It’s harder to run in hotter weather, something that is easy to forget when toeing the line at a marathon. If you’ve set goals based on cool weather training or performance without taking the heat into account, you will go out too fast and your overall time will suffer. But how much does your performance change with temperature? I found a study<ref name="study"/> that gives some answers.
==The Answer, Part 1==The study showed how finish time changes with temperature. The , and the results are shown in the following graph.
http://jfsavage.smugmug.com/photos/817939120_uZxSb-X3.jpg
To explain how this This graph workswell for runners finishing the race at 3 hour pace or faster, let’s use a couple but that excludes the majority of examplesmarathon runners. You’ll need How can we extend this to slower runners? ==The Answer(s), Part 2==I’ve taken two approaches to know extending the heat index//feels like temperature graph, as you can see below. The first approach is to assume that you expect the decline in performance is linear with a zero origin, as shown by the red line. The second approach is to assume the decline is linear from the two noted end points, as shown by the other colored lines. This will give us two projections of performance decline and I’ve created tables at the raceend of this page based on these assumptions. ==Your Mileage May Vary==There are a lot of flaws in this approach, which you should be aware of. * This study uses only sub-3 hour marathon runners, and your projected cool weather their performancecharacteristics could be quite different to slower runners. * Runner A There is expecting to run a 2:40 marathon wide individual variation in cool conditionsperformance decline due to temperature. The level of heat adaptation the runner had, but the race is projecting 60 degreesbody size and shape, etc all play into this. * The 15C/59C line at lines in the 160 minute mark indicates graphs above are clearly not linear, so making this type of assumption is overly simplistic and probably excessively conservative. * Extrapolating information is a 3% drop in performanceflawed approach, so as there is no way of knowing what the corrected time actual data would be nearly 5 minutes slowerlook like. * Runner B ==Usability of the data==Given all these problems, is this approach usable or useful? I think there is expecting to some use, as long as you understand the limitations. If the charts below say you can run a 34:30 48 marathon in based on your cool conditionsweather performance and the projected temperature, but the race this does not mean you can run a 4:48 in practice. What it does provide is projecting 70 degrees. The graph only goes a sense of just how much you will need to 3 hoursslow down on a hot day, so we and how important weather is in your results. Hopefully this information will assume cause you to reset your goals and promote a liner progression, which flexible approach on race day. ==Marathon Selection==One key note from this analysis is likely that weather will play a huge role in your results. If you are seeking a race to be too conservativeachieve a specific time goal, such as Boston Qualification, but will give us an ideachoosing a race that has a high probability of cool or cold weather becomes important. You are probably better off with a hillier course than warm weather for instance. At ==Zero Origin Table=={| {{table}}| align="center" style="background:#f0f0f0;"|'''40f'''| align="center" style="background:#f0f0f0;"|'''50f'''| align="center" style="background:#f0f0f0;"|'''60f'''| align="center" style="background:#f0f0f0;"|'''70f'''| align="center" style="background:#f0f0f0;"|'''80f'''|-| 3:00:00||3:05:24 (3%)||3:10:48 (6%)||3:16:12 (9%)||3:21:36 (12%)|-| 3:05:00||3:10:42 (3%)||3 hours, the 20C/68C line is :16:25 (6%)||3:22:07 (9 percent. If we scale by %)||3:27:49 (12%)|-| 3:10:00||3:16:01 (3%)||3:22:02 (6%)||3:28:03 (10%)||3:34:04 (13%)|-| 3:15:00||3:21:20 (3%)||3:27:40 (7%)||3:34:01 (10%)||3:40:21 (13%)|-| 3:20:00||3:26:40 (3%)||3:33:20 (7%)||3:40:00 (10%)||3:46:40 (13%)|-| 3:25:00||3:32:00 (3%)||3:39:00 (7%)||3:46:01 (10%)||3:53:01 (14%)|-| 3:30:00||3:37:21 (4%)||3:44:42 (7%)||3:52:03 (11%)||3:59:24 (14%)|-| 3:35:00||3:42:42 (4%)||3:50:25 (7%)||3:58:07 (11%)||4:05:49 (14%)|-| 3:40:00||3:48:04 (4%)||3:56:08 (7%)||4:04:12 (11%)||4:12:16 (15%)|-| 3:45:00||3:53:26 (4%)||4:01:52 (8%)||4:10:19 (11%)||4/:18:45 (15%)|-| 3:50:00||3, that gives :58:49 (4%)||4:07:38 (8%)||4:16:27 (12%. On )||4:25:16 (15%)|-| 3:55:00||4:04:12 (4%)||4:13:24 (8%)||4:22:37 (12%)||4:31:49 (16%)|-| 4:00:00||4:09:36 (4%)||4:19:12 (8%)||4:28:48 (12%)||4:38:24 (16%)|-| 4:05:00||4:15:00 (4%)||4:25:00 (8%)||4:35:01 (12%)||4:45:01 (16%)|-| 4:10:00||4:20:25 (4%)||4:30 :50 (8%)||4:41:15 (13%)||4:51:40 (17%)|-| 4:15:00||4:25:50 (4%)||4:36:40 (9%)||4:47:31 (13%)||4:58:21 (17%)|-| 4:20:00||4:31:16 (210 minutes4%), ||4:42:32 (9%)||4:53:48 (13%)||5:05:04 (17%)|-| 4:25:00||4:36:42 (4%)||4:48:24 (9%)||5:00:07 (13%)||5:11:49 (18%)|-| 4:30:00||4:42:09 (5%)||4:54:18 (9%)||5:06:27 (14%)||5:18:36 (18%)|-| 4:35:00||4:47:36 (5%)||5:00:12 (9%)||5:12:49 (14%)||5:25:25 (18%)|-| 4:40:00||4:53:04 (5%)||5:06:08 (9%)||5:19:12 (14%)||5:32:16 (19%)|-| 4:45:00||4:58:32 (5%)||5:12:04 (10%)||5:25:37 (14%)||5:39:09 (19%)|-| 4:50:00||5:04:01 (5%)||5:18:02 (10%)||5:32:03 (15% gives a corrected time of 3)||5:46:04 (19%)|-| 4:55, a slowdown of :00||5:09:30 (5%)||5:24:00 (10%)||5:38:31 (15%)||5:53:01 (20%)|-| 5:00:00||5:15:00 (5%)||5:30:00 (10%)||5:45:00 (15%)||6:00:00 (20%)|-| 5:05:00||5:20:30 (5%)||5:36:00 (10%)||5:51:31 (15%)||6:07:01 (20%)|-| 5:10:00||5:26:01 (5%)||5:42:02 (10%)||5:58:03 (16%)||6:14:04 (21%)|-| 5:15:00||5:31:32 (5%)||5:48:04 (11%)||6:04:37 (16%)||6:21:09 (21%)|-| 5:20:00||5:37:04 (5%)||5:54:08 (11%)||6:11:12 (16%)||6:28:16 (21%)|-| 5:25:00||5:42:36 (5%)||6:00:12 (11%)||6:17:49 (16%)||6:35:25 (22%)|-| 5:30:00||5:48:09 (6%)||6:06:18 (11%)||6:24:27 (17%)||6:42:36 (22%)|-| 5:35:00||5:53:42 (6%)||6:12:24 (11%)||6:31:07 (17%)||6:49:49 (22%)|-| 5:40:00||5:59:16 (6%)||6:18:32 (11%)||6:37:48 (17%)||6:57:04 (23%)|-| 5:45:00||6:04:50 (6%)||6:24:40 (12%)||6:44:31 (17%)||7:04:21 (23%)|-| 5:50:00||6:10:25 minutes. (6%)||6:30:50 (12%)||6:51:15 (18%)||7:11:40 (23%)|-| 5:55:00||6:16:00 (6%)||6:37:00 (12%)||6:58:01 (18%)||7:19:01 (24%)|-| 6:00:00||6:21:36 (6%)||6:43:12 (12%)||7:04:48 (18%)||7:26:24 (24%)|}
==110 Offset Table==
{| {{table}}
| align="center" style="background:#f0f0f0;"|'''40f'''
| align="center" style="background:#f0f0f0;"|'''50f'''
| align="center" style="background:#f0f0f0;"|'''60f'''
| align="center" style="background:#f0f0f0;"|'''70f'''
| align="center" style="background:#f0f0f0;"|'''80f'''
|-
| 3:00:00||3:05:24 (3%)||3:10:48 (6%)||3:16:12 (9%)||3:21:36 (12%)
|-
| 3:05:00||3:10:42 (3%)||3:16:25 (6%)||3:22:07 (10%)||3:27:49 (13%)
|-
| 3:10:00||3:16:01 (3%)||3:22:02 (7%)||3:28:03 (10%)||3:34:04 (14%)
|-
| 3:15:00||3:21:20 (4%)||3:27:40 (7%)||3:34:01 (11%)||3:40:21 (15%)
|-
| 3:20:00||3:26:40 (4%)||3:33:20 (8%)||3:40:00 (12%)||3:46:40 (15%)
|-
| 3:25:00||3:32:00 (4%)||3:39:00 (8%)||3:46:01 (12%)||3:53:01 (16%)
|-
| 3:30:00||3:37:21 (4%)||3:44:42 (9%)||3:52:03 (13%)||3:59:24 (17%)
|-
| 3:35:00||3:42:42 (5%)||3:50:25 (9%)||3:58:07 (14%)||4:05:49 (18%)
|-
| 3:40:00||3:48:04 (5%)||3:56:08 (9%)||4:04:12 (14%)||4:12:16 (19%)
|-
| 3:45:00||3:53:26 (5%)||4:01:52 (10%)||4:10:19 (15%)||4:18:45 (20%)
|-
| 3:50:00||3:58:49 (5%)||4:07:38 (10%)||4:16:27 (15%)||4:25:16 (21%)
|-
| 3:55:00||4:04:12 (5%)||4:13:24 (11%)||4:22:37 (16%)||4:31:49 (21%)
|-
| 4:00:00||4:09:36 (6%)||4:19:12 (11%)||4:28:48 (17%)||4:38:24 (22%)
|-
| 4:05:00||4:15:00 (6%)||4:25:00 (12%)||4:35:01 (17%)||4:45:01 (23%)
|-
| 4:10:00||4:20:25 (6%)||4:30:50 (12%)||4:41:15 (18%)||4:51:40 (24%)
|-
| 4:15:00||4:25:50 (6%)||4:36:40 (12%)||4:47:31 (19%)||4:58:21 (25%)
|-
| 4:20:00||4:31:16 (6%)||4:42:32 (13%)||4:53:48 (19%)||5:05:04 (26%)
|-
| 4:25:00||4:36:42 (7%)||4:48:24 (13%)||5:00:07 (20%)||5:11:49 (27%)
|-
| 4:30:00||4:42:09 (7%)||4:54:18 (14%)||5:06:27 (21%)||5:18:36 (27%)
|-
| 4:35:00||4:47:36 (7%)||5:00:12 (14%)||5:12:49 (21%)||5:25:25 (28%)
|-
| 4:40:00||4:53:04 (7%)||5:06:08 (15%)||5:19:12 (22%)||5:32:16 (29%)
|-
| 4:45:00||4:58:32 (8%)||5:12:04 (15%)||5:25:37 (23%)||5:39:09 (30%)
|-
| 4:50:00||5:04:01 (8%)||5:18:02 (15%)||5:32:03 (23%)||5:46:04 (31%)
|-
| 4:55:00||5:09:30 (8%)||5:24:00 (16%)||5:38:31 (24%)||5:53:01 (32%)
|-
| 5:00:00||5:15:00 (8%)||5:30:00 (16%)||5:45:00 (24%)||6:00:00 (33%)
|-
| 5:05:00||5:20:30 (8%)||5:36:00 (17%)||5:51:31 (25%)||6:07:01 (33%)
|-
| 5:10:00||5:26:01 (9%)||5:42:02 (17%)||5:58:03 (26%)||6:14:04 (34%)
|-
| 5:15:00||5:31:32 (9%)||5:48:04 (18%)||6:04:37 (26%)||6:21:09 (35%)
|-
| 5:20:00||5:37:04 (9%)||5:54:08 (18%)||6:11:12 (27%)||6:28:16 (36%)
|-
| 5:25:00||5:42:36 (9%)||6:00:12 (18%)||6:17:49 (28%)||6:35:25 (37%)
|-
| 5:30:00||5:48:09 (9%)||6:06:18 (19%)||6:24:27 (28%)||6:42:36 (38%)
|-
| 5:35:00||5:53:42 (10%)||6:12:24 (19%)||6:31:07 (29%)||6:49:49 (39%)
|-
| 5:40:00||5:59:16 (10%)||6:18:32 (20%)||6:37:48 (30%)||6:57:04 (39%)
|-
| 5:45:00||6:04:50 (10%)||6:24:40 (20%)||6:44:31 (30%)||7:04:21 (40%)
|-
| 5:50:00||6:10:25 (10%)||6:30:50 (21%)||6:51:15 (31%)||7:11:40 (41%)
|-
| 5:55:00||6:16:00 (11%)||6:37:00 (21%)||6:58:01 (32%)||7:19:01 (42%)
|-
| 6:00:00||6:21:36 (11%)||6:43:12 (21%)||7:04:48 (32%)||7:26:24 (43%)
|}
==The Details==
The study looked at 140 marathon results from 6 races (Boston, New York, Twin Cities, Grandma's, Richmond, Hartford, and Vancouver). Only the first 300 finish times were used as races only started recording all finishers in the 1990s. This gives a pool of 42,000 finish times. The races were divided up into four groups
