | 119 | Unknown | UK | 00:35:29.3 | 00:34:35.9 | |||||
| 275 | 22 | Female | 40-49 | 00:36:09.6 | 00:34:44.7 | |||||
| 276 | 106 | Female | 30-39 | 00:37:00.1 | 00:34:50.7 | |||||
| 277 | 495 | Female | 40-49 | 00:36:01.8 | 00:34:51.8 | |||||
| 278 | 427 | Female | 10-13 | 00:37:08.9 | 00:34:53.7 | |||||
| 279 | 17 | Unknown | UK | 00:35:04.1 | 00:34:59.4 | |||||
| 280 | 239 | Male | 7 – 9 Years old | 00:37:30.6 | 00:35:02.7 | |||||
| 281 | 486 | Male | 60-99 | 00:36:15.7 | 00:35:03.6 | |||||
| 282 | 250 | Female | 40-49 | 00:35:51.7 | 00:35:05.1 | |||||
| 283 | 425 | Male | 40-49 | 00:37:33.7 | 00:35:18.5 | |||||
| 284 | 292 | Male | 30-39 | 00:36:18.3 | 00:35:22.7 | |||||
| 285 | 419 | Female | 50-59 | 00:36:06.8 | 00:35:23.7 | |||||
| 286 | 424 | Female | 40-49 | 00:37:40.1 | 00:35:25.0 | |||||
| 287 | 324 | Male | 60-99 | 00:36:22.6 | 00:35:27.9 | |||||
| 288 | 273 | Female | 10-13 | 00:35:30.1 | 00:35:30.1 | |||||
| 289 | 10 | Female | 14-18 | 00:37:05.3 | 00:35:30.2 | |||||
| 290 | 143 | Male | 60-99 | 00:36:49.4 | 00:35:31.4 | |||||
| 291 | 452 | Male | 60-99 | 00:38:22.8 | 00:35:57.4 | |||||
| 292 | 294 | Female | 40-49 | 00:37:01.0 | 00:36:03.6 | |||||
| 293 | 295 | Male | 50-59 | 00:37:21.1 | 00:36:03.8 | |||||
| 294 | 325 | Female | 40-49 | 00:36:32.5 | 00:36:06.4 | |||||
| 295 | 440 | Male | 14-18 | 00:38:39.7 | 00:36:07.3 | |||||
| 296 | 485 | Male | UK | 00:37:01.6 | 00:36:09.2 | |||||
| 297 | 315 | Female | 10-13 | 00:37:16.4 | 00:36:17.2 | |||||
| 298 | 389 | Male | 10-13 | 00:36:34.8 | 00:36:18.8 | |||||
| 299 | 340 | Unknown | UK | 00:38:04.3 | 00:36:22.5 | |||||
| 300 | 91 | Male | 30-39 | 00:38:08.1 | 00:36:46.9 | |||||
| 301 | 103 | Male | 40-49 | 00:38:09.1 | 00:36:48.8 | |||||
| 302 | 102 | Female | 6 & Under | 00:38:10.3 | 00:36:51.2 | |||||
| 303 | 471 | Female | 50-59 | 00:39:04.3 | 00:36:56.4 | |||||
| 304 | 65 | Male | 10-13 | 00:38:04.0 | 00:37:06.7 | |||||
| 305 | 110 | Male | 60-99 | 00:38:42.0 | 00:37:51.1 | |||||
| 306 | 247 | Female | 19-29 | 00:38:11.1 | 00:37:56.8 | |||||
| 307 | 432 | Female | 50-59 | 00:39:16.3 | 00:38:10.3 | |||||
| 308 | 430 | Male | 50-59 | 00:39:15.9 | 00:38:10.8 | |||||
| 309 | 449 | Male | 30-39 | 00:38:22.6 | 00:38:22.6 | |||||
| 310 | 275 | Male | 10-13 | 00:42:13.7 | 00:38:39.0 | |||||
| 311 | 222 | Female | 30-39 | 00:38:44.3 | 00:38:39.7 | |||||
| 312 | 397 | Female | 40-49 | 00:42:49.7 | 00:38:45.9 | |||||
| 313 | 402 | Female | 10-13 | 00:41:45.1 | 00:38:46.2 | |||||
| 314 | 210 | Female | 40-49 | 00:40:26.9 | 00:38:48.4 | |||||
| 315 | 245 | Female | 40-49 | 00:40:51.6 | 00:38:59.4 | |||||
| 316 | 244 | Female | 14-18 | 00:40:52.4 | 00:39:00.0 | |||||
| 317 | 145 | Female | 40-49 | 00:45:09.2 | 00:39:00.9 | |||||
| 318 | 92 | Female | 30-39 | 00:41:16.1 | 00:39:56.5 | |||||
| 319 | 266 | Male | 60-99 | 00:42:54.8 | 00:40:15.6 | |||||
| 320 | 497 | Male | 40-49 | 00:43:10.8 | 00:40:34.6 | |||||
| 321 | 206 | Male | 19-29 | 00:50:35.8 | 00:40:36.7 | |||||
| 322 | 35 | Female | UK | 00:41:55.1 | 00:40:38.9 | |||||
| 323 | 496 | Male | 7 – 9 Years old | 00:43:10.4 | 00:40:42.5 | |||||
| 324 | 3 | Female | 50-59 | 00:41:40.2 | 00:40:48.6 | |||||
| 325 | 213 | Unknown | UK | 00:45:36.1 | 00:40:51.1 | |||||
| 326 | 304 | Female | 14-18 | 00:44:28.3 | 00:41:02.9 | |||||
| 327 | 499 | Female | 10-13 | 00:43:34.6 | 00:41:03.2 | |||||
| 328 | 500 | Female | 40-49 | 00:43:36.5 | 00:41:04.2 | |||||
| 329 | 19 | Female | 40-49 | 00:41:12.3 | 00:41:07.2 | |||||
| 330 | 498 | Female | 40-49 | 00:43:39.8 | 00:41:11.2 | |||||
| 331 | 307 | Female | 40-49 | 00:45:09.1 | 00:41:43.3 | |||||
| 332 | 284 | Male | 10-13 | 00:43:15.6 | 00:42:01.4 | |||||
| 333 | 64 | Female | 40-49 | 00:45:11.2 | 00:42:25.7 | |||||
| 334 | 44 | Female | 40-49 | 00:45:29.1 | 00:42:26.7 | |||||
| 335 | 80 | Female | 7 – 9 Years old | 00:43:55.7 | 00:42:37.5 | |||||
| 336 | 116 | Male | 30-39 | 00:42:38.1 | 00:42:38.1 | |||||
| 337 | 108 | Female | 60-99 | 00:44:03.3 | 00:42:52.4 | |||||
| 338 | 61 | Male | 14-18 | 00:45:43.2 | 00:42:56.3 | |||||
| 339 | 211 | Male | 10-13 | 00:44:40.7 | 00:43:01.5 | |||||
| 340 | 241 | Male | 7 – 9 Years old | 00:45:38.3 | 00:43:12.5 | |||||
| 341 | 242 | Male | 40-49 | 00:45:37.7 | 00:43:12.8 | |||||
| 342 | 314 | Female | 40-49 | 00:44:23.6 | 00:43:24.7 | |||||
| 343 | 378 | Female | 14-18 | 00:44:40.7 | 00:43:27.4 | |||||
| 344 | 16 | Female | 14-18 | 00:43:39.4 | 00:43:34.6 | |||||
| 345 | 97 | Female | 30-39 | 00:45:45.9 | 00:43:38.0 | |||||
| 346 | 98 | Male | 7 – 9 Years old | 00:45:47.3 | 00:43:38.8 | |||||
| 347 | 39 | Male | UK | 00:46:11.9 | 00:43:45.3 | |||||
| 348 | 355 | Male | 40-49 | 00:45:46.1 | 00:44:05.0 | |||||
| 349 | 484 | Female | UK | 00:45:17.7 | 00:44:33.9 | |||||
| 350 | 448 | Male | 40-49 | 00:45:41.8 | 00:45:31.8 | |||||
| 351 | 398 | Female | 14-18 | 00:50:13.3 | 00:46:10.2 | |||||
| 352 | 483 | Female | UK | 00:46:56.3 | 00:46:11.7 | |||||
| 353 | 150 | Female | 10-13 | 00:49:28.5 | 00:46:31.0 | |||||
| 354 | 423 | Male | UK | 00:48:47.1 | 00:46:49.9 | |||||
| 355 | 421 | Male | UK | 00:48:47.1 | 00:46:50.4 | |||||
| 356 | 220 | Female | 7 – 9 Years old | 00:47:04.8 | 00:47:00.0 | |||||
| 357 | 356 | Male | 7 – 9 Years old | 00:48:46.3 | 00:47:00.4 | |||||
| 358 | 267 | Female | 60-99 | 00:50:10.3 | 00:47:31.4 | |||||
| 359 | 66 | Female | 40-49 | 00:48:15.8 | 00:47:33.6 | |||||
| 360 | 134 | Male | 19-29 | 00:49:32.0 | 00:47:45.0 | |||||
| 361 | 148 | Female | 10-13 | 00:49:14.6 | 00:48:00.9 | |||||
| 362 | 323 | Female | 7 – 9 Years old | 00:49:14.0 | 00:48:01.5 | |||||
| 363 | 361 | Female | 50-59 | 00:49:35.0 | 00:48:07.1 | |||||
| 364 | 362 | Female | 30-39 | 00:49:35.4 | 00:48:07.2 | |||||
| 365 | 352 | Female | 40-49 | 00:50:09.4 | 00:48:22.2 | |||||
| 366 | 312 | Female | 40-49 | 00:51:27.9 | 00:48:35.0 | |||||
| 367 | 262 | Female | 14-18 | 00:52:25.1 | 00:49:44.5 | |||||
| 368 | 474 | Female | UK | 00:52:27.2 | 00:50:00.8 | |||||
| 369 | 376 | Female | 19-29 | 00:53:02.7 | 00:50:21.3 | |||||
| 370 | 429 | Male | 40-49 | 00:55:28.5 | 00:51:55.8 | |||||
| 371 | 118 | Female | 30-39 | 00:55:29.3 | 00:54:52.8 | |||||
| 372 | 67 | Male | 40-49 | 00:56:44.9 | 00:56:01.7 | |||||
| 373 | 117 | Female | 30-39 | 00:56:43.5 | 00:56:05.9 | |||||
| 374 | 40 | Female | UK | 00:59:48.6 | 00:56:26.4 | |||||
| 375 | 457 | Male | 14-18 | 00:59:07.6 | 00:56:37.3 | |||||
| 376 | 395 | Male | 19-29 | 00:59:06.1 | 00:57:08.1 | |||||
| 377 | 394 | Female | 19-29 | 00:59:06.3 | 00:57:08.1 | |||||
| 378 | 392 | Female | 60-99 | 00:59:22.8 | 00:57:26.4 | |||||
| 379 | 393 | Male | 60-99 | 00:59:25.3 | 00:57:28.5 | |||||
| 380 | 327 | Male | 19-29 | 01:02:18.1 | 00:58:39.4 | |||||
| 381 | 21 | Unknown | UK | 01:01:17.9 | 00:58:41.8 | |||||
| 382 | 330 | Female | 19-29 | 01:02:23.5 | 00:58:42.5 | |||||
| 383 | 20 | Male | 50-59 | 01:01:18.8 | 00:58:42.7 | |||||
| 384 | 414 | Male | 14-18 | 01:02:22.9 | 00:58:42.8 | |||||
| 385 | 331 | Male | 50-59 | 01:02:20.4 | 00:58:43.3 | |||||
| 386 | 328 | Male | 19-29 | 01:02:20.6 | 00:58:43.7 | |||||
| 387 | 216 | Unknown | UK | 01:02:57.9 | 00:58:57.4 | |||||
| 388 | 215 | Unknown | UK | 01:02:58.9 | 00:58:58.3 | |||||
| 389 | 7 | Male | 10-13 | 01:05:03.9 | 01:00:43.2 | |||||
| 390 | 8 | Female | 7 – 9 Years old | 01:05:12.0 | 01:00:53.4 | |||||
| 391 | 123 | Female | 7 – 9 Years old | 01:04:49.6 | 01:02:26.9 | |||||
| 392 | 439 | Female | 40-49 | 01:05:05.1 | 01:02:29.2 | |||||
| 393 | 442 | Female | 7 – 9 Years old | 01:05:05.6 | 01:02:31.4 | |||||
| 394 | 441 | Female | 10-13 | 01:05:07.1 | 01:02:31.5 | |||||
| 395 | 357 | Male | 10-13 | 01:11:47.5 | 01:07:52.3 | |||||
| 396 | 217 | Unknown | UK | 01:14:14.4 | 01:09:18.2 | |||||
| 397 | 212 | Unknown | UK | 01:14:13.9 | 01:09:18.3 | |||||
| 398 | 214 | Unknown | UK | 01:14:09.9 | 01:09:18.7 | |||||
| 399 | 302 | Female | 30-39 | 01:18:29.3 | 01:12:32.3 | |||||
| 400 | 306 | Male | 30-39 | 01:18:43.3 | 01:12:45.1 |
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