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Task 3 (Open)

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

ELLIOTELLIOTKANGCKBIGARATOOMALIGHTHDWYERSKHANCOKHANCO
The optimised route. Pilots fly it in the direction of the arrows. The radii, the leg distances and the start times are on the task page.

Analysis computed

Pilots
37
Airtime
82h (13:42–18:19 AEDT)
Thermals
18251 shared by 2+ pilots
Working band
8942575 m
Airtime split
  • 38%climbing
  • 23%gliding
  • 39%searching

What the weather did

Bushfire smoke was visible

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 average the vectors 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 — measured and modelled alike — share one time axis (AEDT), so a vertical scan compares the two at the same moment. Arrows fly WITH the wind — direction figures are degrees the wind blows from; arrow length and opacity track speed and sample count. On the per-leg chart the pale bar is when the field flew that leg and the solid band inside it is the circling its wind was measured from — a leg the field glided is measured in a sliver of the time it was flown. Exact numbers are in the day family’s tables under “The metrics in detail”.

Which behaviours went with better results

Every row is one behaviour, measured for each pilot and then compared against the published placings (Spearman's rank correlation, ρ). Rank 1 is best, so a behaviour where more is better shows a negative ρ. A bigger bar means the behaviour tracked the placings more closely on this task, and pilots measured is how much of the analysed field the behaviour applied to — a reading drawn from half the field is thinner than one drawn from all of it. Select a row to see that behaviour plotted against rank — the chart stays in view while you work down the table.

Low saves dug out from the bottom of the band

Each dot is a pilot: across is what was measured, up is a better rank. ρ = -0.61 (clear pattern, n = 37). No expected direction — the sign is the finding: larger values went with better ranks here. The curve is a trend fitted through the dots: left to right it runs from about rank 25 to about rank 4.
BehaviourStrengthWhat it meansPilots measured
Low saves dug out from the bottom of the band
clear pattern
Glide speed between climbs
clear pattern
Time spent flying with a gaggle
clear pattern
How long after the gate opened the pilot started
some pattern
Climbing faster than the pilots sharing the thermal
some pattern
Climb rate at thermal exit
could be chance
Share of lift turned in that was kept as a climb
could be chance
Glide L/D against the field median
could be chance
Share of the height gain made outside thermals
could be chance
How low the pilot gets between climbs
could be chance
Climbs joined on another pilot's marker
could be chance
Share of race time spent hunting for the next climb
could be chance
How often leaving the gaggle paid off
could be chance
How much of the thermal the pilot climbed before leaving it
could be chance
Share of the flight spent in air that wasn’t sinking
could be chance
Gliding faster when the next climb is stronger
could be chance
How round and consistent the circles were
could be chance
Gliding wide of the optimal course line
could be chance
Time to core thermals
could be chance
Distance covered between climbs
could be chance

clear pattern is |ρ| ≥ 0.5, some pattern ≥ 0.3 and faint pattern below — each only once the coefficient is bigger than chance alone produces at that many pilots (its noise floor). could be chance (in the statistics: within noise) means shuffling the placings produces a coefficient that size more than 5% of the time, so it cannot be told apart from luck however big it looks. too few pilots is fewer than 8 pilots with a value — not enough to tell either way.

Rank 20 behaviours against one day's results and a few will look strong on luck alone — the ones worth believing are those that repeat across tasks in the competition-level analysis.

Outcome checks

These are not behaviours. They measure the result itself, for example the time behind the leader and the race time lost, so they always follow the places. They are here as a check on the analysis. A weak pattern in this table means that something is wrong in the numbers, and not in the flying of any pilot. Their per-pilot tables stay in the Race craft section below.

OutcomeStrengthWhat it meansPilots measured
Race time lost against the fastest pilots, leg by leg
could be chance

The whole field at a glance

1. Rory Duncan
2. Jon Durand
3. Neale Halsall
4. Glen Mcfarlane
5. Steven Crosby
6. Steve Blenkinsop
7. Rich Reinauer
8. David Drabble
9. Paul Bissett-Amess
10. Harrison Rowntree
11. Gordon Rigg
12. Daniel Rhodes
13. Mitch Butler
14. Craig Taylor
15. Diego Mendonca
16. Rohan Holtkamp
17. Troy Horton
18. Andrew Sutton
19. John Muldoon
20. Todd Wisewould
21. Rennick Kerr
22. Olav Opsanger
23. Vic Hare
24. Neil Hooke
25. Trent Brown
26. Nils Vesk
27. Peter Burkitt
28. Michael Free
29. Enda Carrigan
30. Ivo van der Leeden
31. Hossain Tefaili
32. Bruce Atkinson
33. Ward Gunn
34. Airie Merlin
35. Brett Davis
36. Gary Herman
37. Thomas McDonald
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. The columns start with the behaviours whose better end went with better places, continue through the behaviours that separated nobody, and end with the behaviours that ran the other way. A field that one behaviour separated therefore shades dark in the top-left corner, and a field where each pilot won differently does not. The band above rates how much pattern each group of columns holds: a clear, some or faint pattern, noise (could be chance), or too few pilots to tell. The family sections below carry the exact values. † This behaviour has no good or bad direction. The shade is the position in the field, and not the quality.

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. Each group carries the name of its strongest signature. A ★ marks the pilot most typical of their group.

Group ASink crossers

10 pilots · ranks 125 · median 10.5 · middle half 8.319.8

  • LowShare of the flight spent in air that wasn’t sinking group median P18 in this field (54 percent)
  • HighGlide L/D against the field median group median P82 in this field (1.07 ratio) · usually a strength
  • HighClimb rate at thermal exit group median P81 in this field (1.5 metres per second)
  • HighHow much of the thermal the pilot climbed before leaving it group median P79 in this field (71 percent)
  • 1. Rory Duncan
  • 6. Steve Blenkinsop
  • 8. David Drabble
  • 9. Paul Bissett-Amess
  • 10. Harrison Rowntree (most typical of this group)
  • 11. Gordon Rigg
  • 13. Mitch Butler
  • 22. Olav Opsanger
  • 23. Vic Hare
  • 25. Trent Brown

Group BStop-often flyers

21 pilots · ranks 237 · median 18 · middle half 1227

  • LowDistance covered between climbs group median P28 in this field (1.4 kilometres) · usually costly
  • LowLow saves dug out from the bottom of the band group median P28 in this field (0.0 count)
  • HighShare of race time spent hunting for the next climb group median P69 in this field (45 percent) · usually costly
  • LowHow round and consistent the circles were group median P31 in this field (0.16 ratio) · usually a strength
  • 2. Jon Durand
  • 3. Neale Halsall
  • 4. Glen Mcfarlane
  • 5. Steven Crosby
  • 7. Rich Reinauer
  • 12. Daniel Rhodes
  • 14. Craig Taylor
  • 15. Diego Mendonca
  • 16. Rohan Holtkamp
  • 17. Troy Horton
  • 18. Andrew Sutton
  • 19. John Muldoon
  • 20. Todd Wisewould
  • 21. Rennick Kerr
  • 24. Neil Hooke
  • 27. Peter Burkitt (most typical of this group)
  • 29. Enda Carrigan
  • 31. Hossain Tefaili
  • 33. Ward Gunn
  • 35. Brett Davis
  • 37. Thomas McDonald

Group CThermal milkers

5 pilots · ranks 2634 · median 30 · middle half 2832

  • LowClimb rate at thermal exit group median P6 in this field (0.3 metres per second)
  • LowClimbing faster than the pilots sharing the thermal group median P6 in this field (50 percent) · usually costly
  • HighHow round and consistent the circles were group median P91 in this field (0.23 ratio) · usually costly
  • LowGlide speed between climbs group median P9 in this field (47.4 kilometres per hour) · usually costly
  • 26. Nils Vesk
  • 28. Michael Free
  • 30. Ivo van der Leeden (most typical of this group)
  • 32. Bruce Atkinson
  • 34. Airie Merlin

Not clustered: 36. Gary Herman — only 5 of 20 metrics available (needs ≥ 60%).

GlideComp groups the pilots by flying style, and not by score. It transforms the rank of every behavioural metric to a percentile inside the field. It then compares two pilots by the mean percentile gap over the metrics that both pilots have, and never fills in a missing value. Ward-linkage agglomeration forms the groups, and the best mean silhouette selects the number of groups. Each group carries the spread of the GAP ranks of its members, which shows where a style paid and where it did not. On this task, 36 pilots on 20 behavioural metrics formed 3 groups, with k searched from 2 to 6. The mean silhouette is 0.16. A value near 0 means soft group boundaries, and a value near 1 means tight, well-separated groups.

The metrics in detail

best: could be chance (0.04)

best: some pattern (0.45)

best: clear pattern (0.54)

#PilotGlideSpdGlideL/DSpeedToFlyWide%Dolphin%
1Rory Duncan73.1 (13 glides, 65 min gliding)1.03 (6 legs compared)-3.1 (12 glide→climb pairs)19 (6 legs completed)4 (282 of 6653 m gained outside thermals)
2Jon Durand60.2 (16 glides, 86 min gliding)1.03 (5 legs compared)2.2 (15 glide→climb pairs)28 (5 legs completed)13 (682 of 5303 m gained outside thermals)
3Neale Halsall62.0 (30 glides, 120 min gliding)0.92 (3 legs compared)2.2 (29 glide→climb pairs)57 (4 legs completed)18 (1014 of 5725 m gained outside thermals)
4Glen Mcfarlane58.2 (13 glides, 101 min gliding)0.99 (3 legs compared)1.8 (12 glide→climb pairs)35 (4 legs completed)12 (638 of 5321 m gained outside thermals)
5Steven Crosby56.9 (20 glides, 108 min gliding)1.05 (3 legs compared)0.4 (19 glide→climb pairs)33 (4 legs completed)15 (820 of 5301 m gained outside thermals)
6Steve Blenkinsop62.0 (10 glides, 68 min gliding)1.07 (3 legs compared)-0.8 (9 glide→climb pairs)29 (4 legs completed)5 (227 of 4525 m gained outside thermals)
7Rich Reinauer70.7 (26 glides, 92 min gliding)0.83 (2 legs compared)4.0 (25 glide→climb pairs)100 (4 legs completed)11 (950 of 8533 m gained outside thermals)
8David Drabble68.9 (17 glides, 75 min gliding)1.18 (3 legs compared)0.4 (16 glide→climb pairs)44 (4 legs completed)16 (652 of 4162 m gained outside thermals)
9Paul Bissett-Amess59.5 (16 glides, 68 min gliding)0.98 (2 legs compared)0.9 (15 glide→climb pairs)41 (4 legs completed)10 (434 of 4462 m gained outside thermals)
10Harrison Rowntree66.6 (14 glides, 60 min gliding)1.02 (4 legs compared)-2.9 (13 glide→climb pairs)29 (4 legs completed)8 (340 of 4152 m gained outside thermals)
11Gordon Rigg58.8 (11 glides, 68 min gliding)0.94 (2 legs compared)9.6 (10 glide→climb pairs)34 (4 legs completed)3 (124 of 4730 m gained outside thermals)
12Daniel Rhodes70.3 (21 glides, 91 min gliding)0.93 (2 legs compared)0.7 (20 glide→climb pairs)55 (3 legs completed)11 (731 of 6839 m gained outside thermals)
13Mitch Butler62.7 (19 glides, 82 min gliding)1.08 (2 legs compared)3.2 (18 glide→climb pairs)50 (3 legs completed)12 (474 of 3910 m gained outside thermals)
14Craig Taylor69.0 (13 glides, 69 min gliding)0.92 (3 legs compared)8.3 (12 glide→climb pairs)44 (3 legs completed)13 (586 of 4558 m gained outside thermals)
15Diego Mendonca51.8 (28 glides, 110 min gliding)1.06 (2 legs compared)3.8 (27 glide→climb pairs)95 (3 legs completed)17 (982 of 5711 m gained outside thermals)
16Rohan Holtkamp57.0 (16 glides, 87 min gliding)1.02 (2 legs compared)2.0 (15 glide→climb pairs)36 (3 legs completed)17 (729 of 4254 m gained outside thermals)
17Troy Horton53.2 (21 glides, 80 min gliding)0.95 (3 legs compared)-2.0 (20 glide→climb pairs)48 (3 legs completed)13 (591 of 4468 m gained outside thermals)
18Andrew Sutton56.6 (19 glides, 68 min gliding)0.83 (2 legs compared)2.3 (18 glide→climb pairs)38 (3 legs completed)12 (499 of 4230 m gained outside thermals)
19John Muldoon48.2 (16 glides, 72 min gliding)1.06 (2 legs compared)4.3 (15 glide→climb pairs)55 (3 legs completed)11 (499 of 4598 m gained outside thermals)
20Todd Wisewould61.8 (21 glides, 62 min gliding)0.97 (2 legs compared)-0.6 (20 glide→climb pairs)54 (3 legs completed)21 (794 of 3714 m gained outside thermals)
21Rennick Kerr45.4 (16 glides, 88 min gliding)0.81 (3 legs compared)-1.5 (15 glide→climb pairs)41 (3 legs completed)20 (903 of 4480 m gained outside thermals)
22Olav Opsanger65.3 (7 glides, 44 min gliding)1.49 (3 legs compared)6.5 (6 glide→climb pairs)10 (3 legs completed)17 (275 of 1604 m gained outside thermals)
23Vic Hare69.9 (12 glides, 42 min gliding)4.0 (11 glide→climb pairs)-4 (2 legs completed)18 (493 of 2796 m gained outside thermals)
24Neil Hooke52.8 (10 glides, 46 min gliding)0.72 (2 legs compared)-0.4 (9 glide→climb pairs)26 (2 legs completed)15 (499 of 3233 m gained outside thermals)
25Trent Brown58.4 (2 glides, 24 min gliding)1.12 (2 legs compared)5 (2 legs completed)4 (83 of 2103 m gained outside thermals)
26Nils Vesk51.6 (5 glides, 37 min gliding)0.86 (2 legs compared)2.9 (4 glide→climb pairs)37 (2 legs completed)7 (211 of 2919 m gained outside thermals)
27Peter Burkitt58.3 (11 glides, 43 min gliding)1.16 (1 leg compared)-0.7 (10 glide→climb pairs)32 (2 legs completed)11 (349 of 3190 m gained outside thermals)
28Michael Free45.7 (10 glides, 41 min gliding)0.93 (1 leg compared)0.1 (9 glide→climb pairs)35 (2 legs completed)7 (152 of 2283 m gained outside thermals)
29Enda Carrigan54.4 (8 glides, 61 min gliding)0.83 (1 leg compared)-5.4 (7 glide→climb pairs)99 (2 legs completed)14 (621 of 4405 m gained outside thermals)
30Ivo van der Leeden47.4 (4 glides, 37 min gliding)0.82 (1 leg compared)20 (2 legs completed)5 (89 of 1698 m gained outside thermals)
31Hossain Tefaili55.3 (7 glides, 25 min gliding)1.05 (1 leg compared)-1.6 (6 glide→climb pairs)23 (2 legs completed)23 (302 of 1321 m gained outside thermals)
32Bruce Atkinson51.9 (4 glides, 31 min gliding)2.31 (2 legs compared)68 (2 legs completed)2 (10 of 567 m gained outside thermals)
33Ward Gunn63.2 (17 glides, 55 min gliding)0.77 (2 legs compared)2.6 (16 glide→climb pairs)267 (2 legs completed)20 (598 of 2974 m gained outside thermals)
34Airie Merlin45.6 (1 glides, 15 min gliding)0.54 (2 legs compared)20 (2 legs completed)11 (68 of 647 m gained outside thermals)
35Brett Davis47.5 (6 glides, 20 min gliding)0.69 (1 leg compared)6.7 (5 glide→climb pairs)95 (1 leg completed)27 (192 of 712 m gained outside thermals)
36Gary Herman
37Thomas McDonald58.3 (3 glides, 17 min gliding)27 (117 of 437 m gained outside thermals)

Glide speed between climbs

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.

Field glide speed: median 58.3 km/h · p90 69.5 km/h (36 pilots)

best: clear pattern (0.61)

#PilotFloor%LowSaveskm/climbSearch%
1Rory Duncan53 (11 descents, lowest -3% of band)2.0 (deepest save from 0% of band)4.0 (mean shared-climb pctile 86%)24
2Jon Durand1 (6 descents, lowest -6% of band)2.0 (deepest save from 4% of band)2.5 (mean shared-climb pctile 52%)36
3Neale Halsall26 (13 descents, lowest -20% of band)1.0 (deepest save from 6% of band)1.2 (mean shared-climb pctile 48%)53
4Glen Mcfarlane-7 (5 descents, lowest -13% of band)3.0 (deepest save from -3% of band)1.8 (mean shared-climb pctile 59%)39
5Steven Crosby23 (8 descents, lowest -12% of band)1.0 (deepest save from -6% of band)2.1 (mean shared-climb pctile 52%)46
6Steve Blenkinsop83 (5 descents, lowest 19% of band)0.03.4 (mean shared-climb pctile 54%)24
7Rich Reinauer10 (11 descents, lowest -20% of band)4.0 (deepest save from -4% of band)1.4 (mean shared-climb pctile 61%)28
8David Drabble58 (8 descents, lowest 31% of band)0.01.8 (mean shared-climb pctile 55%)38
9Paul Bissett-Amess68 (7 descents, lowest 10% of band)1.0 (deepest save from 14% of band)2.1 (mean shared-climb pctile 49%)34
10Harrison Rowntree32 (7 descents, lowest 3% of band)1.0 (deepest save from 8% of band)2.7 (mean shared-climb pctile 57%)33
11Gordon Rigg23 (6 descents, lowest 7% of band)1.0 (deepest save from 13% of band)4.5 (mean shared-climb pctile 42%)35
12Daniel Rhodes45 (12 descents, lowest 6% of band)1.0 (deepest save from 5% of band)1.3 (mean shared-climb pctile 55%)47
13Mitch Butler69 (11 descents, lowest -9% of band)0.01.7 (mean shared-climb pctile 43%)42
14Craig Taylor13 (8 descents, lowest -9% of band)1.0 (deepest save from 5% of band)1.7 (mean shared-climb pctile 56%)43
15Diego Mendonca72 (15 descents, lowest -23% of band)0.01.0 (mean shared-climb pctile 49%)50
16Rohan Holtkamp29 (5 descents, lowest -19% of band)1.0 (deepest save from 11% of band)1.5 (mean shared-climb pctile 41%)45
17Troy Horton26 (6 descents, lowest -9% of band)0.01.4 (mean shared-climb pctile 53%)44
18Andrew Sutton25 (5 descents, lowest 6% of band)0.01.3 (mean shared-climb pctile 44%)46
19John Muldoon16 (8 descents, lowest -5% of band)1.0 (deepest save from 8% of band)1.3 (mean shared-climb pctile 41%)37
20Todd Wisewould73 (9 descents, lowest -25% of band)0.01.0 (mean shared-climb pctile 54%)40
21Rennick Kerr1 (7 descents, lowest -15% of band)1.0 (deepest save from 0% of band)1.2 (mean shared-climb pctile 56%)43
22Olav Opsanger-5 (3 descents, lowest -21% of band)0.05.7 (mean shared-climb pctile 53%)33
23Vic Hare48 (7 descents, lowest -17% of band)0.01.6 (mean shared-climb pctile 45%)38
24Neil Hooke13 (4 descents, lowest -9% of band)0.01.6 (mean shared-climb pctile 35%)32
25Trent Brown0.011.5 (mean shared-climb pctile 56%)20
26Nils Vesk-3 (4 descents, lowest -4% of band)2.0 (deepest save from -3% of band)6.6 (mean shared-climb pctile 28%)20
27Peter Burkitt27 (6 descents, lowest -4% of band)0.01.6 (mean shared-climb pctile 48%)41
28Michael Free4 (5 descents, lowest -2% of band)0.02.4 (mean shared-climb pctile 24%)25
29Enda Carrigan30 (5 descents, lowest 15% of band)0.01.5 (mean shared-climb pctile 49%)45
30Ivo van der Leeden1.0 (deepest save from 14% of band)4.2 (mean shared-climb pctile 36%)29
31Hossain Tefaili10 (2 descents, lowest 0% of band)0.047
32Bruce Atkinson74 (3 descents, lowest 61% of band)0.032
33Ward Gunn17 (2 descents, lowest 12% of band)0.046
34Airie Merlin0.025
35Brett Davis7 (2 descents, lowest -5% of band)0.069
36Gary Herman0.091
37Thomas McDonald0.065

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 29/32/35% · glide 24/29/33% · search 32/39/46%

best: clear pattern (0.51)

#PilotInGaggle%Marked%LeaveWin%
1Rory Duncan2230 (6/20 climbs marked)
2Jon Durand6733 (9/27 climbs marked)
3Neale Halsall4528 (15/53 climbs marked)0 (0W–2L (2 departures))
4Glen Mcfarlane7537 (13/35 climbs marked)
5Steven Crosby6839 (12/31 climbs marked)50 (1W–1L (2 departures))
6Steve Blenkinsop3433 (6/18 climbs marked)100 (3W–0L (3 departures))
7Rich Reinauer2920 (9/45 climbs marked)
8David Drabble4852 (17/33 climbs marked)100 (2W–0L (2 departures))
9Paul Bissett-Amess4963 (17/27 climbs marked)50 (1W–1L (2 departures))
10Harrison Rowntree2733 (7/21 climbs marked)100 (2W–0L (2 departures))
11Gordon Rigg5050 (6/12 climbs marked)100 (2W–0L (2 departures))
12Daniel Rhodes815 (6/39 climbs marked)
13Mitch Butler4737 (11/30 climbs marked)50 (1W–1L (2 departures))
14Craig Taylor3855 (16/29 climbs marked)
15Diego Mendonca4031 (15/49 climbs marked)
16Rohan Holtkamp2924 (8/33 climbs marked)0 (0W–1L (1 departure))
17Troy Horton6866 (21/32 climbs marked)0 (0W–2L (2 departures))
18Andrew Sutton7461 (20/33 climbs marked)0 (0W–3L (3 departures))
19John Muldoon2433 (11/33 climbs marked)
20Todd Wisewould2629 (11/38 climbs marked)
21Rennick Kerr1333 (11/33 climbs marked)
22Olav Opsanger1957 (4/7 climbs marked)
23Vic Hare4539 (9/23 climbs marked)
24Neil Hooke1748 (11/23 climbs marked)100 (1W–0L (1 departure))
25Trent Brown2567 (2/3 climbs marked)
26Nils Vesk4140 (2/5 climbs marked)
27Peter Burkitt4152 (11/21 climbs marked)100 (1W–0L (1 departure))
28Michael Free531 (4/13 climbs marked)
29Enda Carrigan1452 (11/21 climbs marked)
30Ivo van der Leeden017 (1/6 climbs marked)
31Hossain Tefaili3883 (10/12 climbs marked)
32Bruce Atkinson513 (1/8 climbs marked)
33Ward Gunn2539 (11/28 climbs marked)100 (1W–0L (1 departure))
34Airie Merlin31
35Brett Davis4878 (7/9 climbs marked)
36Gary Herman0
37Thomas McDonald00 (0/4 climbs marked)

Time spent flying with a gaggle

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.

54 gaggle episodes detected (peak size 13 pilots).

best: some pattern (0.48)

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 average the vectors 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 §12.3.6). 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 distance of the final leg from goal. There is no expected direction: a marginal glide wins if it connects, and loses if it does not.