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Task 2 (Open)

How the field flew this task, and which behaviours separated it.

JILJIL
The optimised route — radii, leg distances and start times are on the task page.

Analysis computed

Pilots
50
Thermals
20122 shared by 2+ pilots
Working band
3711899 m
Airtime split
  • searching20%
  • climbing39%
  • gliding41%

What the weather did

From the weather model

Independent of the tracklogs: modelled conditions for the task area.

Fetching the day’s weather — it will appear here in a moment.

From the pilots' tracks

What the field actually flew — wind, climb strength and leg timing measured from every pilot's tracklog.

The day’s wind, hour by hour and leg by leg. What the air did, read from the field itself. We estimate the wind from the circling of every pilot. The first method is the drift of the circle centre, and the second method, used when the first is not available, is the modulation of the ground speed. We then combine the estimates two ways. The table by hour of day shows how the wind increased and changed direction through the day. The table by speed-section leg shows the wind on each part of the course. This metric describes the day, so it has no value for each pilot.

How strong the day’s climbs were, hour by hour. When the day started, reached its peak, and ended. We group the thermal climbs of all pilots by the hour in which each climb started, labelled in the time zone of the competition. The median and the 90th-percentile average climb rate for each hour show how the lift developed. This metric describes the day, so it has no value for each pilot.

Share of the flight spent in air that wasn’t sinking. How much of the flight was in air worth being in. The value is the share of the airborne time of a pilot, on the shared grid, with a 30 s-smoothed vario at or above −0.5 m/s. The time they flew, the line they steered and the way the flight ended all feed this value. It is therefore a reading of the day as much as of the pilot. There is no expected direction, and the sign of the correlation is the finding. The timing table compares the window of the day’s best climbs against the time when the field launched.

All charts share that one time axis. Arrows fly WITH the wind — direction figures are degrees the wind blows from.

Which behaviours went with better ranks

Each row is one behaviour, compared against the published ranks. Select a row to plot it against rank.

How round and consistent the circles were

Each dot is a pilot. ρ = -0.80 (too few pilots, n = 4). Less is expected to be better here, but this task ran the other way: top ranks gather to the right. There is no trend curve. Too few pilots have a value to fit one that means anything. 46 pilots have no value and are not plotted, including the #1, #2 and #3 ranked pilots.
  • Turn direction across the field: 0% left (122 circles).
BehaviourStrengthWhat it meansPilots measured
How round and consistent the circles were
too few pilots
Share of race time spent hunting for the next climb
some pattern
Low saves dug out from the bottom of the band
some pattern
Time to core thermals
some pattern
Glide speed between climbs
could be chance
Time spent flying with a gaggle
could be chance
Climbs joined on another pilot's marker
could be chance
Share of the flight spent in air that wasn’t sinking
could be chance
Share of lift turned in that was kept as a climb
could be chance
Climbing faster than the pilots sharing the thermal
could be chance
How low the pilot gets between climbs
could be chance
Climb rate at thermal exit
could be chance
How much of the thermal the pilot climbed before leaving it
could be chance
Gliding faster when the next climb is stronger
could be chance

1 behaviour was measured on fewer than 8 pilots — too few to tell either way.

The whole field at a glance

1. James Abbott
2. Hugo Armstrong
3. Sarah Baker
4. Poppy Boyle
5. Finn Carter
6. Liam Chen
7. Olivia Dixon
8. Scarlett Doyle
9. Archie Ellison
10. Noah Evans
11. Freya Foster
12. Emma Fraser
13. George Gibson
14. Jack Grant
15. Willow Harding
16. Ava Hughes
17. Harry Ingram
18. William Irwin
19. Evie Jarvis
20. Mia Jensen
21. Ethan Kelly
22. Oscar Knight
23. Matilda Larsen
24. Grace Lowe
25. Jasper Mercer
26. Lucas Murphy
27. Harper Newton
28. Chloe Nolan
29. Henry OConnor
30. Toby Osborne
31. Georgia Palmer
32. Zoe Patel
33. Oliver Quinn
34. Angus Rankin
35. Ruby Reid
36. Thomas Singh
37. Maya Sutton
38. Fergus Tobin
39. Isla Turner
40. Alice Underhill
41. Charlie Underwood
42. Ella Vaughan
43. Rory Voss
44. Max Walker
45. Hazel Whelan
46. Lily Xu
47. Cody Yates
48. Leo Young
49. Amelia Zammit
50. Frankie Zeller
The pilots in rank order against every behaviour. A darker cell is a better percentile in this field, and an empty cell is a behaviour that does not apply.

Pilot style clusters

The groups are flying style, and not score. The spread of ranks in each group shows where that style paid and where it did not.

Group AUnfussy climbers

19 pilots · ranks 249 · median 27 · middle half 20.534.5

  • HighShare of lift turned in that was kept as a climb group median P77 in this field (82 percent)
  • LowTime to core thermals group median P24 in this field (60 seconds) · usually a strength
  • LowHow low the pilot gets between climbs group median P24 in this field (8 percent)
  • HighShare of the flight spent in air that wasn’t sinking group median P76 in this field (40 percent)
  • 2. Hugo Armstrong
  • 11. Freya Foster
  • 15. Willow Harding
  • 17. Harry Ingram
  • 20. Mia Jensen
  • 21. Ethan Kelly
  • 23. Matilda Larsen
  • 25. Jasper Mercer
  • 26. Lucas Murphy
  • 27. Harper Newton
  • 28. Chloe Nolan
  • 30. Toby Osborne
  • 31. Georgia Palmer
  • 33. Oliver Quinn
  • 36. Thomas Singh (most typical of this group)
  • 39. Isla Turner
  • 46. Lily Xu
  • 47. Cody Yates
  • 49. Amelia Zammit

Group BSlow corers

25 pilots · ranks 450 · median 32 · middle half 1641

  • HighTime to core thermals group median P76 in this field (80 seconds) · usually costly
  • HighClimbing faster than the pilots sharing the thermal group median P72 in this field (78 percent) · usually a strength
  • HighHow low the pilot gets between climbs group median P70 in this field (12 percent)
  • LowShare of lift turned in that was kept as a climb group median P31 in this field (67 percent)
  • 4. Poppy Boyle
  • 5. Finn Carter
  • 8. Scarlett Doyle
  • 9. Archie Ellison
  • 13. George Gibson
  • 14. Jack Grant
  • 16. Ava Hughes
  • 18. William Irwin
  • 19. Evie Jarvis (most typical of this group)
  • 22. Oscar Knight
  • 24. Grace Lowe
  • 29. Henry OConnor
  • 32. Zoe Patel
  • 34. Angus Rankin
  • 35. Ruby Reid
  • 37. Maya Sutton
  • 38. Fergus Tobin
  • 40. Alice Underhill
  • 41. Charlie Underwood
  • 42. Ella Vaughan
  • 43. Rory Voss
  • 44. Max Walker
  • 45. Hazel Whelan
  • 48. Leo Young
  • 50. Frankie Zeller

Not clustered: 1. James Abbott — only 1 of 14 metrics available (needs ≥ 60%); 3. Sarah Baker — only 1 of 14 metrics available (needs ≥ 60%); 6. Liam Chen — only 2 of 14 metrics available (needs ≥ 60%); 7. Olivia Dixon — only 7 of 14 metrics available (needs ≥ 60%); 10. Noah Evans — only 7 of 14 metrics available (needs ≥ 60%); 12. Emma Fraser — only 7 of 14 metrics available (needs ≥ 60%).

44 pilots on 14 behavioural metrics formed 2 groups.

The metrics in detail

best: could be chance (0.16)

best: too few pilots (0.80)

#PilotOut-climbCore sLeaveRateKept%TopOut%Round
1James Abbott
2Hugo Armstrong0 (3 shared climbs)60 (6 climbs ≥ 60 s)-1.1 (6 climbs ≥ 90 s)50 (7/14 circling bouts led to climbs)78 (mean on-course altitude 36% of band)
3Sarah Baker
4Poppy Boyle54 (1 shared climb)80 (6 climbs ≥ 60 s)-0.8 (6 climbs ≥ 90 s)61 (28/46 circling bouts led to climbs)96 (mean on-course altitude 47% of band) (8 circles, 0% left)
5Finn Carter39 (2 shared climbs)80 (6 climbs ≥ 60 s)-0.9 (6 climbs ≥ 90 s)33 (6/18 circling bouts led to climbs)74 (mean on-course altitude 40% of band) (4 circles, 0% left)
6Liam Chen
7Olivia Dixon52 (1 shared climb)10 (1 climb ≥ 60 s)-1.1 (1 climb ≥ 90 s)
8Scarlett Doyle90 (2 shared climbs)80 (6 climbs ≥ 60 s)-1.4 (6 climbs ≥ 90 s)33 (5/15 circling bouts led to climbs)100 (mean on-course altitude 48% of band) (1 circles, 0% left)
9Archie Ellison88 (2 shared climbs)80 (6 climbs ≥ 60 s)-1.3 (6 climbs ≥ 90 s)80 (8/10 circling bouts led to climbs)58 (mean on-course altitude 38% of band)
10Noah Evans22 (1 shared climb)10 (1 climb ≥ 60 s)-1.1 (1 climb ≥ 90 s) (2 circles, 0% left)
11Freya Foster34 (3 shared climbs)70 (7 climbs ≥ 60 s)-1.3 (7 climbs ≥ 90 s)86 (31/36 circling bouts led to climbs)63 (mean on-course altitude 36% of band)
12Emma Fraser83 (1 shared climb)10 (1 climb ≥ 60 s)-1.2 (1 climb ≥ 90 s)
13George Gibson83 (2 shared climbs)80 (7 climbs ≥ 60 s)-1.3 (7 climbs ≥ 90 s)46 (6/13 circling bouts led to climbs)62 (mean on-course altitude 37% of band)
14Jack Grant58 (2 shared climbs)45 (2 climbs ≥ 60 s)-1.4 (2 climbs ≥ 90 s)86 (6/7 circling bouts led to climbs)75 (mean on-course altitude 33% of band)
15Willow Harding0 (2 shared climbs)60 (7 climbs ≥ 60 s)-1.0 (7 climbs ≥ 90 s)83 (34/41 circling bouts led to climbs)64 (mean on-course altitude 35% of band)
16Ava Hughes85 (1 shared climb)45 (2 climbs ≥ 60 s)-1.0 (2 climbs ≥ 90 s)71 (5/7 circling bouts led to climbs)76 (mean on-course altitude 34% of band)
17Harry Ingram56 (2 shared climbs)70 (7 climbs ≥ 60 s)-1.0 (7 climbs ≥ 90 s)29 (6/21 circling bouts led to climbs)83 (mean on-course altitude 45% of band) (2 circles, 0% left)
18William Irwin98 (1 shared climb)80 (3 climbs ≥ 60 s)-1.2 (3 climbs ≥ 90 s)73 (8/11 circling bouts led to climbs)64 (mean on-course altitude 33% of band)
19Evie Jarvis78 (1 shared climb)80 (8 climbs ≥ 60 s)-1.1 (8 climbs ≥ 90 s)38 (10/26 circling bouts led to climbs)76 (mean on-course altitude 45% of band)0.19 (10 circles, 0% left)
20Mia Jensen10 (2 shared climbs)40 (2 climbs ≥ 60 s)-1.0 (2 climbs ≥ 90 s)100 (8/8 circling bouts led to climbs)91 (mean on-course altitude 39% of band)
21Ethan Kelly44 (2 shared climbs)45 (2 climbs ≥ 60 s)-1.0 (2 climbs ≥ 90 s)104 (mean on-course altitude 44% of band) (1 circles, 0% left)
22Oscar Knight17 (1 shared climb)60 (8 climbs ≥ 60 s)-1.2 (8 climbs ≥ 90 s)38 (9/24 circling bouts led to climbs)94 (mean on-course altitude 49% of band)0.20 (30 circles, 0% left)
23Matilda Larsen52 (2 shared climbs)70 (8 climbs ≥ 60 s)-1.0 (8 climbs ≥ 90 s)78 (53/68 circling bouts led to climbs)75 (mean on-course altitude 43% of band)
24Grace Lowe67 (1 shared climb)80 (3 climbs ≥ 60 s)-1.0 (3 climbs ≥ 90 s)50 (2/4 circling bouts led to climbs)79 (mean on-course altitude 40% of band)
25Jasper Mercer18 (2 shared climbs)70 (8 climbs ≥ 60 s)-1.3 (8 climbs ≥ 90 s)85 (57/67 circling bouts led to climbs)95 (mean on-course altitude 47% of band) (1 circles, 0% left)
26Lucas Murphy26 (1 shared climb)60 (3 climbs ≥ 60 s)-1.3 (3 climbs ≥ 90 s)90 (18/20 circling bouts led to climbs)79 (mean on-course altitude 42% of band) (1 circles, 0% left)
27Harper Newton37 (4 shared climbs)70 (8 climbs ≥ 60 s)-1.0 (8 climbs ≥ 90 s)88 (56/64 circling bouts led to climbs)79 (mean on-course altitude 43% of band) (9 circles, 0% left)
28Chloe Nolan6 (2 shared climbs)60 (4 climbs ≥ 60 s)-1.1 (4 climbs ≥ 90 s)87 (39/45 circling bouts led to climbs)107 (mean on-course altitude 52% of band)
29Henry OConnor21 (2 shared climbs)70 (4 climbs ≥ 60 s)-1.4 (4 climbs ≥ 90 s)67 (4/6 circling bouts led to climbs)62 (mean on-course altitude 37% of band) (4 circles, 0% left)
30Toby Osborne48 (3 shared climbs)60 (8 climbs ≥ 60 s)-0.9 (8 climbs ≥ 90 s)68 (32/47 circling bouts led to climbs)74 (mean on-course altitude 39% of band)
31Georgia Palmer6 (4 shared climbs)70 (9 climbs ≥ 60 s)-1.0 (9 climbs ≥ 90 s)85 (61/72 circling bouts led to climbs)91 (mean on-course altitude 47% of band)
32Zoe Patel83 (2 shared climbs)80 (3 climbs ≥ 60 s)-1.3 (3 climbs ≥ 90 s)67 (2/3 circling bouts led to climbs)74 (mean on-course altitude 37% of band)
33Oliver Quinn46 (1 shared climb)70 (4 climbs ≥ 60 s)-1.2 (4 climbs ≥ 90 s)81 (22/27 circling bouts led to climbs)89 (mean on-course altitude 40% of band)
34Angus Rankin100 (4 shared climbs)90 (9 climbs ≥ 60 s)-1.1 (9 climbs ≥ 90 s)67 (20/30 circling bouts led to climbs)67 (mean on-course altitude 42% of band)
35Ruby Reid93 (1 shared climb)90 (4 climbs ≥ 60 s)-1.0 (4 climbs ≥ 90 s)74 (14/19 circling bouts led to climbs)86 (mean on-course altitude 40% of band)
36Thomas Singh6 (2 shared climbs)60 (4 climbs ≥ 60 s)-1.0 (4 climbs ≥ 90 s)79 (27/34 circling bouts led to climbs)83 (mean on-course altitude 40% of band)
37Maya Sutton77 (3 shared climbs)80 (9 climbs ≥ 60 s)-1.2 (9 climbs ≥ 90 s)77 (20/26 circling bouts led to climbs)80 (mean on-course altitude 44% of band)0.17 (24 circles, 0% left)
38Fergus Tobin87 (2 shared climbs)80 (9 climbs ≥ 60 s)-0.9 (9 climbs ≥ 90 s)80 (44/55 circling bouts led to climbs)93 (mean on-course altitude 45% of band)
39Isla Turner3 (2 shared climbs)60 (5 climbs ≥ 60 s)-1.2 (5 climbs ≥ 90 s)80 (53/66 circling bouts led to climbs)107 (mean on-course altitude 52% of band) (2 circles, 0% left)
40Alice Underhill98 (3 shared climbs)80 (10 climbs ≥ 60 s)-1.2 (10 climbs ≥ 90 s)76 (42/55 circling bouts led to climbs)75 (mean on-course altitude 43% of band) (1 circles, 0% left)
41Charlie Underwood57 (3 shared climbs)80 (5 climbs ≥ 60 s)-0.9 (5 climbs ≥ 90 s)52 (14/27 circling bouts led to climbs)81 (mean on-course altitude 42% of band)0.13 (14 circles, 0% left)
42Ella Vaughan39 (1 shared climb)70 (5 climbs ≥ 60 s)-1.2 (5 climbs ≥ 90 s)73 (30/41 circling bouts led to climbs)76 (mean on-course altitude 47% of band)
43Rory Voss74 (1 shared climb)80 (11 climbs ≥ 60 s)-1.0 (11 climbs ≥ 90 s)77 (65/84 circling bouts led to climbs)86 (mean on-course altitude 49% of band) (2 circles, 0% left)
44Max Walker66 (2 shared climbs)70 (5 climbs ≥ 60 s)-1.3 (5 climbs ≥ 90 s)56 (5/9 circling bouts led to climbs)59 (mean on-course altitude 36% of band) (1 circles, 0% left)
45Hazel Whelan97 (4 shared climbs)80 (11 climbs ≥ 60 s)-1.4 (11 climbs ≥ 90 s)59 (23/39 circling bouts led to climbs)68 (mean on-course altitude 38% of band) (1 circles, 0% left)
46Lily Xu27 (4 shared climbs)60 (5 climbs ≥ 60 s)-1.1 (5 climbs ≥ 90 s)90 (43/48 circling bouts led to climbs)82 (mean on-course altitude 43% of band) (1 circles, 0% left)
47Cody Yates23 (2 shared climbs)70 (11 climbs ≥ 60 s)-0.9 (11 climbs ≥ 90 s)70 (57/82 circling bouts led to climbs)88 (mean on-course altitude 44% of band)
48Leo Young61 (1 shared climb)90 (5 climbs ≥ 60 s)-1.1 (5 climbs ≥ 90 s)69 (18/26 circling bouts led to climbs)71 (mean on-course altitude 37% of band) (1 circles, 0% left)
49Amelia Zammit19 (2 shared climbs)70 (5 climbs ≥ 60 s)-0.9 (5 climbs ≥ 90 s)71 (25/35 circling bouts led to climbs)54 (mean on-course altitude 37% of band) (2 circles, 0% left)
50Frankie Zeller95 (2 shared climbs)90 (11 climbs ≥ 60 s)-1.2 (11 climbs ≥ 90 s)74 (35/47 circling bouts led to climbs)70 (mean on-course altitude 39% of band)

Share of lift turned in that was kept as a climb

Measured in percent · no expected direction

How selective the pilot is about the lift they stop for. Each period of circling of 30 s or more after the start counts as lift that the pilot sampled. If the period overlaps a detected thermal, the pilot kept that lift. If it does not, they turned a few circles and left it. The value is the percentage kept. A low value means they are selective. A high value means they keep almost every climb they turn in. There is no expected direction: selection wins on a strong day and wastes time on a weak one.

Acceptance by hour

HourMedian accepted (%)pilots
7143
7538
8031
7018
809
792
1001

Median per-pilot acceptance %, bucketed by the hour (competition time zone).

How round and consistent the circles were

Measured in ratio · lower is better

Whether the pilot flies clean, repeatable circles, or moves around the thermal. We fit each detected circle by least squares. The RMS fit error divided by the fitted radius measures how round the turn was. The value is the median over all of the circles of the pilot. A lower value means smoother and more consistent turns.

Turn direction across the field: 0% left (122 circles).

best: could be chance (0.20)

best: some pattern (0.38)

#PilotFloor%LowSavesSearch%
1James Abbott
2Hugo Armstrong5 (4 descents, lowest 5% of band)5.0 (deepest save from 5% of band)26
3Sarah Baker
4Poppy Boyle11 (4 descents, lowest 10% of band)5.0 (deepest save from 10% of band)24
5Finn Carter14 (4 descents, lowest 14% of band)5.0 (deepest save from 14% of band)20
6Liam Chen0.0
7Olivia Dixon0.00
8Scarlett Doyle13 (4 descents, lowest 13% of band)5.0 (deepest save from 13% of band)26
9Archie Ellison10 (4 descents, lowest 9% of band)5.0 (deepest save from 9% of band)4
10Noah Evans0.00
11Freya Foster12 (5 descents, lowest 12% of band)6.0 (deepest save from 12% of band)19
12Emma Fraser0.00
13George Gibson14 (5 descents, lowest 13% of band)6.0 (deepest save from 13% of band)14
14Jack Grant1.0 (deepest save from 13% of band)20
15Willow Harding8 (5 descents, lowest 8% of band)6.0 (deepest save from 8% of band)21
16Ava Hughes1.0 (deepest save from 11% of band)9
17Harry Ingram7 (5 descents, lowest 7% of band)6.0 (deepest save from 7% of band)20
18William Irwin2.0 (deepest save from 12% of band)12
19Evie Jarvis11 (6 descents, lowest 11% of band)7.0 (deepest save from 11% of band)26
20Mia Jensen1.0 (deepest save from 7% of band)4
21Ethan Kelly1.0 (deepest save from 5% of band)14
22Oscar Knight15 (6 descents, lowest 14% of band)7.0 (deepest save from 14% of band)28
23Matilda Larsen8 (6 descents, lowest 7% of band)7.0 (deepest save from 7% of band)23
24Grace Lowe0.017
25Jasper Mercer6 (6 descents, lowest 5% of band)7.0 (deepest save from 5% of band)14
26Lucas Murphy2.0 (deepest save from 5% of band)15
27Harper Newton13 (6 descents, lowest 13% of band)7.0 (deepest save from 13% of band)15
28Chloe Nolan8 (2 descents, lowest 8% of band)3.0 (deepest save from 8% of band)9
29Henry OConnor13 (2 descents, lowest 13% of band)3.0 (deepest save from 13% of band)21
30Toby Osborne6 (6 descents, lowest 6% of band)7.0 (deepest save from 6% of band)22
31Georgia Palmer10 (7 descents, lowest 10% of band)8.0 (deepest save from 10% of band)20
32Zoe Patel2.0 (deepest save from 12% of band)12
33Oliver Quinn6 (2 descents, lowest 6% of band)3.0 (deepest save from 6% of band)17
34Angus Rankin11 (7 descents, lowest 10% of band)8.0 (deepest save from 10% of band)13
35Ruby Reid12 (2 descents, lowest 12% of band)3.0 (deepest save from 12% of band)12
36Thomas Singh8 (2 descents, lowest 8% of band)3.0 (deepest save from 7% of band)17
37Maya Sutton14 (7 descents, lowest 14% of band)8.0 (deepest save from 14% of band)26
38Fergus Tobin13 (7 descents, lowest 12% of band)8.0 (deepest save from 12% of band)18
39Isla Turner5 (3 descents, lowest 5% of band)4.0 (deepest save from 5% of band)16
40Alice Underhill12 (8 descents, lowest 12% of band)9.0 (deepest save from 12% of band)26
41Charlie Underwood12 (3 descents, lowest 12% of band)4.0 (deepest save from 12% of band)34
42Ella Vaughan12 (3 descents, lowest 11% of band)4.0 (deepest save from 11% of band)24
43Rory Voss13 (9 descents, lowest 13% of band)10.0 (deepest save from 13% of band)21
44Max Walker13 (3 descents, lowest 13% of band)4.0 (deepest save from 13% of band)17
45Hazel Whelan11 (9 descents, lowest 10% of band)10.0 (deepest save from 10% of band)22
46Lily Xu11 (3 descents, lowest 11% of band)4.0 (deepest save from 11% of band)24
47Cody Yates6 (9 descents, lowest 6% of band)10.0 (deepest save from 6% of band)27
48Leo Young7 (3 descents, lowest 7% of band)4.0 (deepest save from 7% of band)22
49Amelia Zammit8 (3 descents, lowest 8% of band)4.0 (deepest save from 8% of band)31
50Frankie Zeller10 (9 descents, lowest 9% of band)10.0 (deepest save from 9% of band)27

Share of race time spent hunting for the next climb

Measured in percent · lower is better

Time that goes into neither a climb nor progress down the course. This is the time spent to find lift, to stay up, and to decide what to do next. The value is the share of the speed-section time, from the start to ESS or to the landing, in which the pilot neither climbed in a thermal nor glided with real net speed. A lower value means less time lost between climbs.

Speed-section phase shares, field p25/median/p75: climb 30/35/39% · glide 38/45/54% · search 14/20/24%

best: could be chance (0.19)

Footnotes

How the field is compared

Everything that compares pilots to each other uses one shared clock. That includes gaggles, shared thermals, and the position of each pilot at the same moment. GlideComp resamples every track onto a common 10-second grid. Two pilots are therefore always compared at the same instant, whatever rate their instruments logged at.

Metric glossary

How GlideComp measures every metric on this page. On screen, the ⓘ beside a metric opens the same description in place. On paper, this section is the reference for all of them.

Day profile & wind

The day’s wind, hour by hour and leg by leg(“Wind” in tables)
Measured in kilometres per hour · no expected direction

What the air did, read from the field itself. We estimate the wind from the circling of every pilot. The first method is the drift of the circle centre, and the second method, used when the first is not available, is the modulation of the ground speed. We then combine the estimates two ways. The table by hour of day shows how the wind increased and changed direction through the day. The table by speed-section leg shows the wind on each part of the course. This metric describes the day, so it has no value for each pilot.

How strong the day’s climbs were, hour by hour(“Climb/hr” in tables)
Measured in metres per second · no expected direction

When the day started, reached its peak, and ended. We group the thermal climbs of all pilots by the hour in which each climb started, labelled in the time zone of the competition. The median and the 90th-percentile average climb rate for each hour show how the lift developed. This metric describes the day, so it has no value for each pilot.

Share of the flight spent in air that wasn’t sinking(“NonSink%” in tables)
Measured in percent · no expected direction

How much of the flight was in air worth being in. The value is the share of the airborne time of a pilot, on the shared grid, with a 30 s-smoothed vario at or above −0.5 m/s. The time they flew, the line they steered and the way the flight ended all feed this value. It is therefore a reading of the day as much as of the pilot. There is no expected direction, and the sign of the correlation is the finding. The timing table compares the window of the day’s best climbs against the time when the field launched.

Climbing

Climbing faster than the pilots sharing the thermal(“Out-climb” in tables)
Measured in percent · higher is better

When this pilot and other pilots were in the SAME thermal, who climbed faster? In every thermal that two pilots or more used, we rank each use by its average climb rate. The percentile of a use is the share of uses that were strictly slower. The value is the duration-weighted mean percentile over the shared climbs of the pilot. 50% is exactly average. 80% means they climbed faster than four in five of the pilots they shared lift with. The shared thermal is what separates centring skill from thermal selection: a pilot who only found better air gets no higher value here.

Time to core thermals(“Core s” in tables)
Measured in seconds · lower is better

How long the pilot takes to get into the best lift after they arrive in a thermal. For each thermal of 60 s or more, we measure the seconds from the entry until the 30 s rolling climb rate first reaches 90% of its peak in that thermal. The value is the median across the thermals of the pilot. Every second here is a second spent climbing slower than the thermal can carry them.

Climb rate at thermal exit(“LeaveRate” in tables)
Measured in metres per second · no expected direction

The median climb rate that the pilot left thermals at. For each thermal of 90 s or more, we take the climb rate over its final 30 s. A high value means they leave lift that still works. A low value means they stay in a climb until nothing is left. This is an absolute rate, so read it against the day: compare it with the median climb in "How strong the day’s climbs were". A pilot who leaves at 1.5 m/s leaves a good climb on a 1 m/s day, and takes the worst lift available on a 4 m/s day. There is no expected direction. The sign of the correlation says which behaviour paid on this task.

Share of lift turned in that was kept as a climb(“Kept%” in tables)
Measured in percent · no expected direction

How selective the pilot is about the lift they stop for. Each period of circling of 30 s or more after the start counts as lift that the pilot sampled. If the period overlaps a detected thermal, the pilot kept that lift. If it does not, they turned a few circles and left it. The value is the percentage kept. A low value means they are selective. A high value means they keep almost every climb they turn in. There is no expected direction: selection wins on a strong day and wastes time on a weak one.

How much of the thermal the pilot climbed before leaving it(“TopOut%” in tables)
Measured in percent · no expected direction

Does the pilot climb to the top of every thermal, or leave with lift still above them? We take the altitude where they left each thermal after the start, as a percentage of the day’s working band. 0% is the floor of the field and 100% is its ceiling. The value is the median. There is no expected direction: a climb to the top buys height in reserve, and an early departure buys time.

How round and consistent the circles were(“Round” in tables)
Measured in ratio · lower is better

Whether the pilot flies clean, repeatable circles, or moves around the thermal. We fit each detected circle by least squares. The RMS fit error divided by the fitted radius measures how round the turn was. The value is the median over all of the circles of the pilot. A lower value means smoother and more consistent turns.

Gliding

Glide speed between climbs(“GlideSpd” in tables)
Measured in kilometres per hour · higher is better

How fast the pilot moves down the course when they are on a glide. The value is the duration-weighted mean ground speed over every glide after the start, which is the glide distance divided by the glide time. A higher value means more ground covered in each minute between climbs.

Glide L/D against the field median(“GlideL/D” in tables)
Measured in ratio · higher is better

Whether the pilot found better air on glide than the other pilots on the same leg. For each completed speed-section leg, we take the pilot's glide-phase L/D. That is the path distance divided by the net altitude lost during the glides, and we skip a leg that loses less than 100 m. We divide it by the median L/D of the field on that same leg, and then average over the legs. 1.10 means the pilot glided 10% further for each metre lost than the usual pilot on those legs.

Gliding faster when the next climb is stronger(“SpeedToFly” in tables)
Measured in kilometres per hour · higher is better

Speed to fly: the pilot flies faster when a good climb is in front of them, and slower when it is not. We pair each glide after the start with the climb rate of the next thermal that starts within 5 minutes. The value is the mean glide speed before climbs stronger than the median, minus the mean glide speed before weaker climbs. +8 km/h means the pilot flew 8 km/h faster into the good climbs. This is a PROXY, and not true speed to fly, because there is no glider polar data.

Gliding wide of the optimal course line(“Wide%” in tables)
Measured in percent · lower is better

How much further the pilot flew on glide than the optimised course line needed. 0% is a flight exactly along the line, and 12% is a glide 12% further than necessary. On each completed speed-section leg, we compare the pilot's route with the optimised distance of the leg, weighted by that optimised distance. Only the glides are measured at their full path length. Circling and searching contribute their entry-to-exit displacement instead. A climb or a search for lift therefore never reads as a wide line, because a pilot chooses a line only on glide. 0% is a real value that a pilot can reach: a pilot who flies the line of the optimiser scores exactly zero.

Share of the height gain made outside thermals(“Dolphin%” in tables)
Measured in percent · no expected direction

Dolphin flying: how much of the height that the pilot gained came outside of circling. The value is the share of the altitude gain after the start, smoothed over 10 s, that the pilot made outside a detected thermal. There is no expected direction. The sign of the correlation shows whether dolphin flying paid on this day.

Decision-making

How low the pilot gets between climbs(“Floor%” in tables)
Measured in percent · no expected direction

How low the pilot goes before the next climb. A high value is a race with height in reserve, and a low value is a flight that goes down near the ground. We take each pair of climbs that the pilot made after the start, and we find the lowest point between them. We keep only the gaps that go down 100 m or more, because a top-up between two climbs is not a descent. We do not count a sled run or the glide to goal, because the pilot made no climb after them. The value is the median of those low points, as a percentage of the day's working band. 0% is where the lowest tenth of the field's climbs started, and 100% is where the highest tenth stopped. Thus a negative value shows that the pilot went lower than almost all of the field. The pilot must have two or more of these descents. There is no expected direction. The sign of the correlation says whether height in reserve pays.

Low saves dug out from the bottom of the band(“LowSaves” in tables)
Measured in count · no expected direction

How many times the pilot got low and climbed out again. We count the climbs after the start that the pilot entered below 15% of the working band, and that then gained 300 m or more. Those are true low saves. Zero is a real value, and not a missing one: it means the pilot never got that low. There is no expected direction. The sign of the correlation says whether a climb-out or a flight that stays high pays.

Distance covered between climbs(“km/climb” in tables)
Measured in kilometres · higher is better

How far the pilot gets down the course before they must stop and circle again. This is the direct reading of how often they stop. The value is the scored flown distance divided by the number of thermals taken after the start, so 3 km means three kilometres of course for each climb. The pilot must fly 20 km or more. The note of each pilot adds their mean climb percentile inside shared thermals, so you can read the number of stops together with the climb strength. Long legs between weak climbs is a different day from long legs between strong ones.

Share of race time spent hunting for the next climb(“Search%” in tables)
Measured in percent · lower is better

Time that goes into neither a climb nor progress down the course. This is the time spent to find lift, to stay up, and to decide what to do next. The value is the share of the speed-section time, from the start to ESS or to the landing, in which the pilot neither climbed in a thermal nor glided with real net speed. A lower value means less time lost between climbs.

Gaggle

Time spent flying with a gaggle(“InGaggle%” in tables)
Measured in percent · no expected direction

Whether the pilot raced with other pilots or alone. The value is the share of their flying time after the start inside a detected gaggle, that is, clustered with one other racing pilot or more on the shared time grid. There is no expected direction. A gaggle increases the power to search for lift, but it also holds a pilot to its own speed. The sign of the correlation says which of the two occurred here.

Climbs joined on another pilot's marker(“Marked%” in tables)
Measured in percent · no expected direction

How much of the lift of the pilot another pilot found first. The value is the share of their climbs after the start where another pilot was already established in the same thermal when they arrived. Established means 30 s or more into the climb, and still climbing. A high value means they mostly climb on the markers of other pilots. A low value means they find their own air. There is no expected direction. A marker is free information, but it puts a pilot where the last climb was, and not where the next one is.

How often leaving the gaggle paid off(“LeaveWin%” in tables)
Measured in percent · no expected direction

When a pilot leaves a gaggle that continues to fly, did the departure pay off? We compare the arrival of the pilot who left at the next turnpoint against the median arrival of the pilots who stayed. A win rate of more than 50% means their departures beat the gaggle. A pilot counts as a pilot who stayed only if they were still in the gaggle after the split, and reached that turnpoint after it.

Race craft

How long after the gate opened the pilot started(“StartDly” in tables)
Measured in seconds · lower is better

Every second between the opening of the gate and the crossing of the start line is a second lost for nothing. The value is the seconds from the start gate taken to the scored SSS crossing. On an elapsed-time task, the pilot’s own crossing is the reference, so the delay is 0 by definition. The start table adds the crossing altitude, and the distance behind the leading pilot who had already started.

Race time lost against the fastest pilots, leg by leg(“TimeLost” in tables)
Measured in seconds · lower is better

For each completed speed-section leg, we compare the leg time of the pilot with the mean of the top 10 pilots by rank who completed that leg. Only the losses count, and we add them together. The sum of the leg times is the race time, and the rank defines the reference, so this metric follows the result by construction. Read the waterfall table, which shows every leg against the task winner, for the diagnosis. Do not read the correlation as a finding.

Race time behind the leader at ESS(“Behind” in tables)
Measured in minutes · lower is better

At each speed-section turnpoint, we compare the elapsed race time of the pilot, which is the reaching time minus their own start, with the fastest pilot to that turnpoint. The value is the minutes behind at ESS. It follows the final rank almost exactly, because this metric is the sanity check of the evaluation.

Arriving at ESS with height to spare(“Spare m” in tables)
Measured in metres · lower is better

Height still available at ESS that the pilot no longer needed. That altitude was available for more speed, and the pilot did not use it. The value is the altitude at ESS minus the altitude needed to glide to goal at the standard glide ratio of the sport, which is 5.0 for HG and 4.0 for PG (S7F §13.4.6). A large positive margin means the pilot arrived too high. A margin near zero means they flew the final glide with little height to spare.

Final glide committed to when leaving the last climb(“FinalGl” in tables)
Measured in ratio · no expected direction

How optimistic the pilot was about their final glide. A pilot wins or loses a task by the height at which they leave the last climb. At the last climb of the pilot before ESS, or before the landing, we divide the distance to goal by their height above goal. That is the glide ratio they committed to. 8 means they left and needed 8:1 to make goal. The value counts only when that climb ended within 1.5 times the length of the last course leg longer than 1 km from goal — when ESS and goal share a waypoint, the zero-length hop between them is not that leg. There is no expected direction: a marginal glide wins if it connects, and loses if it does not.