Official Event Results
2023 Hill Country Turkey Trot
Event Date
11/23/2023
Races
1
Result Rows
303
Split Rows
606
Entered
303
Finishers
302
Fastest Time
16:27
Average Time
32:59
| Place | Race No | Name | Gender | Division | Time | Chip Time | Pace | City | State | Details |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 147 | Male | Overall | 00:16:27.7 | 00:16:25.9 | |||||
| 2 | 162 | Male | Overall | 00:17:34.4 | 00:17:34.2 | |||||
| 3 | 264 | Male | Overall | 00:17:35.1 | 00:17:34.5 | |||||
| 4 | 131 | Male | 40-49 | 00:18:04.1 | 00:18:03.1 | |||||
| 5 | 471 | Male | 14-18 | 00:18:17.5 | 00:18:16.6 | |||||
| 6 | 324 | Male | 14-18 | 00:18:26.4 | 00:18:25.5 | |||||
| 7 | 374 | Male | 14-18 | 00:18:32.7 | 00:18:30.6 | |||||
| 8 | 454 | Male | 14-18 | 00:18:32.3 | 00:18:31.6 | |||||
| 9 | 232 | Male | 40-49 | 00:18:37.0 | 00:18:34.7 | |||||
| 10 | 369 | Male | 40-49 | 00:18:40.8 | 00:18:37.9 | |||||
| 11 | 450 | Male | 40-49 | 00:18:41.0 | 00:18:38.6 | |||||
| 12 | 437 | Male | 14-18 | 00:18:57.4 | 00:18:53.3 | |||||
| 13 | 108 | Male | 14-18 | 00:18:56.9 | 00:18:53.5 | |||||
| 14 | 448 | Male | 14-18 | 00:18:58.1 | 00:18:53.6 | |||||
| 15 | 249 | Male | 14-18 | 00:18:57.2 | 00:18:56.0 | |||||
| 16 | 459 | Male | 14-18 | 00:18:58.7 | 00:18:57.7 | |||||
| 17 | 325 | Male | 10-13 | 00:18:58.5 | 00:18:58.3 | |||||
| 18 | 263 | Male | 14-18 | 00:19:08.6 | 00:19:07.7 | |||||
| 19 | 445 | Male | 14-18 | 00:19:15.9 | 00:19:13.0 | |||||
| 20 | 368 | Male | 10-13 | 00:19:22.2 | 00:19:22.2 | |||||
| 21 | 327 | Male | 40-49 | 00:19:41.7 | 00:19:40.5 | |||||
| 22 | 417 | Male | 14-18 | 00:19:47.3 | 00:19:42.9 | |||||
| 23 | 130 | Female | Overall | 00:19:50.0 | 00:19:47.6 | |||||
| 24 | 422 | Male | 7 – 9 Years old | 00:19:53.9 | 00:19:51.1 | |||||
| 25 | 491 | Male | 50-59 | 00:20:08.6 | 00:20:06.2 | |||||
| 26 | 253 | Male | 19-29 | 00:20:14.7 | 00:20:10.7 | |||||
| 27 | 254 | Male | 19-29 | 00:20:12.2 | 00:20:11.0 | |||||
| 28 | 262 | Female | Overall | 00:20:27.9 | 00:20:23.0 | |||||
| 29 | 283 | Female | Overall | 00:20:30.7 | 00:20:28.5 | |||||
| 30 | 212 | Female | 19-29 | 00:21:10.4 | 00:20:55.3 | |||||
| 31 | 149 | Male | 50-59 | 00:21:03.2 | 00:20:57.1 | |||||
| 32 | 312 | Male | 30-39 | 00:21:14.6 | 00:21:08.2 | |||||
| 33 | 255 | Male | 50-59 | 00:21:11.7 | 00:21:09.5 | |||||
| 34 | 350 | Male | 14-18 | 00:21:14.2 | 00:21:09.9 | |||||
| 35 | 231 | Female | 14-18 | 00:21:20.1 | 00:21:15.6 | |||||
| 36 | 466 | Female | 10-13 | 00:21:19.5 | 00:21:15.6 | |||||
| 37 | 234 | Female | 14-18 | 00:21:23.7 | 00:21:19.7 | |||||
| 38 | 317 | Male | 14-18 | 00:21:39.4 | 00:21:37.8 | |||||
| 39 | 221 | Female | 19-29 | 00:21:44.4 | 00:21:39.8 | |||||
| 40 | 102 | Male | 10-13 | 00:21:43.7 | 00:21:40.4 | |||||
| 41 | 141 | Male | 10-13 | 00:21:44.0 | 00:21:41.4 | |||||
| 42 | 105 | Male | 10-13 | 00:21:45.8 | 00:21:43.2 | |||||
| 43 | 397 | Male | 14-18 | 00:21:49.9 | 00:21:45.8 | |||||
| 44 | 158 | Male | 30-39 | 00:21:51.9 | 00:21:46.3 | |||||
| 45 | 370 | Male | 14-18 | 00:21:54.4 | 00:21:51.6 | |||||
| 46 | 326 | Male | 10-13 | 00:22:05.9 | 00:22:04.6 | |||||
| 47 | 123 | Male | 30-39 | 00:22:24.2 | 00:22:15.0 | |||||
| 48 | 157 | Male | 19-29 | 00:22:21.7 | 00:22:17.2 | |||||
| 49 | 456 | Male | 14-18 | 00:22:25.2 | 00:22:23.6 | |||||
| 50 | 265 | Male | 19-29 | 00:22:44.9 | 00:22:35.5 | |||||
| 51 | 239 | Female | 30-39 | 00:22:48.4 | 00:22:41.0 | |||||
| 52 | 284 | Female | 10-13 | 00:22:48.7 | 00:22:47.1 | |||||
| 53 | 495 | Female | 10-13 | 00:22:50.2 | 00:22:47.9 | |||||
| 54 | 197 | Female | 30-39 | 00:22:59.1 | 00:22:49.7 | |||||
| 55 | 447 | Male | 10-13 | 00:23:34.2 | 00:23:02.8 | |||||
| 56 | 500 | Male | 10-13 | 00:23:08.4 | 00:23:07.8 | |||||
| 57 | 371 | Female | 14-18 | 00:23:33.4 | 00:23:11.7 | |||||
| 58 | 472 | Female | 10-13 | 00:23:16.2 | 00:23:12.5 | |||||
| 59 | 474 | Male | 10-13 | 00:23:14.4 | 00:23:14.0 | |||||
| 60 | 396 | Male | 10-13 | 00:23:30.2 | 00:23:14.4 | |||||
| 61 | 449 | Female | 14-18 | 00:23:20.9 | 00:23:16.8 | |||||
| 62 | 199 | Male | 14-18 | 00:23:55.9 | 00:23:17.5 | |||||
| 63 | 352 | Male | 50-59 | 00:23:35.0 | 00:23:25.0 | |||||
| 64 | 270 | Female | 40-49 | 00:23:38.7 | 00:23:28.0 | |||||
| 65 | 251 | Male | 10-13 | 00:23:44.6 | 00:23:40.3 | |||||
| 66 | 188 | Male | 10-13 | 00:23:48.3 | 00:23:40.9 | |||||
| 67 | 490 | Female | 30-39 | 00:23:52.4 | 00:23:41.3 | |||||
| 68 | 463 | Male | 10-13 | 00:23:45.6 | 00:23:42.2 | |||||
| 69 | 473 | Female | 40-49 | 00:23:45.9 | 00:23:42.7 | |||||
| 70 | 479 | Male | 40-49 | 00:23:51.5 | 00:23:42.9 | |||||
| 71 | 489 | Male | 14-18 | 00:23:53.4 | 00:23:49.7 | |||||
| 72 | 486 | Male | 14-18 | 00:23:53.6 | 00:23:50.5 | |||||
| 73 | 115 | Male | 40-49 | 00:24:12.9 | 00:23:53.8 | |||||
| 74 | 282 | Female | 40-49 | 00:24:01.7 | 00:23:55.3 | |||||
| 75 | 237 | Female | Overall | 00:24:11.9 | 00:23:55.4 | |||||
| 76 | 334 | Male | 10-13 | 00:23:57.3 | 00:23:55.7 | |||||
| 77 | 280 | Male | UK | 00:24:08.0 | 00:24:06.6 | |||||
| 78 | 432 | Male | 14-18 | 00:28:44.7 | 00:24:11.5 | |||||
| 79 | 200 | Male | 30-39 | 00:24:26.7 | 00:24:13.0 | |||||
| 80 | 353 | Male | 10-13 | 00:24:31.6 | 00:24:27.5 | |||||
| 81 | 462 | Female | 10-13 | 00:24:45.2 | 00:24:29.3 | |||||
| 82 | 107 | Female | 40-49 | 00:24:51.3 | 00:24:36.8 | |||||
| 83 | 203 | Male | 50-59 | 00:24:57.6 | 00:24:49.8 | |||||
| 84 | 204 | Male | 10-13 | 00:25:00.2 | 00:24:52.3 | |||||
| 85 | 419 | Male | 30-39 | 00:25:30.5 | 00:24:53.2 | |||||
| 86 | 484 | Male | 10-13 | 00:25:00.2 | 00:24:59.2 | |||||
| 87 | 116 | Male | 10-13 | 00:25:21.0 | 00:25:01.4 | |||||
| 88 | 267 | Male | 10-13 | 00:25:21.6 | 00:25:01.4 | |||||
| 89 | 301 | Female | 14-18 | 00:25:07.7 | 00:25:01.8 | |||||
| 90 | 252 | Female | 14-18 | 00:25:11.9 | 00:25:07.3 | |||||
| 91 | 124 | Female | 30-39 | 00:25:22.2 | 00:25:11.3 | |||||
| 92 | 240 | Male | 50-59 | 00:25:27.3 | 00:25:15.4 | |||||
| 93 | 213 | Male | 50-59 | 00:25:33.4 | 00:25:16.7 | |||||
| 94 | 250 | Female | 40-49 | 00:25:33.4 | 00:25:29.5 | |||||
| 95 | 344 | Male | 40-49 | 00:26:02.4 | 00:25:31.0 | |||||
| 96 | 274 | Male | 14-18 | 00:29:02.0 | 00:25:32.6 | |||||
| 97 | 302 | Female | 14-18 | 00:25:46.0 | 00:25:40.9 | |||||
| 98 | 375 | Female | 40-49 | 00:26:29.2 | 00:25:48.9 | |||||
| 99 | 356 | Female | 40-49 | 00:26:17.4 | 00:25:50.3 | |||||
| 100 | 481 | Male | 14-18 | 00:26:00.7 | 00:25:53.1 | |||||
| 101 | 345 | Female | 10-13 | 00:26:02.6 | 00:25:55.4 | |||||
| 102 | 337 | Female | 30-39 | 00:26:23.4 | 00:26:15.5 | |||||
| 103 | 172 | Male | 19-29 | 00:26:46.6 | 00:26:15.7 | |||||
| 104 | 465 | Female | 19-29 | 00:26:41.9 | 00:26:27.2 | |||||
| 105 | 198 | Male | 7 – 9 Years old | 00:26:49.1 | 00:26:34.9 | |||||
| 106 | 475 | Female | 14-18 | 00:26:44.4 | 00:26:39.1 | |||||
| 107 | 241 | Female | 14-18 | 00:26:46.9 | 00:26:41.4 | |||||
| 108 | 178 | Male | 10-13 | 00:27:13.9 | 00:26:42.2 | |||||
| 109 | 386 | Female | 10-13 | 00:26:51.9 | 00:26:42.3 | |||||
| 110 | 220 | Female | 19-29 | 00:27:05.7 | 00:26:47.3 | |||||
| 111 | 400 | Female | 19-29 | 00:26:58.7 | 00:26:48.0 | |||||
| 112 | 494 | Male | 14-18 | 00:27:14.1 | 00:26:51.0 | |||||
| 113 | 360 | Female | 14-18 | 00:27:33.9 | 00:26:53.8 | |||||
| 114 | 222 | Male | 40-49 | 00:27:49.4 | 00:27:01.0 | |||||
| 115 | 303 | Male | 50-59 | 00:28:32.9 | 00:27:01.5 | |||||
| 116 | 382 | Male | 40-49 | 00:32:12.9 | 00:27:09.0 | |||||
| 117 | 106 | Male | 50-59 | 00:27:37.6 | 00:27:11.1 | |||||
| 118 | 101 | Male | 7 – 9 Years old | 00:27:25.8 | 00:27:11.9 | |||||
| 119 | 179 | Male | 10-13 | 00:27:52.0 | 00:27:20.2 | |||||
| 120 | 268 | Male | 30-39 | 00:27:53.9 | 00:27:33.2 | |||||
| 121 | 104 | Female | 40-49 | 00:28:15.6 | 00:27:41.3 | |||||
| 122 | 347 | Female | 14-18 | 00:29:16.6 | 00:27:47.7 | |||||
| 123 | 455 | Female | 50-59 | 00:28:00.7 | 00:27:49.8 | |||||
| 124 | 342 | Female | 19-29 | 00:28:33.9 | 00:27:54.3 | |||||
| 125 | 266 | Female | 40-49 | 00:28:36.4 | 00:28:15.3 | |||||
| 126 | 310 | Female | 10-13 | 00:28:23.3 | 00:28:20.5 | |||||
| 127 | 320 | Male | 19-29 | 00:28:28.6 | 00:28:21.7 | |||||
| 128 | 189 | Female | 14-18 | 00:28:30.3 | 00:28:22.7 | |||||
| 129 | 423 | Male | 40-49 | 00:30:50.2 | 00:28:26.0 | |||||
| 130 | 119 | Male | 10-13 | 00:29:17.6 | 00:28:39.9 | |||||
| 131 | 468 | Male | 10-13 | 00:28:59.1 | 00:28:46.3 | |||||
| 132 | 348 | Female | 40-49 | 00:30:15.1 | 00:28:47.2 | |||||
| 133 | 257 | Male | 10-13 | 00:28:57.1 | 00:28:47.9 | |||||
| 134 | 118 | Male | 40-49 | 00:29:24.9 | 00:28:48.0 | |||||
| 135 | 389 | Female | 30-39 | 00:29:27.9 | 00:28:59.3 | |||||
| 136 | 269 | Male | 14-18 | 00:29:51.1 | 00:29:01.5 | |||||
| 137 | 496 | Male | 19-29 | 00:29:27.7 | 00:29:04.3 | |||||
| 138 | 467 | Male | 40-49 | 00:29:22.7 | 00:29:09.8 | |||||
| 139 | 233 | Male | 10-13 | 00:29:34.1 | 00:29:10.0 | |||||
| 140 | 453 | Male | 40-49 | 00:29:22.1 | 00:29:11.1 | |||||
| 141 | 126 | Male | 14-18 | 00:30:51.9 | 00:29:12.2 | |||||
| 142 | 103 | Male | 40-49 | 00:29:52.2 | 00:29:17.1 | |||||
| 143 | 209 | Male | 10-13 | 00:29:36.7 | 00:29:17.1 | |||||
| 144 | 173 | Female | 19-29 | 00:29:17.2 | 00:29:17.2 | |||||
| 145 | 171 | Male | 10-13 | 00:32:44.5 | 00:29:24.8 | |||||
| 146 | 306 | Male | 60-99 | 00:29:52.9 | 00:29:26.0 | |||||
| 147 | 351 | Female | 60-99 | 00:30:12.7 | 00:29:28.0 | |||||
| 148 | 464 | Male | 10-13 | 00:29:55.2 | 00:29:29.0 | |||||
| 149 | 498 | Male | 40-49 | 00:30:13.9 | 00:29:29.4 | |||||
| 150 | 430 | Male | 50-59 | 00:34:34.9 | 00:29:38.0 | |||||
| 151 | 357 | Male | 10-13 | 00:30:48.6 | 00:29:41.5 | |||||
| 152 | 298 | Male | 10-13 | 00:30:51.2 | 00:29:44.1 | |||||
| 153 | 367 | Female | 30-39 | 00:32:05.4 | 00:29:45.5 | |||||
| 154 | 279 | Male | 60-99 | 00:31:26.8 | 00:29:45.9 | |||||
| 155 | 366 | Mixed | UK | 00:32:05.9 | 00:29:46.0 | |||||
| 156 | 145 | Female | 19-29 | 00:31:05.7 | 00:29:48.5 | |||||
| 157 | 196 | Male | 10-13 | 00:31:02.1 | 00:29:49.8 | |||||
| 158 | 488 | Female | 60-99 | 00:30:09.2 | 00:29:56.0 | |||||
| 159 | 434 | Female | 30-39 | 00:30:09.2 | 00:29:56.2 | |||||
| 160 | 236 | Female | 19-29 | 00:30:39.4 | 00:30:00.6 | |||||
| 161 | 319 | Female | 10-13 | 00:32:46.7 | 00:30:01.6 | |||||
| 162 | 144 | Male | 19-29 | 00:31:29.7 | 00:30:12.1 | |||||
| 163 | 143 | Female | 40-49 | 00:31:35.4 | 00:30:17.5 | |||||
| 164 | 295 | Female | 14-18 | 00:30:59.8 | 00:30:18.5 | |||||
| 165 | 208 | Female | 50-59 | 00:30:42.1 | 00:30:20.3 | |||||
| 166 | 485 | Female | 40-49 | 00:31:59.4 | 00:30:27.8 | |||||
| 167 | 137 | Female | 19-29 | 00:31:10.4 | 00:30:28.6 | |||||
| 168 | 181 | Female | 19-29 | 00:39:12.8 | 00:30:30.1 | |||||
| 169 | 418 | Female | 7 – 9 Years old | 00:30:32.2 | 00:30:31.6 | |||||
| 170 | 354 | Male | 10-13 | 00:30:49.4 | 00:30:45.0 | |||||
| 171 | 170 | Male | 10-13 | 00:34:10.3 | 00:30:51.1 | |||||
| 172 | 315 | Male | 50-59 | 00:32:11.1 | 00:30:56.2 | |||||
| 173 | 316 | Female | 10-13 | 00:32:12.2 | 00:30:56.8 | |||||
| 174 | 278 | Female | 60-99 | 00:32:47.1 | 00:31:07.8 | |||||
| 175 | 277 | Female | 19-29 | 00:33:08.3 | 00:31:28.2 | |||||
| 176 | 388 | Male | 30-39 | 00:32:04.3 | 00:31:35.6 | |||||
| 177 | 404 | Female | 10-13 | 00:31:44.1 | 00:31:35.9 | |||||
| 178 | 300 | Male | 40-49 | 00:32:48.1 | 00:31:39.6 | |||||
| 179 | 425 | Female | 40-49 | 00:34:04.2 | 00:31:41.3 | |||||
| 180 | 113 | Male | 40-49 | 00:32:23.8 | 00:31:47.6 | |||||
| 181 | 110 | Female | 40-49 | 00:32:23.7 | 00:31:48.0 | |||||
| 182 | 428 | Male | 10-13 | 00:33:01.8 | 00:31:51.5 | |||||
| 183 | 429 | Female | 40-49 | 00:33:02.2 | 00:31:52.3 | |||||
| 184 | 243 | Male | 10-13 | 00:31:54.1 | 00:31:53.5 | |||||
| 185 | 175 | Male | 10-13 | 00:31:54.4 | 00:31:54.1 | |||||
| 186 | 346 | Female | 50-59 | 00:40:21.2 | 00:31:54.8 | |||||
| 187 | 245 | Male | 7 – 9 Years old | 00:32:38.6 | 00:31:55.4 | |||||
| 188 | 187 | Male | 7 – 9 Years old | 00:32:14.9 | 00:32:05.5 | |||||
| 189 | 361 | Male | 40-49 | 00:34:30.9 | 00:32:08.6 | |||||
| 190 | 217 | Male | UK | 00:35:15.7 | 00:32:16.7 | |||||
| 191 | 216 | Mixed | UK | 00:35:15.5 | 00:32:17.1 | |||||
| 192 | 318 | Male | 40-49 | 00:35:00.0 | 00:32:19.8 | |||||
| 193 | 343 | Female | 14-18 | 00:33:37.3 | 00:32:20.7 | |||||
| 194 | 244 | Male | 40-49 | 00:33:13.4 | 00:32:29.3 | |||||
| 195 | 218 | Male | 50-59 | 00:33:47.3 | 00:32:30.6 | |||||
| 196 | 313 | Male | 50-59 | 00:33:00.6 | 00:32:42.8 | |||||
| 197 | 314 | Male | 10-13 | 00:33:01.9 | 00:32:43.8 | |||||
| 198 | 493 | Female | 19-29 | 00:33:10.4 | 00:32:46.9 | |||||
| 199 | 148 | Male | 40-49 | 00:34:23.4 | 00:32:51.6 | |||||
| 200 | 205 | Female | 30-39 | 00:33:55.9 | 00:32:53.8 | |||||
| 201 | 442 | Female | 40-49 | 00:36:43.2 | 00:32:58.1 | |||||
| 202 | 153 | Female | 10-13 | 00:34:02.9 | 00:33:00.5 | |||||
| 203 | 191 | Female | 10-13 | 00:34:30.3 | 00:33:07.3 | |||||
| 204 | 387 | Male | 10-13 | 00:33:19.4 | 00:33:11.5 | |||||
| 205 | 385 | Male | 10-13 | 00:33:19.6 | 00:33:13.2 | |||||
| 206 | 168 | Female | 40-49 | 00:33:54.7 | 00:33:27.5 | |||||
| 207 | 399 | Male | 19-29 | 00:33:38.0 | 00:33:27.7 | |||||
| 208 | 497 | Female | 40-49 | 00:34:27.7 | 00:33:44.9 | |||||
| 209 | 391 | Male | 7 – 9 Years old | 00:34:53.4 | 00:33:45.7 | |||||
| 210 | 390 | Female | 30-39 | 00:34:53.5 | 00:33:45.8 | |||||
| 211 | 307 | Female | 14-18 | 00:34:00.9 | 00:33:52.4 | |||||
| 212 | 499 | Male | 10-13 | 00:34:55.6 | 00:34:13.4 | |||||
| 213 | 321 | Female | 14-18 | 00:34:58.6 | 00:34:15.2 | |||||
| 214 | 470 | Male | 60-99 | 00:34:33.6 | 00:34:16.3 | |||||
| 215 | 299 | Male | UK | 00:35:28.1 | 00:34:19.5 | |||||
| 216 | 259 | Female | 40-49 | 00:34:40.1 | 00:34:20.0 | |||||
| 217 | 190 | Female | 30-39 | 00:34:29.6 | 00:34:22.0 | |||||
| 218 | 492 | Female | 50-59 | 00:34:51.3 | 00:34:27.2 | |||||
| 219 | 398 | Female | UK | 00:36:09.5 | 00:35:05.5 | |||||
| 220 | 444 | Female | 19-29 | 00:39:51.9 | 00:36:06.7 | |||||
| 221 | 309 | Female | 19-29 | 00:39:51.7 | 00:36:07.0 | |||||
| 222 | 443 | Male | 50-59 | 00:40:03.7 | 00:36:19.0 | |||||
| 223 | 331 | Female | 19-29 | 00:38:44.5 | 00:36:19.1 | |||||
| 224 | 446 | Male | 60-99 | 00:37:26.9 | 00:36:22.2 | |||||
| 225 | 129 | Female | 14-18 | 00:37:52.0 | 00:36:34.3 | |||||
| 226 | 287 | Male | 60-99 | 00:37:09.2 | 00:36:41.7 | |||||
| 227 | 210 | Male | 40-49 | 00:38:15.2 | 00:36:48.5 | |||||
| 228 | 349 | Male | 40-49 | 00:38:22.6 | 00:36:52.9 | |||||
| 229 | 177 | Female | 50-59 | 00:37:50.0 | 00:36:59.2 | |||||
| 230 | 487 | Female | 60-99 | 00:38:28.9 | 00:37:05.9 | |||||
| 231 | 151 | Male | 14-18 | 00:38:17.9 | 00:37:14.9 | |||||
| 232 | 121 | Female | 7 – 9 Years old | 00:37:53.9 | 00:37:22.8 | |||||
| 233 | 383 | Female | UK | 00:38:18.1 | 00:37:37.5 | |||||
| 234 | 461 | Male | 7 – 9 Years old | 00:38:01.7 | 00:37:45.5 | |||||
| 235 | 296 | Male | 10-13 | 00:39:41.0 | 00:38:06.4 | |||||
| 236 | 211 | Female | 10-13 | 00:39:35.0 | 00:38:07.8 | |||||
| 237 | 219 | Female | 50-59 | 00:39:32.5 | 00:38:14.9 | |||||
| 238 | 275 | Female | 50-59 | 00:42:25.5 | 00:39:03.6 | |||||
| 239 | 150 | Male | 10-13 | 00:40:20.8 | 00:39:17.9 | |||||
| 240 | 161 | Female | 40-49 | 00:44:31.4 | 00:39:28.7 | |||||
| 241 | 297 | Female | 40-49 | 00:42:26.2 | 00:40:53.6 | |||||
| 242 | 215 | Male | 14-18 | 00:48:59.0 | 00:40:53.9 | |||||
| 243 | 292 | Male | 10-13 | 00:42:47.0 | 00:41:02.6 | |||||
| 244 | 392 | Female | 50-59 | 00:42:57.7 | 00:41:04.1 | |||||
| 245 | 125 | Female | 40-49 | 00:42:57.0 | 00:41:16.4 | |||||
| 246 | 127 | Male | 40-49 | 00:42:59.0 | 00:41:16.8 | |||||
| 247 | 436 | Male | 40-49 | 00:44:01.5 | 00:41:33.9 | |||||
| 248 | 435 | Female | 40-49 | 00:44:01.3 | 00:41:35.0 | |||||
| 249 | 146 | Male | 60-99 | 00:42:02.0 | 00:41:41.3 | |||||
| 250 | 433 | Male | 30-39 | 00:42:08.8 | 00:42:08.8 | |||||
| 251 | 180 | Male | 19-29 | 00:50:40.9 | 00:42:18.2 | |||||
| 252 | 362 | Female | 40-49 | 00:44:51.5 | 00:42:30.3 | |||||
| 253 | 482 | Female | 10-13 | 00:42:45.7 | 00:42:37.5 | |||||
| 254 | 393 | Female | 50-59 | 00:42:56.9 | 00:42:46.3 | |||||
| 255 | 358 | Male | 60-99 | 00:45:48.2 | 00:43:11.8 | |||||
| 256 | 431 | Female | 14-18 | 00:51:11.2 | 00:43:29.3 | |||||
| 257 | 133 | Female | 60-99 | 00:46:06.1 | 00:43:30.0 | |||||
| 258 | 192 | Male | 60-99 | 00:46:06.2 | 00:43:32.2 | |||||
| 259 | 120 | Female | 40-49 | 00:44:09.5 | 00:43:40.1 | |||||
| 260 | 476 | Female | 10-13 | 00:43:58.2 | 00:43:46.4 | |||||
| 261 | 477 | Female | 10-13 | 00:43:59.4 | 00:43:49.3 | |||||
| 262 | 152 | Female | 40-49 | 00:45:38.3 | 00:43:55.5 | |||||
| 263 | 424 | Female | 10-13 | 00:43:59.0 | 00:43:59.0 | |||||
| 264 | 426 | Male | 7 – 9 Years old | 00:44:00.0 | 00:44:00.0 | |||||
| 265 | 260 | Male | 10-13 | 00:45:31.2 | 00:44:29.3 | |||||
| 266 | 132 | Male | 7 – 9 Years old | 00:45:37.5 | 00:44:36.9 | |||||
| 267 | 384 | Male | 40-49 | 00:46:27.0 | 00:44:39.1 | |||||
| 268 | 122 | Female | 50-59 | 00:46:27.0 | 00:44:39.3 | |||||
| 269 | 202 | Female | 14-18 | 00:53:00.5 | 00:45:19.8 | |||||
| 270 | 160 | Male | 40-49 | 00:46:15.3 | 00:45:23.1 | |||||
| 271 | 256 | Female | 40-49 | 00:46:15.1 | 00:45:23.3 | |||||
| 272 | 483 | Female | 7 – 9 Years old | 00:48:03.7 | 00:45:36.8 | |||||
| 273 | 159 | Male | 7 – 9 Years old | 00:46:28.0 | 00:45:37.1 | |||||
| 274 | 480 | Female | 40-49 | 00:48:03.4 | 00:45:37.2 | |||||
| 275 | 201 | Female | 40-49 | 00:53:25.7 | 00:45:45.1 | |||||
| 276 | 359 | Female | 60-99 | 00:48:45.0 | 00:46:07.9 | |||||
| 277 | 341 | Male | UK | 00:49:18.7 | 00:46:59.4 | |||||
| 278 | 408 | Female | 14-18 | 00:48:56.0 | 00:47:04.3 | |||||
| 279 | 409 | Male | 40-49 | 00:48:56.2 | 00:47:04.5 | |||||
| 280 | 438 | Female | 14-18 | 00:50:54.3 | 00:48:26.9 | |||||
| 281 | 439 | Female | 14-18 | 00:50:57.2 | 00:48:31.6 | |||||
| 282 | 322 | Male | 50-59 | 00:52:52.1 | 00:50:06.2 | |||||
| 283 | 440 | Female | 30-39 | 00:55:37.7 | 00:52:59.9 | |||||
| 284 | 142 | Male | 40-49 | 00:56:00.4 | 00:53:28.5 | |||||
| 285 | 333 | Male | 40-49 | 00:55:44.0 | 00:54:48.4 | |||||
| 286 | 169 | Female | 7 – 9 Years old | 00:55:44.4 | 00:54:48.8 | |||||
| 287 | 332 | Female | 30-39 | 00:55:49.3 | 00:54:54.2 | |||||
| 288 | 288 | Female | 60-99 | 00:57:43.3 | 00:56:50.2 | |||||
| 289 | 109 | Female | 40-49 | 00:59:34.2 | 00:58:03.1 | |||||
| 290 | 290 | Female | 19-29 | 01:00:35.5 | 00:58:49.1 | |||||
| 291 | 291 | Female | 50-59 | 01:00:38.4 | 00:58:51.6 | |||||
| 292 | 289 | Male | 19-29 | 01:00:40.6 | 00:58:53.0 | |||||
| 293 | 293 | Mixed | UK | 00:59:30.6 | 00:59:07.6 | |||||
| 294 | 207 | Male | 40-49 | 01:02:01.6 | 00:59:12.0 | |||||
| 295 | 294 | Female | 7 – 9 Years old | 00:59:31.5 | 00:59:31.5 | |||||
| 296 | 206 | Female | 60-99 | 01:07:02.3 | 01:00:57.3 | |||||
| 297 | 403 | Female | 40-49 | 01:03:12.6 | 01:00:59.7 | |||||
| 298 | 193 | Male | 30-39 | 01:06:25.0 | 01:01:59.6 | |||||
| 299 | 304 | Male | 14-18 | 01:07:24.4 | 01:03:43.4 | |||||
| 300 | 411 | Female | 30-39 | 01:08:11.7 | 01:04:25.1 | |||||
| 301 | 412 | Female | 60-99 | 01:08:14.2 | 01:04:27.7 | |||||
| 302 | 410 | Female | 19-29 | 01:08:14.0 | 01:04:29.9 | |||||
| – | 128 | Male | 10-13 | Started | Started |
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