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Field analysis

Corryong Cup 2023 — which behaviours separated the field, task by task.

Analysis computed

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Something changed (a track, a penalty, or the task). The analysis below was computed before that change and may shift slightly.

Which behaviours went with better results, across tasks

A behaviour that keeps its sign and its size across every task tells you about flying. A behaviour that changes between tasks tells you about the weather on those days. Rank 1 is the best rank, so a behaviour where more is better shows a negative ρ, and its bar is left of centre. Read each row from left to right: the average of the behaviour over the tasks, whether it held from day to day, how it looks against the overall standings, and then each task.

BehaviourAcross tasksDay to dayAgainst comp standingsT1T2T3T4
Glide speed between climbs
same way each task
clear pattern

ρ -0.81 · 44 of 45 pilots

Gliding wide of the optimal course line
same way each task
clear pattern

ρ 0.60 · 42 of 45 pilots

Time spent flying with a gaggle
same way each task
clear pattern

ρ -0.74 · 45 of 45 pilots

Share of race time spent hunting for the next climb
same way each task
clear pattern

ρ 0.71 · 45 of 45 pilots

Share of lift turned in that was kept as a climb
same way each task
clear pattern

ρ -0.65 · 43 of 45 pilots

Distance covered between climbs
same way each task
clear pattern

ρ -0.61 · 41 of 45 pilots

How long after the gate opened the pilot started
same way each task
clear pattern

ρ 0.84 · 45 of 45 pilots

How much of the thermal the pilot climbed before leaving it
same way each task
clear pattern

ρ -0.68 · 44 of 45 pilots

How often leaving the gaggle paid off
same way each task
could be chance

ρ -0.12 · 34 of 45 pilots

Glide L/D against the field median
same way each task
some pattern

ρ -0.43 · 42 of 45 pilots

Climbs joined on another pilot's marker
same way each task
clear pattern

ρ -0.53 · 42 of 45 pilots

How low the pilot gets between climbs
same way each task
clear pattern

ρ -0.60 · 42 of 45 pilots

Share of the height gain made outside thermals
same way each task
some pattern

ρ 0.41 · 42 of 45 pilots

Arriving at ESS with height to spare
same way each task
could be chance

ρ 0.12 · 32 of 45 pilots

Share of the flight spent in air that wasn’t sinking
same way each task
could be chance

ρ 0.22 · 45 of 45 pilots

Climb rate at thermal exit
one clear task only
could be chance

ρ -0.26 · 45 of 45 pilots

Climbing faster than the pilots sharing the thermal
same way each task
could be chance

ρ -0.25 · 45 of 45 pilots

Low saves dug out from the bottom of the band
no clear task
could be chance

ρ 0.10 · 45 of 45 pilots

Gliding faster when the next climb is stronger
no clear task
could be chance

ρ 0.06 · 42 of 45 pilots

How round and consistent the circles were
no clear task
could be chance

ρ -0.04 · 42 of 45 pilots

Time to core thermals
no clear task
could be chance

ρ -0.05 · 45 of 45 pilots

Across tasks is the average of the coefficients of each task, weighted by n, with the signs kept. It is also the order of the table. A behaviour that pulled the same way every day comes first, because days that pull opposite ways cancel each other there. Day to day reads only the tasks whose coefficient cleared its own noise floor, which are the solid bars. A hollow bar is a day whose coefficient can be chance. A behaviour that depends on the day is a finding, not a fault. Against comp standings is a separate reading. It takes the average of each pilot for that behaviour over the whole competition, and correlates it against their overall place. The verdict and the pilot count belong to that reading.

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.

3 more metrics describe the day and not a pilot, for example the wind and the strength of the climbs. They have no value for each pilot to correlate, so they have no row here. They are in the glossary below, and on the analysis of each task.

Consistency map

The same table as a picture. It plots how much each behaviour separated the field on each day (across) against how consistently that behaviour pulled one way (up).

A dot on the diagonal separates the field the same way in every task. A dot far below the diagonal is strong on each day, but changes direction, so the payoff depended on the day. The Across tasks column of the table gives the exact value of the up axis.

Outcome checks

These are not behaviours. They measure the result itself, so they always follow the places. They are here as a check on the analysis. A weak pattern means that something is wrong in the numbers, and not in the flying of any pilot.

OutcomeAcross tasksDay to dayAgainst comp standingsT1T2T3T4
Race time behind the leader at ESS
same way each task
clear pattern

ρ 0.74 · 32 of 45 pilots

Race time lost against the fastest pilots, leg by leg
same way each task
some pattern

ρ 0.49 · 42 of 45 pilots

Standings behind these figures

#PilotTasksPoints
1Scott Barrett43703
2Rohan Holtkamp43420
3Olav Opsanger43413
4Rohan Taylor43382
5Steve Docherty43120
6Jon Durand42851
7Paul Bissett-Amess42660
8Corinna Schwiegershausen42417
9Hughbert Alexander42413
10Peter Burkitt42410
11Guy Hubbard42401
12Adam Stevens32187
13Stuart Cathcart42183
14Steven Crosby32171
15Neale Halsall42156
16James Atkinson42040
17Steve Blenkinsop31955
18Richard Martin41931
19Peter Adriaans41903
20Ward Gunn41756
21James Wynd41683
22Jay Kubeil41677
23Mitch Butler41460
24Neil Hooke41420
25Adrian Connor41351
26Sam Prest31279
27Andrew Sutton41131
28Peter Tolhurst41057
29Vic Hare41052
30Troy Horton3984
31John Harriott3883
32Andrew Taylor3807
33Peter Garrone4736
34Dustan Hansen4535
35Jason Lannstrom2467
36Jason Carman4466
37Magnus Ronningen3448
38Mark Jeffree3437
39Dean Bayly2426
40David Jackson2269
41Randall Clotworthy1228
42Alexander Kot1164
43Ted Sadowski192
44Donny Gardner186
45Richard Hughes169

Metric glossary

How GlideComp measures every metric named above. These are the current method descriptions of the engine. The report of each task carries the same text beside its numbers.

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.