SRV Melbourne Layout GP (3xDRS)

23 Jan 22 21:55 CET
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Overview Practice
Open in Simresults Download as JSON L/S = Overall Best Lap/Sector L/S = Driver's Best Lap/Sector
# Name Team Car Best Practice Lap Average Lap Laps
1 Stiftung Plankentest II STM BMW M4 2022 01:45.394
Tyre: M
01:51.822 50 laps / 6 cuts
2 Stiftung Plankentest I STM Audi RS5 2022 01:45.972
Tyre: M
01:46.896 15 laps / 3 cuts
3 Horizont Personalmanagement Racing STM Audi RS5 2022 01:46.986
Tyre: S
02:11.354 28 laps / 4 cuts
4 SRV Jägermeister eSport II STM Audi RS5 2022 01:47.113
Tyre: S
02:29.674 35 laps / 8 cuts
5 HabKeins STM BMW M4 2022 01:47.508
Tyre: M
02:30.472 47 laps / 6 cuts
6 CRM Motorsport STM Mercedes C63 2022 01:47.665
Tyre: S
03:38.930 17 laps / 5 cuts
7 HabKeins STM BMW M4 2022 01:48.951
Tyre: M
02:43.959 26 laps / 8 cuts
8 Horizont Personalmanagement Racing STM BMW M4 2022 01:49.678
Tyre: S
02:50.734 44 laps / 13 cuts
9 Micro-Machines Sim Racing I STM Mercedes C63 2022 01:51.394
Tyre: S
01:53.090 17 laps / 5 cuts
10 Bayern Racing STM Mercedes C63 2022 01:55.354
Tyre: M
02:46.273 3 laps / 1 cuts
11 Bayern Racing STM Mercedes C63 2022 01:56.652
Tyre: S
02:02.290 29 laps / 11 cuts
12 HabAuchKeins STM BMW M4 2022 02:30.433
Tyre: S
02:30.433 3 laps / 2 cuts
# Driver Other Driver Type Impact Speed (Km/h) Relative Position World Position Time Show on Map
1 Collision with environment 16.1 X: -1.0 Y: -0.3 Z: 1.8 X: -405.9 Y: 3.2 Z: 8.7 16:57:21 (CET)
2 Collision with environment 95.3 X: 0.7 Y: -0.3 Z: 2.2 X: -465.5 Y: 2.9 Z: -20.9 16:57:26 (CET)
3 Collision with environment 33.7 X: -0.7 Y: -0.3 Z: 2.3 X: -345.5 Y: 2.9 Z: 140.5 17:16:50 (CET)
4 Collision with environment 58.5 X: -0.7 Y: -0.3 Z: 2.3 X: -180.3 Y: 3.1 Z: -829.8 17:32:45 (CET)
5 Collision with environment 42.6 X: 1.0 Y: -0.1 Z: 1.7 X: -409.3 Y: 2.9 Z: 30.8 18:00:26 (CET)
6 Collision with environment 20.2 X: 1.0 Y: -0.3 Z: 1.8 X: 160.0 Y: 2.8 Z: 737.4 18:06:21 (CET)
7 Collision with environment 7.4 X: -1.0 Y: -0.4 Z: 0.2 X: 28.2 Y: 3.2 Z: -283.1 18:12:24 (CET)
8 Collision with environment 7.5 X: -1.0 Y: -0.3 Z: 1.7 X: 32.4 Y: 3.4 Z: -308.7 18:15:21 (CET)
9 Collision with environment 8.3 X: -1.0 Y: -0.3 Z: 1.8 X: 31.6 Y: 3.4 Z: -304.3 18:17:11 (CET)
10 Collision with environment 146.6 X: -0.7 Y: -0.3 Z: 2.3 X: -475.5 Y: 2.0 Z: 114.9 18:18:06 (CET)
11 Collision with environment 24.9 X: 0.9 Y: -0.1 Z: -1.4 X: 127.2 Y: 2.9 Z: 706.3 18:39:44 (CET)
12 Collision with environment 62.4 X: -0.9 Y: -0.3 Z: 2.2 X: -349.8 Y: 2.8 Z: 112.5 18:43:51 (CET)
13 Collision with environment 10.6 X: 0.9 Y: -0.4 Z: 2.1 X: -530.3 Y: 3.8 Z: -739.9 18:48:09 (CET)
14 Collision with environment 32.1 X: -0.9 Y: -0.4 Z: 2.2 X: 61.0 Y: 3.8 Z: -391.2 18:54:24 (CET)
15 Collision with environment 9.6 X: 0.9 Y: -0.4 Z: 2.2 X: -83.4 Y: 3.4 Z: -826.9 18:57:49 (CET)
16 Collision with environment 9.9 X: -0.9 Y: -0.4 Z: 2.2 X: 64.4 Y: 3.8 Z: -396.1 19:08:25 (CET)
17 Collision with environment 66.1 X: -0.9 Y: -0.4 Z: 2.2 X: -152.0 Y: 3.2 Z: -817.6 19:11:56 (CET)
18 Collision with environment 9.8 X: 1.0 Y: -0.3 Z: 1.8 X: 37.1 Y: 2.9 Z: -234.4 19:11:59 (CET)
19 Collision with environment 16.4 X: -0.7 Y: -0.4 Z: 2.3 X: 15.5 Y: 3.2 Z: -73.5 19:12:09 (CET)
20 Collision with environment 18.6 X: 0.9 Y: -0.4 Z: 2.2 X: -52.7 Y: 3.2 Z: 504.4 19:12:24 (CET)
21 Collision with environment 1.8 X: -1.0 Y: -0.4 Z: 1.8 X: 29.6 Y: 3.2 Z: -291.9 19:13:39 (CET)
22 Collision with environment 43.1 X: 0.9 Y: -0.4 Z: 2.2 X: 296.3 Y: 2.9 Z: 745.5 19:16:41 (CET)
23 Collision with environment 8.8 X: -1.0 Y: -0.4 Z: 1.8 X: 38.0 Y: 3.4 Z: -339.7 19:19:39 (CET)
24 Collision with environment 12.4 X: 0.9 Y: -0.4 Z: 2.2 X: -605.7 Y: 2.9 Z: -514.7 19:21:09 (CET)
25 Collision with environment 25.8 X: 0.9 Y: -0.4 Z: 2.2 X: -46.0 Y: 3.2 Z: 510.8 19:23:09 (CET)
26 Collision with environment 25.9 X: 0.9 Y: -0.4 Z: -1.9 X: -51.0 Y: 3.2 Z: 506.1 19:24:19 (CET)
27 Collision with environment 28.6 X: -0.9 Y: -0.4 Z: 2.2 X: 333.0 Y: 2.8 Z: 633.9 19:25:26 (CET)
28 Collision with environment 12.3 X: -0.9 Y: -0.4 Z: 2.2 X: -347.7 Y: 2.8 Z: 129.9 19:26:11 (CET)
29 Collision with environment 29.7 X: -0.9 Y: -0.4 Z: -1.9 X: 662.4 Y: 3.2 Z: 807.3 19:29:36 (CET)
30 Collision with environment 42.1 X: -0.0 Y: -0.4 Z: 2.4 X: -648.4 Y: 2.9 Z: -414.6 19:30:26 (CET)
31 Collision with environment 11.6 X: -0.7 Y: -0.4 Z: 2.3 X: -348.0 Y: 2.8 Z: 128.3 19:31:36 (CET)
32 Collision with environment 16.4 X: -0.9 Y: -0.4 Z: 2.2 X: -348.2 Y: 2.7 Z: 126.8 19:31:46 (CET)
33 Collision with environment 39.4 X: -0.9 Y: -0.4 Z: 2.2 X: 673.5 Y: 3.3 Z: 802.6 19:32:36 (CET)
34 Collision with environment 17.0 X: 1.0 Y: -0.4 Z: 1.8 X: -523.5 Y: 3.7 Z: -743.9 19:32:36 (CET)
35 Collision with environment 88.3 X: -0.7 Y: -0.4 Z: 2.3 X: -348.7 Y: 2.7 Z: 122.3 19:34:01 (CET)
36 Collision with environment 31.2 X: -0.9 Y: -0.4 Z: 2.2 X: -653.8 Y: 2.9 Z: -412.7 19:37:09 (CET)
37 Collision with environment 18.8 X: 0.9 Y: -0.4 Z: 2.2 X: -43.8 Y: 3.2 Z: 513.0 19:37:34 (CET)
38 Collision with environment 47.7 X: -0.7 Y: -0.4 Z: 2.3 X: 661.4 Y: 3.2 Z: 807.7 19:39:36 (CET)
39 Collision with environment 15.1 X: 0.8 Y: -0.0 Z: -2.4 X: 650.1 Y: 3.5 Z: 810.8 19:39:41 (CET)
40 Collision with environment 103.5 X: -0.7 Y: -0.4 Z: 2.2 X: 126.7 Y: 2.6 Z: 680.3 19:40:01 (CET)
41 Collision with environment 7.1 X: -1.0 Y: -0.4 Z: 1.8 X: 100.8 Y: 2.7 Z: 655.5 19:40:06 (CET)
42 Collision with environment 3.2 X: -1.0 Y: -0.4 Z: 1.8 X: 173.4 Y: 2.4 Z: 725.0 19:40:26 (CET)
43 Collision with environment 4.0 X: -1.0 Y: -0.4 Z: 1.8 X: 209.2 Y: 3.4 Z: 200.6 19:52:26 (CET)
44 Collision with environment 9.0 X: -0.9 Y: -0.4 Z: 2.2 X: -347.9 Y: 2.8 Z: 128.6 19:53:24 (CET)
45 Collision with environment 92.1 X: -0.3 Y: -0.4 Z: 2.3 X: 126.7 Y: 2.6 Z: 680.3 19:57:09 (CET)
46 Collision with environment 30.8 X: -0.7 Y: -0.4 Z: 2.3 X: -174.8 Y: 3.1 Z: -827.4 19:57:31 (CET)
47 Collision with environment 11.5 X: -0.9 Y: -0.4 Z: -1.9 X: -513.5 Y: 3.1 Z: -89.7 19:58:52 (CET)
48 Collision with environment 3.3 X: -1.0 Y: -0.4 Z: 1.8 X: -261.5 Y: 1.7 Z: 303.6 19:59:57 (CET)
49 Collision with environment 28.5 X: 0.4 Y: -0.4 Z: 2.3 X: 60.7 Y: 2.6 Z: -321.8 20:03:02 (CET)
50 Collision with environment 26.7 X: -0.7 Y: -0.4 Z: 2.3 X: -216.2 Y: 2.7 Z: -853.2 20:08:37 (CET)
51 Collision with environment 39.8 X: -0.9 Y: -0.4 Z: 2.2 X: 631.4 Y: 3.1 Z: 819.4 20:09:46 (CET)
52 Collision with environment 31.0 X: -0.9 Y: -0.4 Z: 2.2 X: 610.5 Y: 3.0 Z: 829.4 20:10:04 (CET)
53 Collision with environment 33.3 X: -0.9 Y: -0.4 Z: 2.2 X: -349.2 Y: 2.7 Z: 118.8 20:14:30 (CET)
54 Collision with environment 8.6 X: 1.0 Y: -0.4 Z: -1.0 X: -605.5 Y: 3.2 Z: -536.9 20:15:45 (CET)
55 Collision with environment 5.7 X: -1.0 Y: -0.4 Z: 1.8 X: 209.7 Y: 3.5 Z: 201.0 20:17:26 (CET)
56 Collision with environment 65.7 X: -0.9 Y: -0.4 Z: 2.2 X: 126.6 Y: 2.6 Z: 680.2 20:20:40 (CET)
57 Collision with environment 19.0 X: 0.9 Y: -0.4 Z: 2.2 X: -49.5 Y: 3.2 Z: 507.5 20:23:18 (CET)
58 Collision with car 40.1 X: 0.9 Y: -0.4 Z: 2.2 X: 621.4 Y: 3.2 Z: 834.2 20:36:36 (CET)
59 Collision with environment 46.2 X: -0.9 Y: 0.3 Z: 1.6 X: 596.4 Y: 3.7 Z: 836.0 20:36:36 (CET)
60 Collision with car 43.2 X: -1.0 Y: -0.4 Z: 0.4 X: 621.1 Y: 3.2 Z: 833.9 20:36:39 (CET)
61 Collision with environment 43.0 X: 0.9 Y: -0.4 Z: -1.9 X: 554.8 Y: 3.0 Z: 869.4 20:36:39 (CET)
62 Collision with car 16.1 X: 0.9 Y: -0.4 Z: 2.0 X: 531.7 Y: 2.9 Z: 873.3 20:36:41 (CET)
63 Collision with environment 94.6 X: 0.3 Y: -0.4 Z: 2.3 X: -606.1 Y: 3.3 Z: -548.3 20:42:59 (CET)
64 Collision with environment 13.8 X: 0.9 Y: -0.4 Z: -1.9 X: -606.5 Y: 3.4 Z: -556.4 20:43:04 (CET)
65 Collision with environment 26.4 X: -0.7 Y: -0.4 Z: 2.3 X: 58.8 Y: 3.7 Z: -388.1 20:43:26 (CET)
66 Collision with environment 24.5 X: -0.9 Y: -0.3 Z: 2.2 X: -636.8 Y: 2.9 Z: -418.5 20:46:02 (CET)
67 Collision with environment 87.3 X: 0.9 Y: -0.3 Z: 2.1 X: -530.6 Y: 3.9 Z: -739.8 20:50:28 (CET)
68 Collision with car 3.3 X: 1.0 Y: -0.4 Z: 1.8 X: 30.9 Y: 3.1 Z: -277.1 20:51:00 (CET)
69 Collision with car 4.6 X: -1.0 Y: -0.4 Z: 0.7 X: 31.1 Y: 3.1 Z: -278.4 20:51:02 (CET)
70 Collision with environment 12.4 X: 1.0 Y: -0.3 Z: 1.8 X: 152.2 Y: 2.8 Z: 729.4 20:51:17 (CET)
71 Collision with environment 27.4 X: 0.7 Y: -0.4 Z: 2.3 X: 535.7 Y: 3.5 Z: 322.8 20:51:30 (CET)
72 Collision with environment 41.5 X: 0.9 Y: -0.3 Z: 2.1 X: -495.9 Y: 3.1 Z: -48.5 20:51:37 (CET)
73 Collision with environment 6.0 X: -1.0 Y: -0.3 Z: 1.8 X: 31.3 Y: 3.3 Z: -302.5 20:51:40 (CET)
74 Collision with environment 5.8 X: 0.9 Y: -0.3 Z: -1.9 X: -513.6 Y: 3.1 Z: -64.7 20:51:42 (CET)
75 Collision with environment 6.5 X: -0.9 Y: -0.3 Z: -1.9 X: 32.9 Y: 3.4 Z: -312.1 20:53:25 (CET)
76 Collision with environment 39.9 X: 1.0 Y: -0.4 Z: 1.8 X: -606.4 Y: 3.3 Z: -554.1 20:53:33 (CET)
77 Collision with environment 15.0 X: -0.9 Y: -0.4 Z: -1.9 X: -395.8 Y: 3.0 Z: 18.2 20:53:54 (CET)
78 Collision with environment 19.1 X: -0.9 Y: -0.4 Z: 2.2 X: -650.7 Y: 2.9 Z: -413.8 20:57:18 (CET)
79 Collision with environment 34.2 X: -0.7 Y: -0.4 Z: 2.3 X: -199.2 Y: 2.8 Z: -840.4 21:00:15 (CET)
80 Collision with environment 14.9 X: 1.0 Y: -0.3 Z: 1.8 X: 154.9 Y: 2.7 Z: 732.1 21:01:37 (CET)
81 Collision with environment 8.2 X: -0.9 Y: -0.4 Z: 2.2 X: -668.0 Y: 2.8 Z: -408.0 21:01:48 (CET)
82 Collision with environment 6.5 X: -0.9 Y: -0.4 Z: 2.2 X: -662.8 Y: 2.9 Z: -409.7 21:01:53 (CET)
83 Collision with environment 56.5 X: 0.8 Y: -0.2 Z: 2.1 X: -605.0 Y: 3.2 Z: -521.3 21:03:53 (CET)
84 Collision with environment 28.0 X: -0.9 Y: -0.4 Z: 2.2 X: -179.1 Y: 3.0 Z: -829.3 21:06:08 (CET)
85 Collision with environment 4.3 X: -1.0 Y: -0.4 Z: -1.0 X: -172.4 Y: 3.1 Z: -826.3 21:06:13 (CET)
86 Collision with environment 26.3 X: -0.9 Y: -0.4 Z: 2.2 X: 48.2 Y: 3.5 Z: -370.3 21:12:09 (CET)
87 Collision with environment 13.1 X: 0.9 Y: -0.4 Z: 2.2 X: -53.9 Y: 3.2 Z: 503.2 21:14:34 (CET)
88 Collision with environment 17.7 X: 0.7 Y: -0.4 Z: 2.3 X: 67.2 Y: 3.8 Z: -400.0 21:18:32 (CET)
89 Collision with environment 3.6 X: -1.0 Y: -0.4 Z: 1.8 X: 29.2 Y: 3.2 Z: -289.2 21:20:32 (CET)
90 Collision with environment 55.0 X: -0.9 Y: -0.4 Z: 2.2 X: -145.6 Y: 3.1 Z: -816.5 21:22:59 (CET)
91 Collision with environment 90.5 X: -0.8 Y: -0.0 Z: 1.9 X: 176.0 Y: 3.6 Z: 173.0 21:24:24 (CET)
92 Collision with environment 110.9 X: -0.8 Y: -0.4 Z: 2.2 X: 299.4 Y: 3.2 Z: 267.8 21:24:29 (CET)
93 Collision with environment 41.8 X: 0.9 Y: -0.4 Z: 2.2 X: -49.9 Y: 3.5 Z: -818.5 21:24:54 (CET)
94 Collision with environment 52.4 X: 0.7 Y: -0.4 Z: 2.3 X: 303.2 Y: 3.0 Z: 741.1 21:30:09 (CET)
95 Collision with environment 102.7 X: -0.7 Y: -0.4 Z: 2.3 X: -360.1 Y: 3.2 Z: 57.4 21:34:24 (CET)
96 Collision with environment 11.0 X: -0.9 Y: -0.4 Z: -1.9 X: 28.9 Y: 3.2 Z: -287.7 21:43:45 (CET)
Car Env Rel
SRV Melbourne Layout GP (3xDRS) SRV Melbourne Layout GP (3xDRS) collisions

There were no penalties in this session.

1st Pascal Hein in STM BMW M4 2022
Best: 01:45.394, Potential: 01:45.049
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:13.443 01:59.175 00:27.621 00:46.647 1 M 0
2 01:45.763 00:33.497 00:26.438 00:45.828
S
S
0 M 0
3 01:45.989 00:33.504 00:26.388 00:46.097 0 M 0
4 01:46.301 00:33.689 00:26.406 00:46.206 0 M 0
5 01:46.094
C
00:33.402 00:26.275 00:46.417 1 M 0
6 03:43.378 02:28.588 00:26.946 00:47.844 0 M 0
7 01:46.124 00:33.562 00:26.483 00:46.079 0 M 0
8 02:10.061 00:33.663 00:29.362 01:07.036 1 M 5000
9 01:52.763 00:39.418 00:26.919 00:46.426 0 M 0
10 01:45.806 00:33.663 00:26.154 00:45.989 0 M 0
11 01:45.861 00:33.361 00:26.433 00:46.067 0 M 0
12 03:07.713 01:53.953 00:27.279 00:46.481 0 M 0
13 01:45.777 00:33.484 00:26.356 00:45.937 0 M 0
14 01:46.186 00:33.592 00:26.257 00:46.337 0 M 0
15 01:46.160 00:33.823 00:26.190 00:46.147 0 M 0
16 01:45.752 00:33.465 00:26.379 00:45.908 0 M 0
17 01:45.555 00:33.338 00:26.330 00:45.887 0 M 0
18 11:04.627 09:51.218 00:26.974 00:46.435 0 M 0
19 01:46.997 00:34.255 00:26.523 00:46.219 0 M 0
20 04:02.192 02:48.923 00:26.901 00:46.368 0 M 0
21 01:45.820 00:33.402 00:26.311 00:46.107 0 M 0
22 01:45.598 00:33.445 00:26.240 00:45.913 0 M 0
23 01:54.283 00:38.364 00:27.341 00:48.578 0 M 0
24 05:40.966 04:25.699 00:28.427 00:46.840 0 M 0
25 01:46.269 00:33.643 00:26.266 00:46.360 0 M 0
26 01:45.768
C
00:33.354 00:26.230 00:46.184 1 M 0
27 02:23.927 01:08.422 00:28.787 00:46.718 0 M 0
28 01:47.687 00:33.672 00:26.347 00:47.668 0 M 0
29 01:46.077 00:33.663 00:26.361 00:46.053 0 M 0
30 01:45.714 00:33.452 00:26.236 00:46.026 0 M 0
31 01:45.394
L
L
00:33.466 00:26.087 00:45.841 0 M 0
32 04:47.335 03:33.405 00:27.081 00:46.849 0 M 0
33 01:46.295
C
00:33.243 00:26.131 00:46.921 1 M 0
34 04:21.070 03:08.022 00:26.932 00:46.116 0 M 0
35 01:47.421 00:33.238
S
S
00:25.983
S
S
00:48.200 0 M 0
36 02:37.775 01:16.911 00:30.321 00:50.543 1 M 0
37 06:02.937 04:09.114 00:59.076 00:54.747 0 M 0
38 02:21.444 00:45.967 00:26.663 01:08.814 0 M 0
39 01:53.746 00:33.889 00:26.554 00:53.303 0 M 0
40 01:54.863 00:41.505 00:26.811 00:46.547 0 M 0
41 02:01.367 00:33.501 00:26.635 01:01.231 0 M 0
42 01:46.922 00:33.834 00:26.581 00:46.507 0 M 0
43 01:46.819 00:33.622 00:26.618 00:46.579 0 M 0
44 01:46.746 00:33.823 00:26.528 00:46.395 0 M 0
45 01:46.969 00:33.705 00:26.693 00:46.571 0 M 0
46 01:48.113 00:33.985 00:26.608 00:47.520 0 M 0
47 01:47.053 00:33.784 00:26.582 00:46.687 0 M 0
48 01:47.636 00:34.080 00:26.693 00:46.863 0 M 0
49 01:47.395 00:33.856 00:26.573 00:46.966 0 M 0
50 01:47.421 00:33.927 00:26.594 00:46.900 0 M 0
2nd Tim Quoos in STM Audi RS5 2022
Best: 01:45.972, Potential: 01:45.918
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 04:18.359 03:04.641 00:26.991 00:46.727 1 M 0
2 01:46.742
C
00:33.820 00:26.694 00:46.228 1 M 0
3 01:47.138 00:33.671 00:26.497 00:46.970 0 M 0
4 01:46.553 00:33.788 00:26.388 00:46.377 0 M 0
5 01:46.194 00:33.627 00:26.423 00:46.144
S
0 M 0
6 01:46.721 00:33.767 00:26.460 00:46.494 0 M 0
7 01:46.747 00:34.247 00:26.321 00:46.179 0 M 0
8 01:45.972
L
00:33.477
S
00:26.297
S
00:46.198 0 M 0
9 01:47.090 00:33.822 00:26.613 00:46.655 0 M 0
10 01:47.201 00:33.982 00:26.474 00:46.745 0 M 0
11 01:46.770 00:33.851 00:26.452 00:46.467 0 M 0
12 01:46.937 00:33.722 00:26.407 00:46.808 0 M 0
13 01:47.310 00:33.960 00:26.401 00:46.949 1 M 0
14 01:47.640 00:33.939 00:26.613 00:47.088 0 M 0
15 01:47.793 00:34.150 00:26.905 00:46.738 0 M 0
3rd Thomas Kneissler in STM Audi RS5 2022
Best: 01:46.986, Potential: 01:46.865
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:33.283 02:16.562 00:28.612 00:48.109 1 S 0
2 01:47.925 00:34.403 00:26.640 00:46.882 0 S 0
3 01:48.216 00:34.578 00:26.793 00:46.845 0 S 0
4 01:48.382 00:34.038 00:26.820 00:47.524 0 S 0
5 03:34.377 02:17.890 00:28.363 00:48.124 0 S 0
6 01:50.897
C
00:35.846 00:27.838 00:47.213 1 S 0
7 01:48.052 00:34.153 00:26.919 00:46.980 0 S 0
8 05:40.674 04:24.984 00:27.989 00:47.701 0 S 0
9 01:49.079 00:34.208 00:27.558 00:47.313 0 S 0
10 01:47.382 00:33.960 00:26.729 00:46.693 0 S 0
11 22:27.093 21:11.105 00:28.323 00:47.665 0 S 0
12 01:47.883 00:33.812
S
00:26.704 00:47.367 0 S 0
13 02:04.393 00:34.308 00:30.266 00:59.819 0 S 0
14 04:27.233 03:09.730 00:28.737 00:48.766 0 S 0
15 01:48.632 00:34.805 00:26.767 00:47.060 0 S 0
16 01:52.561 00:35.372 00:29.503 00:47.686 0 S 0
17 06:01.459 04:42.110 00:30.474 00:48.875 0 S 0
18 01:48.077 00:34.043 00:26.838 00:47.196 0 S 0
19 01:49.060
C
00:34.076 00:26.762 00:48.222 1 S 0
20 01:47.880 00:33.913 00:27.198 00:46.769 0 S 0
21 09:40.913 08:21.268 00:30.272 00:49.373 0 S 0
22 01:47.355 00:33.870 00:26.855 00:46.630 0 S 0
23 01:47.415 00:33.961 00:26.780 00:46.674 0 S 0
24 10:40.232 09:22.122 00:29.403 00:48.707 0 S 0
25 01:46.986
L
00:33.933 00:26.599
S
00:46.454
S
0 S 0
26 05:48.821 04:24.550 00:33.628 00:50.643 0 S 0
27 01:48.102 00:34.374 00:26.837 00:46.891 0 S 0
28 01:56.378
C
00:33.704 00:33.516 00:49.158 1 S 0
4th Michael Weimer in STM Audi RS5 2022
Best: 01:47.113, Potential: 01:46.769
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:01.423 01:46.673 00:27.703 00:47.047 1 S 0
2 02:59.025 01:44.838 00:27.130 00:47.057 0 S 0
3 01:47.388 00:33.821 00:27.054 00:46.513
S
0 S 0
4 01:47.901
C
00:34.195 00:26.960 00:46.746 1 S 0
5 01:47.230 00:34.042 00:26.626 00:46.562 0 S 0
6 04:49.778 03:36.042 00:26.793 00:46.943 0 S 0
7 03:40.458 02:25.938 00:27.063 00:47.457 0 S 0
8 01:47.113
L
00:33.691 00:26.784 00:46.638 0 S 0
9 01:47.151 00:33.720 00:26.603
S
00:46.828 0 S 0
10 05:40.647 04:23.975 00:28.562 00:48.110 1 M 0
11 10:32.803 00:34.123 09:09.243 00:49.437 0 M 0
12 03:30.839 02:08.971 00:29.340 00:52.528 0 M 0
13 01:48.813 00:34.315 00:27.234 00:47.264 0 M 0
14 01:49.323 00:34.186 00:26.897 00:48.240 0 M 0
15 03:00.518 01:30.707 00:28.697 01:01.114 1 M 0
16 03:17.150 01:58.230 00:28.548 00:50.372 1 M 0
17 01:50.324 00:34.567 00:27.495 00:48.262 0 M 0
18 05:01.061 03:45.682 00:27.418 00:47.961 0 M 0
19 01:51.292 00:33.653
S
00:26.811 00:50.828 0 M 0
20 03:53.438 01:34.631 00:28.899 01:49.908 1 M 0
21 01:57.300 00:35.759 00:32.292 00:49.249 0 M 0
22 01:50.767 00:34.960 00:27.531 00:48.276 0 M 0
23 01:51.263 00:34.921 00:27.266 00:49.076 0 M 0
24 04:58.199 03:42.816 00:27.594 00:47.789 0 M 0
25 01:50.766 00:34.590 00:27.868 00:48.308 0 M 0
26 04:00.830 02:45.829 00:28.022 00:46.979 0 M 0
27 01:48.907 00:34.324 00:27.022 00:47.561 0 M 0
28 03:03.083 01:45.148 00:27.486 00:50.449 0 M 0
29 01:48.610 00:34.292 00:27.261 00:47.057 0 M 0
30 01:48.433
C
00:33.922 00:27.027 00:47.484 1 M 0
31 01:48.361
C
00:34.034 00:26.767 00:47.560 1 M 0
32 01:48.190 00:34.057 00:27.162 00:46.971 0 M 0
33 03:26.853 02:09.358 00:28.039 00:49.456 0 M 0
34 01:47.401 00:33.786 00:26.981 00:46.634 0 M 0
35 09:15.611 07:59.989 00:27.810 00:47.812 0 S 0
5th Micha Schloz in STM BMW M4 2022
Best: 01:47.508, Potential: 01:47.508
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:25.862 02:06.226 00:29.317 00:50.319 1 M 0
2 09:06.271 07:47.022 00:28.709 00:50.540 0 M 0
3 01:58.387 00:35.096 00:33.921 00:49.370 0 M 0
4 01:51.174 00:35.002 00:27.526 00:48.646 0 M 0
5 01:50.474
C
00:34.893 00:27.373 00:48.208 1 M 0
6 01:50.072 00:34.585 00:27.427 00:48.060 0 M 0
7 11:19.516 08:48.600 00:29.087 02:01.829 0 M 0
8 01:51.223 00:35.151 00:27.738 00:48.334 0 M 0
9 01:51.273 00:34.993 00:27.653 00:48.627 0 M 0
10 01:51.428 00:35.090 00:27.761 00:48.577 0 M 0
11 04:15.539 02:57.005 00:29.611 00:48.923 0 M 0
12 02:08.720 00:52.950 00:27.742 00:48.028 0 M 0
13 09:20.748 08:02.695 00:28.157 00:49.896 0 M 0
14 01:49.300 00:34.343 00:27.369 00:47.588 0 M 0
15 01:48.406 00:34.106 00:26.937 00:47.363 0 M 0
16 01:54.072 00:34.061 00:32.031 00:47.980 0 M 0
17 01:48.369 00:34.199 00:26.834 00:47.336 0 M 0
18 01:49.980 00:34.731 00:27.441 00:47.808 0 M 0
19 04:19.092 03:03.028 00:28.174 00:47.890 0 M 0
20 01:50.357
C
00:34.164 00:28.331 00:47.862 1 M 0
21 01:47.508
L
00:33.870
S
00:26.774
S
00:46.864
S
0 M 0
22 01:49.066 00:34.056 00:27.126 00:47.884 0 M 0
23 01:48.158 00:34.084 00:26.784 00:47.290 0 M 0
24 06:05.493 04:48.889 00:28.305 00:48.299 0 M 0
25 01:50.600 00:34.767 00:27.260 00:48.573 0 M 0
26 01:50.361 00:34.373 00:27.567 00:48.421 0 M 0
27 04:09.925 02:52.790 00:28.522 00:48.613 0 M 0
28 03:59.104 02:43.022 00:27.977 00:48.105 0 M 0
29 01:52.092 00:36.608 00:27.433 00:48.051 0 M 0
30 01:53.435 00:34.073 00:27.054 00:52.308 0 M 0
31 05:06.799 03:49.908 00:28.489 00:48.402 0 M 0
32 05:31.440 04:15.380 00:27.802 00:48.258 0 M 0
33 01:48.594 00:34.177 00:26.959 00:47.458 0 M 0
34 05:42.954 04:25.009 00:28.841 00:49.104 0 M 0
35 01:50.402 00:34.416 00:27.301 00:48.685 0 M 0
36 01:48.484
C
00:34.023 00:27.031 00:47.430 1 M 0
37 01:48.307 00:34.358 00:26.848 00:47.101 0 M 0
38 03:54.105 02:35.949 00:28.628 00:49.528 0 M 0
39 01:49.376 00:34.083 00:27.256 00:48.037 0 M 0
40 01:52.098
C
00:34.221 00:29.465 00:48.412 1 M 0
41 01:52.216 00:34.415 00:27.284 00:50.517 0 M 0
42 05:27.867 04:10.277 00:28.364 00:49.226 0 M 0
43 02:01.131 00:34.056 00:38.691 00:48.384 0 M 0
44 03:21.428 02:03.754 00:28.841 00:48.833 0 M 0
45 01:50.468 00:34.634 00:27.563 00:48.271 0 M 0
46 01:49.524
C
00:35.031 00:26.927 00:47.566 1 M 0
47 03:46.471 02:30.524 00:27.959 00:47.988 0 M 0
6th Viktor Kaltschew in STM Mercedes C63 2022
Best: 01:47.665, Potential: 01:47.514
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 08:35.183 07:16.182 00:29.933 00:49.068 1 M 0
2 19:44.569 18:28.433 00:27.406 00:48.730 0 M 0
3 01:49.077 00:34.741 00:26.941 00:47.395 0 M 0
4 01:48.823 00:34.780 00:26.721 00:47.322 0 M 0
5 01:58.671
C
00:33.859 00:27.108 00:57.704 1 M 0
6 01:48.090 00:34.384 00:26.546
S
00:47.160 0 M 0
7 01:53.521 00:34.456 00:29.219 00:49.846 0 M 0
8 04:19.970 03:04.019 00:27.901 00:48.050 0 M 0
9 02:04.211 00:34.140 00:26.595 01:03.476 0 M 0
10 01:50.815
C
00:34.544 00:27.190 00:49.081 1 M 0
11 01:49.257
C
00:34.665 00:27.225 00:47.367 1 M 0
12 03:03.275 01:39.441 00:30.824 00:53.010 0 S 0
13 01:47.665
L
00:34.013 00:26.640 00:47.012
S
0 S 0
14 01:58.468
C
00:34.993 00:31.581 00:51.894 1 S 0
15 01:47.835 00:34.187 00:26.604 00:47.044 0 S 0
16 01:48.706 00:33.956
S
00:26.892 00:47.858 0 S 0
17 01:51.421 00:34.435 00:26.748 00:50.238 0 S 0
7th Michael Rasch in STM BMW M4 2022
Best: 01:48.951, Potential: 01:48.803
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 07:53.684 06:35.096 00:29.376 00:49.212 1 M 0
2 01:52.705 00:35.796 00:28.282 00:48.627 0 M 0
3 01:50.471 00:34.831 00:27.518 00:48.122 0 M 0
4 01:56.948
C
00:34.657 00:33.349 00:48.942 1 M 0
5 15:02.766 13:40.240 00:32.378 00:50.148 0 M 0
6 01:52.662 00:35.666 00:27.482 00:49.514 0 M 0
7 01:53.309
C
00:36.526 00:27.436 00:49.347 1 M 0
8 01:53.501 00:35.597 00:27.954 00:49.950 0 M 0
9 04:47.633 03:30.279 00:28.646 00:48.708 0 M 0
10 08:49.396 07:32.603 00:28.238 00:48.555 0 M 0
11 01:49.815
C
00:34.826 00:27.171 00:47.818 1 M 0
12 02:07.561 00:34.343 00:26.874 01:06.344 0 M 0
13 01:48.951
L
00:34.278
S
00:26.945 00:47.728 0 M 0
14 03:30.518 02:14.761 00:27.923 00:47.834 0 M 0
15 01:49.024 00:34.454 00:26.843
S
00:47.727 0 M 0
16 05:28.587 03:59.189 00:40.347 00:49.051 0 M 0
17 01:56.698
C
00:34.370 00:27.086 00:55.242 1 M 0
18 01:49.904 00:35.164 00:27.058 00:47.682
S
0 M 0
19 03:13.856 01:56.664 00:27.936 00:49.256 1 M 0
20 01:54.519 00:34.666 00:27.014 00:52.839 0 M 0
21 03:38.812 02:22.857 00:27.805 00:48.150 0 M 0
22 01:49.455 00:34.457 00:27.261 00:47.737 0 M 0
23 05:38.291 04:21.863 00:28.099 00:48.329 0 M 0
24 01:50.019
C
00:34.769 00:27.261 00:47.989 1 M 0
25 01:50.762 00:34.825 00:28.224 00:47.713 0 M 0
26 01:50.369
C
00:34.554 00:27.931 00:47.884 1 M 0
8th Daniel Amann in STM BMW M4 2022
Best: 01:49.678, Potential: 01:49.535
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 05:30.513 04:02.200 00:32.045 00:56.268 1 M 0
2 10:56.736 09:31.767 00:30.213 00:54.756 1 M 0
3 01:57.607 00:36.198 00:29.447 00:51.962 0 M 0
4 01:58.666 00:37.707 00:30.780 00:50.179 0 M 0
5 01:53.001 00:35.771 00:27.846 00:49.384 0 M 0
6 03:34.465 02:15.940 00:28.390 00:50.135 0 M 0
7 02:07.149 00:41.734 00:35.496 00:49.919 0 M 0
8 02:16.975
C
00:58.185 00:28.907 00:49.883 1 M 0
9 01:54.049 00:36.438 00:27.976 00:49.635 0 M 0
10 02:06.914
C
00:39.907 00:31.464 00:55.543 1 M 0
11 02:06.786 00:42.384 00:29.605 00:54.797 0 M 0
12 07:24.005 06:02.209 00:29.380 00:52.416 0 M 0
13 01:55.855 00:37.605 00:28.376 00:49.874 0 M 0
14 01:52.240
C
00:35.461 00:28.418 00:48.361 1 M 0
15 01:57.825 00:35.717 00:28.603 00:53.505 0 M 0
16 01:59.357
C
00:41.431 00:28.845 00:49.081 1 M 0
17 14:07.082 12:06.303 00:45.602 01:15.177 0 S 0
18 04:13.334 02:27.602 00:34.961 01:10.771 0 S 0
19 01:56.035
C
00:37.064 00:29.156 00:49.815 1 S 0
20 06:00.037 03:31.586 00:32.477 01:55.974 0 M 0
21 01:57.415 00:36.599 00:27.941 00:52.875 0 M 0
22 04:29.699 03:08.430 00:30.842 00:50.427 0 S 0
23 04:17.776 02:59.300 00:28.900 00:49.576 0 S 0
24 02:08.665
C
00:35.200 00:45.077 00:48.388 1 S 0
25 01:50.894 00:34.755 00:27.238 00:48.901 0 S 0
26 02:03.465
C
00:39.675 00:31.171 00:52.619 1 S 0
27 02:52.475 01:32.110 00:31.338 00:49.027 0 S 0
28 03:51.433 02:33.219 00:28.853 00:49.361 0 S 0
29 04:41.125 03:24.598 00:28.112 00:48.415 0 S 0
30 01:50.269 00:34.579
S
00:27.230 00:48.460 0 S 0
31 04:06.678 02:48.440 00:28.477 00:49.761 0 S 0
32 01:49.678
L
00:34.722 00:26.784
S
00:48.172
S
0 S 0
33 02:52.616 01:18.359 00:30.474 01:03.783 1 M 0
34 01:57.097 00:36.700 00:30.731 00:49.666 0 M 0
35 02:03.166 00:41.347 00:28.705 00:53.114 0 M 0
36 16:23.742 15:03.223 00:29.844 00:50.675 0 M 0
37 01:56.145
C
00:37.160 00:28.242 00:50.743 1 M 0
38 06:25.857 04:53.777 00:39.007 00:53.073 0 M 0
39 02:00.091
C
00:40.310 00:31.370 00:48.411 1 M 0
40 01:59.233 00:38.989 00:30.996 00:49.248 0 M 0
41 02:02.333
C
00:37.877 00:34.979 00:49.477 1 M 0
42 01:55.356 00:35.922 00:27.778 00:51.656 0 M 0
43 01:52.414 00:35.558 00:27.752 00:49.104 0 M 0
44 02:01.227 00:34.971 00:33.111 00:53.145 0 M 0
9th Klemens Kowall in STM Mercedes C63 2022
Best: 01:51.394, Potential: 01:50.693
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 04:54.666 03:35.268 00:29.209 00:50.189 1 S 0
2 01:53.134 00:36.225 00:27.958 00:48.951 1 S 0
3 01:53.684 00:35.668 00:28.652 00:49.364 0 S 0
4 01:52.993 00:35.836 00:28.215 00:48.942 0 S 0
5 01:51.394
L
00:34.962
S
00:27.670
S
00:48.762 0 S 0
6 01:51.453 00:35.069 00:28.323 00:48.061
S
0 S 0
7 01:52.068
C
00:35.266 00:27.787 00:49.015 1 S 0
8 06:00.395 04:41.335 00:29.142 00:49.918 0 S 0
9 01:54.374 00:35.584 00:28.359 00:50.431 0 S 0
10 01:57.462 00:35.687 00:28.782 00:52.993 1 S 0
11 01:52.837 00:36.017 00:28.229 00:48.591 0 S 0
12 01:54.355 00:35.074 00:29.840 00:49.441 0 S 0
13 01:53.486 00:36.320 00:27.950 00:49.216 0 S 0
14 01:54.563 00:36.209 00:28.035 00:50.319 0 S 0
15 01:51.769 00:35.517 00:27.818 00:48.434 0 S 0
16 01:52.731
C
00:35.393 00:28.728 00:48.610 1 S 0
17 08:50.869 07:31.890 00:28.975 00:50.004 0 S 0
10th Dieter Suessenguth in STM Mercedes C63 2022
Best: 01:55.354, Potential: 01:53.312
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:19.437 01:57.627 00:31.734 00:50.076 1 M 0
2 03:37.192 02:19.806 00:28.709 00:48.677
S
0 M 0
3 01:55.354
L
00:36.550
S
00:28.085
S
00:50.719 0 M 0
11th Herbert Aeckerle in STM Mercedes C63 2022
Best: 01:56.652, Potential: 01:55.559
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 04:03.460 02:30.944 00:34.182 00:58.334 1 S 0
2 03:00.158 01:24.615 00:37.367 00:58.176 1 S 0
3 02:20.951 00:40.363 00:36.072 01:04.516 0 S 0
4 02:14.620 00:45.461 00:33.539 00:55.620 0 S 0
5 02:05.380 00:40.442 00:30.443 00:54.495 0 S 0
6 01:59.048 00:37.878 00:29.160 00:52.010 0 S 0
7 02:08.388 00:39.643 00:31.185 00:57.560 0 S 0
8 01:59.178 00:37.674 00:30.240 00:51.264 0 S 0
9 02:01.558 00:38.060 00:29.476 00:54.022 0 S 0
10 02:05.079 00:40.596 00:31.022 00:53.461 0 S 0
11 07:24.763 05:56.406 00:34.465 00:53.892 1 S 0
12 01:58.180
C
00:38.233 00:29.196 00:50.751 1 S 0
13 01:57.374 00:37.553 00:29.363 00:50.458
S
0 S 0
14 01:56.652
L
00:36.435
S
00:29.101 00:51.116 0 S 0
15 01:57.697 00:37.124 00:29.291 00:51.282 0 S 0
16 01:57.870 00:37.518 00:28.944 00:51.408 0 S 0
17 01:58.242 00:37.494 00:29.690 00:51.058 0 S 0
18 01:58.359 00:37.241 00:29.872 00:51.246 0 S 0
19 01:56.293
C
00:36.454 00:28.831 00:51.008 1 S 0
20 03:07.386 00:36.901 00:30.173 02:00.312 1 S 0
21 02:15.152 00:49.522 00:32.414 00:53.216 1 S 0
22 02:00.139
C
00:36.875 00:30.195 00:53.069 1 S 0
23 01:58.599
C
00:38.706 00:28.881 00:51.012 1 S 0
24 02:41.286 01:14.256 00:31.941 00:55.089 1 S 0
25 01:59.141 00:38.150 00:28.666
S
00:52.325 0 S 0
26 01:57.457
C
00:36.979 00:28.422 00:52.056 1 S 0
27 02:02.586 00:40.218 00:30.217 00:52.151 0 S 0
28 01:58.885 00:37.817 00:28.944 00:52.124 0 S 0
29 02:00.223 00:37.382 00:29.102 00:53.739 0 S 0
12th Jens Bauer in STM BMW M4 2022
Best: 02:30.433, Potential: 02:30.433
Lap # Lap Time Sector 1 Sector 2 Sector 3 Cuts Tyre Ballast (Kg)
1 03:15.593 01:59.382 00:28.228 00:47.983 1 S 0
2 02:30.433
L
01:15.125
S
00:27.689
S
00:47.619
S
0 S 0
3 01:48.928
C
00:34.881 00:26.968 00:47.079 1 S 0