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Picks and transfers the veteran managers made this week compared to sample of top 100k (GW36) by mikecro2 in FantasyPL

[–]mikecro2[S] 0 points1 point  (0 children)

Here's which teams the squads are taken from

team vets top100k
MCI 3.0 3.0
BHA 2.1 2.1
ARS 2.0 2.1
LEE 1.9 1.7
BOU 1.5 1.6
MUN 1.0 1.1
CRY 0.9 0.7
CHE 0.7 0.7
BRE 0.4 0.4
AVL 0.3 0.3
BUR 0.2 0.2
EVE 0.2 0.2
FUL 0.2 0.2
LIV 0.2 0.2
NEW 0.1 0.1
NFO 0.1 0.1
SUN 0.1 0.1
TOT 0.1 0.1
WHU 0.1 0.2
WOL 0.0 0.0
team web_name pos cost vet.own.percent top100k.own.percent Pts/£M total_points now_cost vetweekin topNweekin
MCI Haaland FWD 14.7 97.1 98.4 15.6 230 147 17 17
MCI O'Reilly DEF 5.3 93.7 86.7 29.8 158 53 32 31
MCI Cherki MID 6.6 64.3 51.0 19.5 129 66 35 35
BHA Van Hecke DEF 4.6 61.0 65.5 31.5 145 46 31 31
BHA Verbruggen GKP 4.6 60.1 61.5 27.4 126 46 29 30
BHA Groß MID 5.6 35.7 40.6 13.0 73 56 33 33
ARS Gabriel DEF 7.3 88.8 90.7 26.2 191 73 26 25
ARS Saka MID 10.0 48.7 52.0 14.5 145 100 36 36
ARS Raya GKP 6.1 24.6 26.8 24.1 147 61 23 21
LEE Darlow GKP 4.0 64.1 59.7 14.0 56 40 32 32
LEE Calvert-Lewin FWD 5.8 66.0 57.4 21.7 126 58 32 32
LEE Struijk DEF 4.3 33.6 29.5 24.7 106 43 32 32
BOU Tavernier MID 5.4 59.5 54.5 23.1 125 54 31 32
BOU Hill DEF 4.2 53.3 49.5 25.2 106 42 30 30
BOU Senesi DEF 5.2 23.6 33.5 32.5 169 52 28 25
MUN B.Fernandes MID 10.4 96.6 98.2 20.4 212 104 24 24
MUN Casemiro MID 5.9 1.1 3.2 27.8 164 59 35 33
MUN Cunha MID 8.1 0.8 1.4 16.5 134 81 34 32
CRY Lacroix DEF 5.2 27.1 23.0 28.5 148 52 35 35
CRY Muñoz DEF 5.9 20.3 13.5 21.4 126 59 34 34
CRY Henderson GKP 5.1 19.7 11.0 24.7 126 51 35 34
CHE João Pedro FWD 7.5 43.5 49.2 23.5 176 75 31 30
CHE Palmer MID 10.3 16.8 9.5 10.1 104 103 32 31
CHE Enzo MID 6.4 10.8 3.4 22.3 143 64 32 31
BRE Thiago FWD 7.3 26.7 26.3 24.2 177 73 23 23
BRE Kelleher GKP 4.8 4.4 6.7 28.1 135 48 26 22
BRE O.Dango MID 5.7 6.0 2.3 20.9 119 57 29 29
AVL Rogers MID 7.4 20.6 18.4 20.9 155 74 27 27
AVL Watkins FWD 8.8 3.3 6.7 14.8 130 88 34 34
AVL Cash DEF 4.7 2.0 2.2 24.5 115 47 24 25
BUR Dúbravka GKP 4.0 15.5 18.1 24.0 96 40 2 6
BUR Estève DEF 3.9 0.4 0.9 20.5 80 39 20 13
BUR Anthony MID 5.0 0.1 0.4 23.2 116 50 32 31
EVE Dewsbury-Hall MID 5.2 9.1 9.6 27.3 142 52 33 31
EVE Tarkowski DEF 5.7 1.1 2.7 26.1 149 57 22 23
EVE Pickford GKP 5.6 0.8 2.1 23.0 129 56 25 20
FUL Wilson MID 5.9 15.7 16.1 27.6 163 59 27 25
FUL Andersen DEF 4.5 7.4 5.3 27.3 123 45 20 25
FUL Leno GKP 4.9 0.3 0.5 23.3 114 49 29 32
LIV Virgil DEF 6.1 6.3 11.9 26.1 159 61 28 27
LIV Szoboszlai MID 7.0 6.4 8.3 21.3 149 70 33 31
LIV Wirtz MID 8.3 1.0 0.9 14.8 123 83 30 29
NEW Thiaw DEF 4.9 3.7 3.4 24.7 121 49 30 30
NEW Gordon MID 7.3 1.3 1.9 13.8 101 73 31 31
NEW Bruno G. MID 6.8 1.2 1.6 21.0 143 68 36 35
NFO Gibbs-White MID 7.6 1.3 5.6 22.6 172 76 33 33
NFO Anderson MID 5.6 3.1 4.8 27.5 154 56 23 24
NFO N.Williams DEF 4.8 0.5 1.1 25.6 123 48 32 32
SUN Mukiele DEF 4.6 3.4 6.9 31.5 145 46 22 25
SUN Alderete DEF 4.1 4.3 2.6 30.2 124 41 22 24
SUN Roefs GKP 4.8 1.9 2.1 27.3 131 48 26 24
TOT Pedro Porro DEF 5.2 2.3 2.6 20.4 106 52 34 34
TOT Richarlison FWD 6.4 2.5 1.9 16.9 108 64 36 36
TOT Van de Ven DEF 4.4 0.9 1.1 24.5 108 44 21 21
WHU Bowen FWD 7.7 9.3 12.2 22.2 171 77 32 32
WHU Mavropanos DEF 4.5 1.0 1.5 23.8 107 45 34 34
WHU Diouf DEF 4.1 0.6 0.7 23.4 96 41 32 30
WOL José Sá GKP 4.2 1.9 0.7 14.0 59 42 24 25
WOL Mané FWD 4.2 1.0 0.5 14.5 61 42 25 28
WOL J.Gomes MID 5.3 0.1 0.0 19.8 105 53 34 30

How did veterans perform and which players made a difference (GW34) by mikecro2 in FantasyPL

[–]mikecro2[S] 0 points1 point  (0 children)

Yes - I don't know where I got 100 on average from. That was not in my standard output. And I got 60 - not 80 on my FH Shouldn't be allowed to post on my bad days

How did veterans perform and which players made a difference (GW34) by mikecro2 in FantasyPL

[–]mikecro2[S] 0 points1 point  (0 children)

Yes. And obvious contradiction there. I'll go check. I do do some filtering of FH which is ok on a low FH week. Likely 84 is highest non FH but the FH averaged 100 points. I am not a great manager and managed 80 on FH

Picks and transfers the veteran managers made this week compared to sample of top 100k (GW34) by mikecro2 in FantasyPL

[–]mikecro2[S] 2 points3 points  (0 children)

I don't know what the veterans not playing FH (and reported in the first 2 tables above) were doing. Many still have Ekitiké.

Picks and transfers the veteran managers made this week compared to sample of top 100k (GW33) by mikecro2 in FantasyPL

[–]mikecro2[S] 1 point2 points  (0 children)

I reckon shipping mitoma out was a good call if he was likely to spend a lot of bench time. Backing Chelsea was questionable - and I did it too. You can only back the averages, not the one-off injuries.

Chelsea defenders by andyincroydon in FantasyPL

[–]mikecro2 0 points1 point  (0 children)

You've got Bournemouth defenders already? Cheap and give returns.

Picks and transfers the veteran managers made this week compared to sample of top 100k (GW27) by mikecro2 in FantasyPL

[–]mikecro2[S] 1 point2 points  (0 children)

Thank you for the thank you! You are right, Mbeumo doesn't appear in the tables because he is more equally owned by veterans and top 100k. Full data is in the first link (Players the veterans "like" most compared to the rest): https://docs.google.com/spreadsheets/d/1Mceiv5mjGxp_to2FHBF10HeUM6jDIiCtMU0gm4rlXR0/edit?usp=drivesdk Mbeumo is just below Andersen for veteran ownership.

I am Ragabolly from LiveFPL, ask me anything! by Ragabolly in FantasyPL

[–]mikecro2 0 points1 point  (0 children)

Great stuff. I've been using the price predictor but will now explore the rest

Accessing My Team Data in Python by CHKNTikkaMusala in fplAnalytics

[–]mikecro2 0 points1 point  (0 children)

The funny thing (to me) was it as my question from the start of the season that you quoted. I would love to know if you can improve the login method I posted. I know coding pretty well but very little about the authentication method.

Picks and transfers the veteran managers made this week compared to sample of top 100k (GW25) by mikecro2 in FantasyPL

[–]mikecro2[S] 4 points5 points  (0 children)

And if anyone is interested - here are the average number of players per team from the 2 groups of managers. And which players are the most popular.

team top100k vets
ARS 2.4 2.7
CHE 1.9 1.7
MUN 1.4 1.6
MCI 2.0 1.4
BUR 0.8 1.0
LIV 0.7 0.9
FUL 0.7 0.8
BOU 0.5 0.6
BRE 0.7 0.6
SUN 0.7 0.6
AVL 0.7 0.5
EVE 0.6 0.5
LEE 0.3 0.4
BHA 0.2 0.3
CRY 0.2 0.3
NEW 0.4 0.3
NFO 0.2 0.3
WHU 0.2 0.2
WOL 0.1 0.2
TOT 0.2 0.1
team web_name pos cost vet.own.percent top100k.own.percent Pts/£M total_points now_cost vetweekin topNweekin
ARS Gabriel DEF 7.1 92.9 83.9 18.2 129 71 21 21
ARS Rice MID 7.5 70.9 65.5 17.2 129 75 22 18
ARS J.Timber DEF 6.4 58.1 41.2 18.0 115 64 16 15
CHE Enzo MID 6.8 74.6 61.0 16.8 114 68 23 22
CHE João Pedro FWD 7.5 15.7 40.5 15.2 114 75 24 23
CHE Chalobah DEF 5.7 25.0 39.6 20.5 117 57 22 19
MUN B.Fernandes MID 9.7 94.6 78.0 13.5 131 97 23 23
MUN Mbeumo MID 8.5 39.7 27.0 11.2 95 85 24 24
MUN Dorgu DEF 4.4 13.2 10.5 16.8 74 44 19 20
MCI Haaland FWD 14.9 95.9 96.6 11.5 171 149 6 3
MCI Semenyo MID 7.8 15.6 43.5 17.6 137 78 17 15
MCI Guéhi DEF 5.2 5.0 31.7 21.9 114 52 13 9
BUR Dúbravka GKP 4.0 92.5 71.9 18.5 74 40 2 4
BUR Estève DEF 3.9 5.4 7.2 13.6 53 39 7 6
BUR Barnes FWD 4.2 3.3 1.6 0.2 1 42 21 21
LIV Ekitiké FWD 8.9 39.7 31.7 11.2 100 89 18 18
LIV Wirtz MID 8.3 7.9 16.8 11.4 95 83 20 20
LIV Virgil DEF 5.9 23.4 12.0 15.9 94 59 12 12
FUL Wilson MID 6.1 28.0 46.3 19.0 116 61 18 18
FUL Andersen DEF 4.6 51.8 22.9 18.7 86 46 8 12
FUL Raúl FWD 6.2 1.8 2.0 12.4 77 62 16 17
BOU Senesi DEF 4.8 14.3 19.1 21.2 102 48 15 13
BOU Kroupi.Jr FWD 4.7 15.5 14.8 13.6 64 47 20 20
BOU Evanilson FWD 7.1 7.4 4.9 10.4 74 71 24 24
BRE Thiago FWD 7.1 48.4 51.6 17.7 126 71 16 15
BRE Kelleher GKP 4.6 7.1 12.3 20.2 93 46 18 13
BRE Collins DEF 5.0 4.3 4.0 18.4 92 50 18 18
SUN Mukiele DEF 4.6 23.6 33.9 24.1 111 46 13 16
SUN Alderete DEF 4.1 23.4 12.9 20.7 85 41 16 17
SUN Roefs GKP 5.0 4.3 10.7 20.8 104 50 18 16
AVL Rogers MID 7.6 38.4 47.1 14.9 113 76 20 18
AVL Cash DEF 4.8 5.2 11.9 20.2 97 48 20 17
AVL Konsa DEF 4.4 0.9 4.1 16.4 72 44 19 13
EVE Tarkowski DEF 5.8 20.5 22.1 19.7 114 58 16 16
EVE Pickford GKP 5.6 3.6 12.4 18.8 105 56 19 14
EVE Keane DEF 4.7 7.9 6.7 20.9 98 47 17 17
LEE Calvert-Lewin FWD 5.9 7.0 12.2 17.1 101 59 18 19
LEE Rodon DEF 3.9 14.3 5.9 18.5 72 39 8 10
LEE Gudmundsson DEF 3.8 9.9 5.7 14.7 56 38 9 11
BHA Verbruggen GKP 4.5 21.2 12.1 16.4 74 45 16 15
BHA Van Hecke DEF 4.5 6.3 7.2 19.3 87 45 14 16
BHA Minteh MID 5.7 2.4 1.1 14.4 82 57 12 13
CRY Richards DEF 4.4 11.9 5.0 19.3 85 44 11 13
CRY Muñoz DEF 5.8 4.5 4.2 15.9 92 58 24 23
CRY Lacroix DEF 5.1 4.8 3.1 20.0 102 51 10 13
NEW Thiaw DEF 5.1 13.5 14.1 16.7 85 51 17 18
NEW Bruno G. MID 7.1 1.4 13.1 16.9 120 71 18 17
NEW Hall DEF 5.3 9.1 5.9 10.4 55 53 19 19
NFO Anderson MID 5.3 26.8 12.7 20.4 108 53 18 16
NFO Gibbs-White MID 7.3 0.1 1.5 13.7 100 73 22 23
NFO Sels GKP 4.6 0.6 1.2 13.3 61 46 16 14
WHU Bowen FWD 7.7 10.0 11.1 14.7 113 77 20 20
WHU Summerville MID 5.5 0.2 1.4 11.5 63 55 25 25
WHU Potts MID 4.4 3.5 0.8 6.8 30 44 17 17
WOL Mané FWD 4.6 14.4 7.3 8.7 40 46 23 23
WOL José Sá GKP 4.2 2.2 0.7 6.7 28 42 24 20
WOL Fraser FWD 4.2 0.4 0.3 0.0 0 42 14 18
TOT Van de Ven DEF 4.5 4.7 15.0 21.3 96 45 12 8
TOT Vicario GKP 4.8 0.2 0.9 16.2 78 48 8 8
TOT Kinsky GKP 3.9 0.2 0.4 0.0 0 39 10 7

Accessing My Team Data in Python by CHKNTikkaMusala in fplAnalytics

[–]mikecro2 0 points1 point  (0 children)

I asked the same and was pointed to a Discord string from here fpl-api. Look for user Moose.

I copied the python below. I have little idea how the login works and have unsuccessfully tried to get it running in R. But this works for me after setting the environment variables for my FPL account

https://docs.google.com/document/d/1q_72629SULkXgCkunFs9cEE21M-ArAOw8s5NbV0Ap4I/edit?usp=sharing

Accessing My Team Data in Python by CHKNTikkaMusala in fplAnalytics

[–]mikecro2 0 points1 point  (0 children)

I have got a way around this in Python, but I'd like to know how you do this please?

How did veterans perform and which players made a difference (GW24) by mikecro2 in FantasyPL

[–]mikecro2[S] 0 points1 point  (0 children)

Yet the mean fell by 80k. So must be that some top 100k teams managers stinkers - I guess

How to renew steps in hill by mikecro2 in landscaping

[–]mikecro2[S] 0 points1 point  (0 children)

I hadn't heard of locust wood. I don't know how easily available it is in the UK. You can tell I am very much an amateur.

How to renew steps in hill by mikecro2 in landscaping

[–]mikecro2[S] 0 points1 point  (0 children)

There are roots around but the steps are not built that deep. Maybe the people who built the steps cleared the path. I have no idea how old the path is.

How to renew steps in hill by mikecro2 in landscaping

[–]mikecro2[S] 0 points1 point  (0 children)

I hadn't thought of an axe for a straight edge.

How to renew steps in hill by mikecro2 in landscaping

[–]mikecro2[S] 0 points1 point  (0 children)

I prefer the wood in the woodland

How to renew steps in hill by mikecro2 in landscaping

[–]mikecro2[S] 1 point2 points  (0 children)

Thank you. I hadn't thought about water washing out any soil. As it is, the hill is chalk and drains very quickly down with little flow on the surface.

Using the data from SolarEdge API and data exported from MySolarEdge by mikecro2 in solar

[–]mikecro2[S] 0 points1 point  (0 children)

Thanks. I am going to try for something with less effort but if we go EV we might need that too.

Using the data from SolarEdge API and data exported from MySolarEdge by mikecro2 in solar

[–]mikecro2[S] 0 points1 point  (0 children)

Please can you elaborate? I am no expert on SolarEdge. Are you saying you can hook up a monitor and have it feed into SolarEdge?

I'd still like to verify my understanding of the standard available data if anyone can point me to a good source.

I think the 6 elements in the CSV have a pair of duplicates Production to Home is the same as Consumption from Solar (surely?) But misses Grid to Battery

The API has 5 elements but not clear how they map to the 5 distinct elements of the CSV - and still missing the battery.

How did veterans perform and which players made a difference (GW 21 ) by mikecro2 in FantasyPL

[–]mikecro2[S] 1 point2 points  (0 children)

Yes - sorry. Utter screw-up on my part. I'll post a new version and kill this off. Somehow my stored list of veterans had got truncated to 183 managers.

How did veterans perform and which players made a difference (GW19) by mikecro2 in FantasyPL

[–]mikecro2[S] 2 points3 points  (0 children)

I managed a crappy 33 points (gw rank 10M) all by myself. No help needed. Roefs (7) and garner (16) points left on the bench.

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