In the Introduction I detailed how, in his Running Formula book, Jack Daniels states that his survey of runners at the 1984 LA Olympics found everyone in events over 3000m had a cadence of 180 or greater – with one exception.

In this post, I’m looking at the 10000m and marathon races from the 2017 World Championships and finding more anomalies than Jack discovered. To read about the cadences of Sprinters and Middle-Distance runners – click the links.

Men’s 10,000m

The race was won by Great Britain’s Mo Farah in 26:49.51s with Uganda’s Joshua Cheptegui and Kenya’s Paul Tanui finishing less than a second behind him. Twenty-two runners had started the 25-lap race and while the early going was slow the race eventually settled down to running laps at around 4:15-30/mile pace. Gradually runners were dropped from the lead pack and at the bell Farah was leading a group of six;  it was here that he kicked and covered the final lap in under 56 seconds.

The technical report on the race covers the first eight finishers and provides their data in the home straight on the 15th lap. We are given the Step Rate when the race has settled down and the runners are running at around 4:30/mile.

	Step Rate (Hz)	Cadence (SPM)
Farah	2.89	173
Cheptegui	3.04	182
Tanui	3.07	184
Muchiri	3.44	206
Yimer	3.23	194
Kamworor	3.09	185
Hadis	3.07	184
Ahmed	2.85	171
Average	3.09	185

I’ve done the conversion from Step Rate to cadence and we can see there is a huge range from 171 up to 206spm. Mo Farah is just a couple of steps higher at 173 than Canada’s Mohammed Ahmed (171). It’s clear a sub-180 cadence was no hindrance to Farah because he won the gold and Ahmed finished 8^th in 27min02 only fifteen seconds behind.

Many of the athletes are running at Jack Daniels’ predicted 180 cadence with Kenya’s Jemal Yimer (194) and Ethiopia’s Bedan Muchiri (206) being the notable exceptions. While the focus of these posts has been to ignore stride length; I think it is useful to recognise Muchiri’s is 1.75m here.

The technical report also provides greater detail (table 2) for the three medallists with their cadence from five points in the race including the home straight as they battle for gold at top speed.

What we see is that, for much of the race, Mo Farah is operating at sub-180 cadence while Cheptegui and Tanui are operating at 180-190. It’s when they reach the final lap of the race that they put the afterburners on and here we see all three runners increase their cadence. Mo Farah continues to have the lowest of the three albeit he is achieving a cadence of 200 at this point.

Women’s 10,000m

The women’s race was run differently to the men’s 10000m. While initially both races began slowly with a pack of runners bunched together; it was about twelve minutes into the women’s race on the 9^th lap that eventual winner Almaz Ayana took charge.

While the 8^th lap had been completed in 1:15 (5min/mile) she now moved to the front and upped the pace with the next two laps coming in 1:08 and 1:07 (4:35-40/mile). Gradually she pulled away from the the rest of the field, lapping back markers and went on to win gold finishing almost a minute ahead of the other medallists. There was a tussle between Tirunesh Dibaba (silver) and Agnes Tirop (bronze) over the last lap with Alice Nanowuna following in fifty metres behind them.

The cadence data (table 3) is a little more conventional for the women with all the runners between 180-192 yet there is one exception – Kenya’s Alice Nawowuna who is down at 173. The race commentators mention Nawowuna is the tallest of the three Kenyans which could explain a longer stride.

	Step Rate (Hz)	Cadence (SPM)
Ayana	3.14	188
Dibaba	3.17	190
Tirop	3.20	192
Nawowuna	2.88	173
Krumins	3.07	184
Infeld	3.02	181
Cheptai	3.07	184
Huddle	3.17	190
Average	3.09	185

As with the men’s data, the sample is from midrace approaching 6000m where they are running at about 4:50-55/mile with the exception of leader Ayana who is at 4:35 and Molly Huddle at 5:03.

Below in table 4 we see the race breakdown for the medallists and cadence increases in the final lap on the home straight. Ayana is unchallenged so never has to hit her highest gear. The battle between Dibaba and Tirop is close and we can see their cadences are very different. At this stage of her career, Dibaba had been running marathons for three years and it is notable how smooth her stride is sprinting against Tirop. At 228, Dibaba’s turnover in this finishing straight is as good as, or better, than many middle distance runners while throughout the rest of the race she is above average by hitting the low 190s.

	Lap 5	Lap 10	Lap 15	Lap 20	Lap 25		Lap 5	Lap 10	Lap 15	Lap 20	Lap 25
Ayana	3.06	3.03	3.14	3.03	3.23		184	182	188	182	194
Dibaba	3.09	3.19	3.17	3.23	3.80		185	191	190	194	228
Tirop	3.08	3.09	3.20	3.03	3.26		185	185	192	182	196

Marathon

The 2017 World Championship marathons were held on a four lap street circuit around London with each lap measuring about 10km.  While there were some long straights on the course, it also had a number of corners to be negotiated which either required runners to run wider or adapt their pace. It was a true head-to-head race in the sense of trying to beat other runners rather than going for a time.

The marathon data is possibly the most interesting data in this whole study because we have two sets of data for the men recorded at around 30km and 40km and, with runners tiring in both men’s and women’s races, we get a glimpse of them running at paces we might expect from above average recreational runners.

The men’s race was won by Geoffrey Kirui of Ethiopia in 2:08:27. Table 5 shows his cadence on lap 3 is 191spm where he is recorded running at 4:50/mile. Having taken the lead at 35km and opened up a lead over silver medallist Tamirat Tola, he had slowed by the 40km mark. By this point he was running at 5:25/mile and his cadence had dropped to 186spm.

		Lap3				Lap4
	Step Rate (Hz)	Cadence (SPM)	Pace (per mile)		Step Rate (Hz)	Cadence (SPM)	Pace (per mile)
Kirui	3.19	191	4:50		3.10	186	5:25
Tola	3.05	183	4:58		3.00	180	5:51
Simbu	2.91	175	5:22		2.89	173	5:27
Hawkins	3.12	187	5:21		3.23	194	5:11
Kipketer	2.85	171	5:29		2.86	171	5:42
Meucci	3.14	186	5:29		—	—	—
Ghebregergis	2.96	178	5:37		2.99	179	5:49
Wanjiru	3.20	192	5:26		3.08	185	6:10
Average	3.05	183	5:19		3.02	181	5:39

Of the other six runners who data was recorded for, only Callum Hawkins increased his pace in the last 10km – this was consistent with him moving up in the race from 8^th place to finish 4^th. To run 10secs/mile quicker his cadence increased from 187 to 194.

Meanwhile Tola, who slowed by almost a minute per mile, dropped his cadence from 183 to 180; similarly Wanjiru who slowed to over 6mins/mile had his cadence drop from 192 to 185.  The other three runners see a small drop in pace – Simbu slows by 5secs/mile – a relatively low cadence of 175 drops further to 173; Kipketer’s cadence remains the same as he slows by 13secs/mile and the one anomaly is Ghebregergis who fractionally increases Step Rate while slowing by 12secs/mile. I’d be inclined to see this as remaining the same with the 0.01Hz change attributable to the normal variations which occur while running.

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The women’s marathon was won by Rose Chelimo in 2:27:11 – not a particularly fast time by modern standards – equating to an average pace of 5:37/mile (35min per 10K). But it was closely contested with the top four runners finishing within ten seconds of each other.

Unlike the men’s race, there is only data provided from the 4^th lap – the 40km mark – and at this late stage of the race we see in table 6 a variety of paces from the 5:28/mile of USA’s Amy Cragg who is almost a minute per mile quicker than Kirwa and Dibaba at 6:17 (barely quicker then a 20min 5K parkrun).

		Lap4
	Step Rate (Hz)	Cadence  (SPM)	Pace (per mile)
Chelimo	3.31	199	5:41
Kiplagat	3.07	184	5:41
Cragg	3.29	197	5:28
Daniel	3.09	185	5:37
Demise	2.95	177	5:56
Kirwa	3.10	186	6:17
Kiprop	2.75	165	5:58
Dibaba	2.92	175	6:17
Average	3.06	184	5:51

We see a significant range of cadences despite all eight finishers running 2hr27-28. Gold and bronze medallists, Chelimo and Cragg are hitting the 190s with Kiplagat, Daniel and Kirwa in the mid-180s – all in line with Jack Daniels’ findings.

Yet there are three runners with sub-180 cadences. There are Ethiopia’s Shure Demise and Mare Dibaba (unrelated to Tirunesh) in the mid-170s. And then there is Kenya’s Helah Kiprop running at only 165spm. Finishing seventh, a minute behind Chelimo this was far from her best race which was a Marathon Majors win in Tokyo in a time of 2:21:27. Knowing she can run a marathon around 20secs per mile faster opens up the question of whether she would achieve that pace through a quicker cadence, longer stride rate or a combination of the two. I would expect her to be capable of a quicker cadence as 165 is extremely low compared to all the other runners detailed.

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Collating the data into table 7 for all 32 runners across the four races we see a symmetrical range of cadences where the majority are in the 180s – which aligns with the average cadence data being 183-185spm. But it also highlights that over a quarter of these runners can be running at sub-180 cadences.

	< 170	170s	180s	190s	200+
Cadence (SPM)	1	8	14	8	1

While the variety of paces goes from 4:15/mile in the men’s 10,000m down to 6:15+/mile in the women’s marathon – we should remember these are all world class athletes who are training many hours per week and getting excellent coaching. They are running times many of us will only dream of and among these runners having a sub-180 cadence is not holding them back.

We’ve also glimpsed cadence at slower paces – the marathons have three men running at 5:49, 5:51, 6:10 per mile and four women running at 5:56, 5:58, 6:17, 6:17 – these are the paces for a 18-20min 5K.  The cadences for these seven runners are 179, 180, 185 and 177, 165, 175, 186.

This suggests, but is by no means definite that, as elite runners move towards recreational paces their cadence can be lower than 180. It’s also backed up by how when the men slowed in their race, four of six runners had lower cadences, while Callum Hawkins increased his pace by increasing his cadence as did each of the 10000m medallists.

In the final post in this series I will summarise what the cadence data can tell us about running and what it might mean for you as a recreational runner. Click here to go to it.