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Task 1 (Open)

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

ell094ell094tho084bog065ber062tow040ell030
The optimised route — radii, leg distances and start times are on the task page.

Analysis computed

Hold tight, the analysis is being recomputed…
Something changed (a track, a penalty, or the task). The analysis below was computed before that change and may shift slightly.
Pilots
14
Airtime
33h (12:55–16:32 AEDT)
Thermals
9626 shared by 2+ pilots
Working band
7791918 m
Airtime split
  • searching35%
  • climbing36%
  • gliding29%

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

A vertical scan compares the measured and the modelled at the same moment. 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”.

The day's thermals

The 40 most-shared of 46 multi-pilot thermals, reconstructed by pooling every pilot's track through the same climb. Everything shown is measured from the tracks — no fitted lift model.

StartPilotsHeight bandMean climbStrongest sideDetail
99001700 m+2.0 m/sSW
37002000 m+2.2 m/sE
69002100 m+2.9 m/sE
515002000 m+2.5 m/sNW
814002000 m+2.2 m/sSW
68001900 m+2.3 m/sN
129001900 m+1.4 m/sSW
514001800 m+1.2 m/sE
1312002000 m+1.3 m/sNE
816002000 m+0.8 m/sN
36001700 m+2.2 m/sNW
1114001900 m+1.4 m/sN
1313002100 m+2.3 m/sSE
98001800 m+1.5 m/sW
314001700 m+1.0 m/sE
410001700 m+1.3 m/sE
911002100 m+2.8 m/sW
211001500 m+1.6 m/sW
27001600 m+1.9 m/sW
58002000 m+2.2 m/sW
68002100 m+1.4 m/sE
512001900 m+1.6 m/sW
414001900 m+1.3 m/sE
38002000 m+1.8 m/sNE
29001200 m+1.2 m/sS
28001200 m+1.1 m/sNE
38001400 m+1.0 m/sE
29001500 m+1.5 m/sS
47001900 m+2.4 m/sW
25001400 m+1.8 m/sNW
513002000 m+1.4 m/sSW
417002100 m+1.2 m/sN
39002100 m+2.3 m/sW
27001900 m+1.5 m/sW
47002100 m+2.3 m/sSW
318002100 m+1.6 m/sS
26001700 m+2.1 m/sNE
26001200 m+1.7 m/sE
214002000 m+1.3 m/sNW
216002100 m+1.9 m/sSE

Thermal at 13:38 AEDT 13 pilots, 24 climbs

  • Wind 14.9 km/h from 308° (NW), measured from 45 circle estimates in the pilots' own tracks.
  • Model wind cross-check loading…
  • Leans 33° from vertical toward 138° (SE), within 10° of downwind.
  • Strongest on the NE side of the core at +1.7 m/s against +1.6 m/s on the SW side.
  • Multiple cores in 2 of 8 bands between 1500 and 1900 m — separate feeders (⬧ in the rose) before they merged.
Watch this thermal in the 3D replay (opens in a new tab)
Pilots in this thermal (climb rates)
PilotMinMedianMax
James Thompson-0.5 m/s+1.8 m/s+4.3 m/s
Rafael Esquillaro-1.5 m/s+1.8 m/s+4.0 m/s
Gareth Carter-0.3 m/s+1.5 m/s+3.0 m/s
Zane Priebbenow-1.3 m/s+1.5 m/s+3.5 m/s
Andy McMurray+0.3 m/s+1.3 m/s+3.5 m/s
Wally Arcidiacono-1.5 m/s+1.3 m/s+3.8 m/s
Richard Binstead-0.5 m/s+1.3 m/s+3.5 m/s
Brian Webb-1.5 m/s+1.0 m/s+3.0 m/s
Kari Ellis-2.0 m/s+1.0 m/s+3.3 m/s
Jan Bennewitz-0.5 m/s+0.8 m/s+1.8 m/s
Geoff Wong-0.8 m/s+0.7 m/s+2.5 m/s
Phillip Mansell-0.5 m/s+0.5 m/s+2.8 m/s
Frank Adler+0.0 m/s+0.5 m/s+2.5 m/s

Each pilot's slowest, typical and best climb over their own vario samples in this thermal — a negative minimum means they touched sink inside it.

Band table (exact numbers)
BandCore offset E/N (m)Working radiusExtentMean climbBest climbSamplesPilotsCores
19002000 m137 / -76177 m307 m+1.0 m/s+2.8 m/s10631
18001900 m36 / -33191 m287 m+1.4 m/s+4.3 m/s31872
17001800 m-49 / 120217 m449 m+1.4 m/s+4.0 m/s31561
16001700 m-24 / 10210 m406 m+1.3 m/s+3.8 m/s16361
15001600 m-52 / 16138 m220 m+1.3 m/s+3.3 m/s17133
14001500 m-143 / 31736 m46 m+1.4 m/s+3.0 m/s2611
13001400 m-189 / 313235 m502 m+1.3 m/s+3.5 m/s6421
12001300 m-241 / 33377 m158 m+1.2 m/s+3.0 m/s3711

The dashed arrow is the weather model’s wind — a model run, not an observation.

Each thermal pools every pilot’s fixes through the same climb into 100 m altitude bands. A band’s core is the lift-weighted centre of its fixes, so the rose and the sector readings are already normalised for the thermal’s lean and drift.

Wedge length is relative climb by side of the core; the dashed ring is the measured working radius and the dotted ring the widest the field ranged. The solid arrow is the wind measured from the pilots’ circles.

Which behaviours went with better ranks

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

Low saves dug out from the bottom of the band

Each dot is a pilot. ρ = -0.76 (clear pattern, n = 14). 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 11 to about rank 6.
BehaviourStrengthWhat it meansPilots measured
Low saves dug out from the bottom of the band
clear pattern
How often leaving the gaggle paid off
too few pilots
Gliding wide of the optimal course line
could be chance
Share of the height gain made outside thermals
could be chance
Glide L/D against the field median
could be chance
Share of the flight spent in air that wasn’t sinking
could be chance
How long after the gate opened the pilot started
could be chance
How much of the thermal the pilot climbed before leaving it
could be chance
Share of lift turned in that was kept as a climb
could be chance
Climb rate at thermal exit
could be chance
Glide speed between climbs
could be chance
Time spent flying with a gaggle
could be chance
Time to core thermals
could be chance
Climbs joined on another pilot's marker
could be chance
How round and consistent the circles were
could be chance
Share of race time spent hunting for the next climb
could be chance
Distance covered between climbs
could be chance
How low the pilot gets between climbs
could be chance
Climbing faster than the pilots sharing the thermal
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.

Outcome checks

These measure the result, not a behaviour, so they always follow the ranks.

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

The whole field at a glance

1. Geoff Wong
2. Gareth Carter
3. Richard Binstead
4. Rafael Esquillaro
5. Andy McMurray
6. Phillip Mansell
7. Martin Joyce
8. Wally Arcidiacono
9. Jan Bennewitz
10. Frank Adler
11. Brian Webb
12. James Thompson
13. Kari Ellis
14. Zane Priebbenow
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 APunished leavers

9 pilots · ranks 113 · median 5 · middle half 310

  • LowHow often leaving the gaggle paid off group median P25 in this field (0 percent)
  • HighHow much of the thermal the pilot climbed before leaving it group median P69 in this field (68 percent)
  • HighClimbing faster than the pilots sharing the thermal group median P69 in this field (70 percent) · usually a strength
  • LowShare of race time spent hunting for the next climb group median P31 in this field (30 percent) · usually a strength
  • 1. Geoff Wong
  • 2. Gareth Carter (most typical of this group)
  • 3. Richard Binstead
  • 4. Rafael Esquillaro
  • 5. Andy McMurray
  • 8. Wally Arcidiacono
  • 10. Frank Adler
  • 11. Brian Webb
  • 13. Kari Ellis

Group BStop-often flyers

5 pilots · ranks 614 · median 9 · middle half 712

  • LowDistance covered between climbs group median P10 in this field (0.9 kilometres) · usually costly
  • LowHow round and consistent the circles were group median P15 in this field (0.13 ratio) · usually a strength
  • LowHow much of the thermal the pilot climbed before leaving it group median P15 in this field (44 percent)
  • LowHow low the pilot gets between climbs group median P15 in this field (13 percent)
  • 6. Phillip Mansell
  • 7. Martin Joyce
  • 9. Jan Bennewitz (most typical of this group)
  • 12. James Thompson
  • 14. Zane Priebbenow

14 pilots on 20 behavioural metrics formed 2 groups.

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.

k was searched from 2 to 4. The mean silhouette is 0.18 — 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 (0.30)

best: could be chance (0.26)

best: could be chance (0.45)

#PilotGlideSpdGlideL/DSpeedToFlyWide%Dolphin%
1Geoff Wong35.1 (24 glides, 98 min gliding)1.07 (3 legs compared)0.5 (23 glide→climb pairs)41 (3 legs completed)8 (524 of 6550 m gained outside thermals)
2Gareth Carter41.7 (24 glides, 71 min gliding)1.18 (3 legs compared)-0.9 (23 glide→climb pairs)16 (3 legs completed)9 (411 of 4688 m gained outside thermals)
3Richard Binstead41.6 (25 glides, 84 min gliding)0.96 (3 legs compared)-1.4 (24 glide→climb pairs)47 (3 legs completed)10 (647 of 6805 m gained outside thermals)
4Rafael Esquillaro40.0 (19 glides, 67 min gliding)1.24 (2 legs compared)1.3 (18 glide→climb pairs)32 (2 legs completed)8 (400 of 4807 m gained outside thermals)
5Andy McMurray42.0 (24 glides, 105 min gliding)1.32 (2 legs compared)-1.4 (23 glide→climb pairs)71 (2 legs completed)7 (429 of 5952 m gained outside thermals)
6Phillip Mansell36.1 (28 glides, 88 min gliding)0.90 (2 legs compared)4.3 (27 glide→climb pairs)57 (2 legs completed)10 (704 of 6705 m gained outside thermals)
7Martin Joyce34.1 (21 glides, 79 min gliding)0.87 (2 legs compared)3.6 (20 glide→climb pairs)46 (2 legs completed)6 (334 of 5525 m gained outside thermals)
8Wally Arcidiacono39.3 (21 glides, 78 min gliding)1.11 (2 legs compared)-1.6 (20 glide→climb pairs)35 (2 legs completed)8 (411 of 5088 m gained outside thermals)
9Jan Bennewitz29.2 (23 glides, 79 min gliding)0.82 (2 legs compared)1.3 (22 glide→climb pairs)51 (2 legs completed)13 (636 of 4914 m gained outside thermals)
10Frank Adler40.3 (6 glides, 35 min gliding)1.05 (1 leg compared)-6.0 (5 glide→climb pairs)17 (1 leg completed)15 (266 of 1826 m gained outside thermals)
11Brian Webb41.0 (9 glides, 36 min gliding)0.95 (1 leg compared)-3.4 (8 glide→climb pairs)21 (1 leg completed)11 (173 of 1639 m gained outside thermals)
12James Thompson37.7 (14 glides, 54 min gliding)0.81 (1 leg compared)0.4 (13 glide→climb pairs)20 (1 leg completed)14 (396 of 2806 m gained outside thermals)
13Kari Ellis37.1 (7 glides, 26 min gliding)1.24 (1 leg compared)4.4 (6 glide→climb pairs)18 (1 leg completed)5 (61 of 1251 m gained outside thermals)
14Zane Priebbenow37.2 (11 glides, 33 min gliding)1.00 (1 leg compared)1.0 (10 glide→climb pairs)13 (1 leg completed)12 (220 of 1796 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 38.5 km/h · p90 41.6 km/h (14 pilots)

best: clear pattern (0.76)

#PilotFloor%LowSaveskm/climbSearch%
1Geoff Wong45 (11 descents, lowest -24% of band)2.0 (deepest save from -11% of band)1.4 (mean shared-climb pctile 44%)30
2Gareth Carter49 (11 descents, lowest -9% of band)1.0 (deepest save from 2% of band)1.6 (mean shared-climb pctile 52%)27
3Richard Binstead31 (15 descents, lowest -18% of band)2.0 (deepest save from -9% of band)1.2 (mean shared-climb pctile 54%)33
4Rafael Esquillaro47 (12 descents, lowest -4% of band)1.0 (deepest save from 7% of band)1.5 (mean shared-climb pctile 57%)26
5Andy McMurray32 (10 descents, lowest -28% of band)2.0 (deepest save from -23% of band)1.5 (mean shared-climb pctile 40%)38
6Phillip Mansell12 (14 descents, lowest -11% of band)2.0 (deepest save from -2% of band)0.9 (mean shared-climb pctile 49%)33
7Martin Joyce13 (16 descents, lowest -12% of band)3.0 (deepest save from -12% of band)1.2 (mean shared-climb pctile 47%)32
8Wally Arcidiacono44 (13 descents, lowest 5% of band)1.0 (deepest save from 5% of band)1.0 (mean shared-climb pctile 52%)22
9Jan Bennewitz13 (14 descents, lowest -28% of band)0.00.7 (mean shared-climb pctile 48%)47
10Frank Adler61 (5 descents, lowest 27% of band)0.01.9 (mean shared-climb pctile 51%)32
11Brian Webb52 (5 descents, lowest -31% of band)0.01.5 (mean shared-climb pctile 42%)33
12James Thompson47 (7 descents, lowest -33% of band)0.039
13Kari Ellis33 (5 descents, lowest 18% of band)0.020
14Zane Priebbenow32 (6 descents, lowest -32% of band)0.035

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 29/33/36% · glide 30/35/42% · search 27/32/35%

best: too few pilots (0.52)

#PilotInGaggle%Marked%LeaveWin%
1Geoff Wong4034 (12/35 climbs marked)100 (1W–0L (1 departure))
2Gareth Carter5634 (11/32 climbs marked)
3Richard Binstead3729 (11/38 climbs marked)50 (1W–1L (2 departures))
4Rafael Esquillaro5847 (14/30 climbs marked)0 (0W–1L (1 departure))
5Andy McMurray4233 (10/30 climbs marked)0 (0W–1L (1 departure))
6Phillip Mansell2922 (11/49 climbs marked)100 (1W–0L (1 departure))
7Martin Joyce206 (2/32 climbs marked)
8Wally Arcidiacono1131 (10/32 climbs marked)
9Jan Bennewitz2134 (14/41 climbs marked)
10Frank Adler5945 (5/11 climbs marked)
11Brian Webb5871 (10/14 climbs marked)0 (0W–1L (1 departure))
12James Thompson3252 (13/25 climbs marked)0 (0W–1L (1 departure))
13Kari Ellis4078 (7/9 climbs marked)
14Zane Priebbenow1720 (3/15 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.

25 gaggle episodes detected (peak size 11 pilots).

best: could be chance (0.30)

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 §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 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.