You can access data from the Squiggle API directly with the
fetch_squiggle_data. This allows direct access to the
Squiggle API.
Note that we also provide some helper functions that map more closely
to our fetch_ functions such as
fetch_ladder_squiggle.
Full instructions for constructing queries can be found at Squiggle API. One of the
following must be provided to the query argument.
teams - Info about teams (e.g. Richmond, Geelong, West
Coast)games - Info about games (e.g. Round 1, 2019 Richmond v
Carlton)sources - Info about models (e.g. Matter of Stats,
GRAFT, Swinburne)tips - Info about tips and predictions made by
modelsstandings - Info about team standings (i.e. the
ladder)ladder - Info about predicted ladders generated by
modelsvirtual - Info about Virtually Season 2020pav - Info about Player Approximate Value from HPN
FootyOptional arguments can then be supplied based on the query.
For example, games takes the following optional
arguments. * year - Year * round - Round *
game - Game ID * complete - Percent of game
complete
These can be supplied as named arguments after the query. For example, to return games from just 2020, we would use the following.
fetch_squiggle_data(query = "games", year = 2020)#> # A tibble: 162 × 24
#> ascore hteamid hgoals localtime is_grand_final date hscore ateamid agoals
#> <int> <int> <int> <chr> <int> <chr> <int> <int> <int>
#> 1 74 1 11 2020-03-21 … 0 2020… 71 16 11
#> 2 57 5 9 2020-03-21 … 0 2020… 63 6 8
#> 3 76 8 4 2020-03-21 … 0 2020… 29 13 10
#> 4 73 9 17 2020-03-21 … 0 2020… 105 7 11
#> 5 62 10 14 2020-03-22 … 0 2020… 90 2 9
#> 6 54 12 8 2020-03-22 … 0 2020… 56 15 7
#> 7 81 14 16 2020-03-19 … 0 2020… 105 3 12
#> 8 51 17 12 2020-03-22 … 0 2020… 78 11 7
#> 9 86 18 5 2020-03-20 … 0 2020… 34 4 13
#> 10 69 2 12 2020-06-13 … 0 2020… 81 6 10
#> # ℹ 152 more rows
#> # ℹ 15 more variables: hbehinds <int>, venue <chr>, hteam <chr>,
#> # is_final <int>, id <int>, roundname <chr>, round <int>, winner <chr>,
#> # abehinds <int>, ateam <chr>, tz <chr>, updated <chr>, complete <int>,
#> # winnerteamid <int>, year <int>Fetch info about one or more AFL teams.
fetch_squiggle_data("teams")#> # A tibble: 18 × 4
#> logo abbrev id name
#> <chr> <chr> <int> <chr>
#> 1 /wp-content/themes/squiggle/assets/images/Adelaide.png ADE 1 Adel…
#> 2 /wp-content/themes/squiggle/assets/images/Brisbane.png BRI 2 Bris…
#> 3 /wp-content/themes/squiggle/assets/images/Carlton.png CAR 3 Carl…
#> 4 /wp-content/themes/squiggle/assets/images/Collingwood.png COL 4 Coll…
#> 5 /wp-content/themes/squiggle/assets/images/Essendon.png ESS 5 Esse…
#> 6 /wp-content/themes/squiggle/assets/images/Fremantle.png FRE 6 Frem…
#> 7 /wp-content/themes/squiggle/assets/images/Geelong.png GEE 7 Geel…
#> 8 /wp-content/themes/squiggle/assets/images/GoldCoast.png GC 8 Gold…
#> 9 /wp-content/themes/squiggle/assets/images/Giants.png GWS 9 Grea…
#> 10 /wp-content/themes/squiggle/assets/images/Hawthorn.png HAW 10 Hawt…
#> 11 /wp-content/themes/squiggle/assets/images/Melbourne.png MEL 11 Melb…
#> 12 /wp-content/themes/squiggle/assets/images/NorthMelbourne.… NOR 12 Nort…
#> 13 /wp-content/themes/squiggle/assets/images/PortAdelaide.png POR 13 Port…
#> 14 /wp-content/themes/squiggle/assets/images/Richmond.png RIC 14 Rich…
#> 15 /wp-content/themes/squiggle/assets/images/StKilda.png STK 15 St K…
#> 16 /wp-content/themes/squiggle/assets/images/Sydney.png SYD 16 Sydn…
#> 17 /wp-content/themes/squiggle/assets/images/WestCoast.png WCE 17 West…
#> 18 /wp-content/themes/squiggle/assets/images/Bulldogs.png WBD 18 West…Fetch info about one or more games.
fetch_squiggle_data(query = "games", year = 2020)#> # A tibble: 162 × 24
#> ascore hteamid hgoals localtime is_grand_final date hscore ateamid agoals
#> <int> <int> <int> <chr> <int> <chr> <int> <int> <int>
#> 1 74 1 11 2020-03-21 … 0 2020… 71 16 11
#> 2 57 5 9 2020-03-21 … 0 2020… 63 6 8
#> 3 76 8 4 2020-03-21 … 0 2020… 29 13 10
#> 4 73 9 17 2020-03-21 … 0 2020… 105 7 11
#> 5 62 10 14 2020-03-22 … 0 2020… 90 2 9
#> 6 54 12 8 2020-03-22 … 0 2020… 56 15 7
#> 7 81 14 16 2020-03-19 … 0 2020… 105 3 12
#> 8 51 17 12 2020-03-22 … 0 2020… 78 11 7
#> 9 86 18 5 2020-03-20 … 0 2020… 34 4 13
#> 10 69 2 12 2020-06-13 … 0 2020… 81 6 10
#> # ℹ 152 more rows
#> # ℹ 15 more variables: hbehinds <int>, venue <chr>, hteam <chr>,
#> # is_final <int>, id <int>, roundname <chr>, round <int>, winner <chr>,
#> # abehinds <int>, ateam <chr>, tz <chr>, updated <chr>, complete <int>,
#> # winnerteamid <int>, year <int>Fetch info about one or more computer models.
# You can get the sources
fetch_squiggle_data("sources")#> # A tibble: 25 × 4
#> url icon id name
#> <chr> <chr> <int> <chr>
#> 1 "https://live.squiggle.com.au/" "/wp-content/uploads/2017/… 1 Squi…
#> 2 "https://thearcfooty.com/" "/wp-content/themes/squigg… 2 The …
#> 3 "http://figuringfooty.com/" "/wp-content/themes/squigg… 3 Figu…
#> 4 "http://www.matterofstats.com/" "/wp-content/themes/squigg… 4 Matt…
#> 5 "" "" 5 Punt…
#> 6 "https://footymaths.blogspot.com" "/wp-content/themes/squigg… 6 FMI
#> 7 "http://plussixoneblog.com/" "/wp-content/themes/squigg… 7 Plus…
#> 8 "/introducing-s10/" "" 8 Aggr…
#> 9 "http://graftratings.com/afl/" "/wp-content/themes/squigg… 9 Graft
#> 10 "https://stattraction.wordpress.com/" "/wp-content/themes/squigg… 10 Stat…
#> # ℹ 15 more rowsFetch info about one or more tips made by computer models.
# Get all tips
fetch_squiggle_data("tips")#> # A tibble: 15,682 × 21
#> hmargin year gameid ateamid source correct err bits ateam updated date
#> <dbl> <int> <int> <int> <chr> <int> <dbl> <dbl> <chr> <chr> <chr>
#> 1 -1 2017 1 14 Squig… 1 42 0 Rich… 2017-0… 2017…
#> 2 NA 2017 1 14 Figur… 1 NA 0.214 Rich… 2017-0… 2017…
#> 3 5.39 2017 1 14 Matte… 0 48.4 -0.208 Rich… 2017-0… 2017…
#> 4 -10.3 2017 2 18 Matte… 1 3.69 0.326 West… 2017-0… 2017…
#> 5 -17 2017 2 18 Squig… 1 3 0.310 West… 2017-0… 2017…
#> 6 3 2017 8 9 Squig… 1 53 0 Grea… 2017-0… 2017…
#> 7 -8 2017 1 14 The A… 1 35 0.234 Rich… 2017-0… 2017…
#> 8 -13 2017 2 18 The A… 1 1 0.358 West… 2017-0… 2017…
#> 9 2 2017 4 11 The A… 0 32 -0.0862 Melb… 2017-0… 2017…
#> 10 29 2017 3 13 The A… 0 57 -1.28 Port… 2017-0… 2017…
#> # ℹ 15,672 more rows
#> # ℹ 10 more variables: hteamid <int>, round <int>, hconfidence <dbl>,
#> # margin <dbl>, tipteamid <int>, sourceid <int>, venue <chr>, hteam <chr>,
#> # confidence <dbl>, tip <chr>We can just look at one particular round.
# Get` just tips from round 1, 2018
fetch_squiggle_data("tips", round = 1, year = 2018)#> # A tibble: 126 × 21
#> hmargin year gameid ateamid source correct err bits ateam updated date
#> <dbl> <int> <int> <int> <chr> <int> <dbl> <dbl> <chr> <chr> <chr>
#> 1 NA 2018 372 3 Punte… 1 NA 0.675 Carl… 2018-0… 2018…
#> 2 NA 2018 373 1 Punte… 1 NA 0.0588 Adel… 2018-0… 2018…
#> 3 NA 2018 374 2 Punte… 1 NA 0.521 Bris… 2018-0… 2018…
#> 4 NA 2018 375 6 Punte… 1 NA 0.666 Frem… 2018-0… 2018…
#> 5 NA 2018 376 12 Punte… 0 NA -0.0151 Nort… 2018-0… 2018…
#> 6 NA 2018 377 4 Punte… 1 NA 0.122 Coll… 2018-0… 2018…
#> 7 NA 2018 378 18 Punte… 1 NA 0.530 West… 2018-0… 2018…
#> 8 NA 2018 379 7 Punte… 0 NA -0.198 Geel… 2018-0… 2018…
#> 9 NA 2018 380 16 Punte… 1 NA 0.486 Sydn… 2018-0… 2018…
#> 10 35.2 2018 372 3 Aggre… 1 9.2 0.674 Carl… 2018-0… 2018…
#> # ℹ 116 more rows
#> # ℹ 10 more variables: hteamid <int>, round <int>, hconfidence <dbl>,
#> # margin <dbl>, tipteamid <int>, sourceid <int>, venue <chr>, hteam <chr>,
#> # confidence <dbl>, tip <chr>Fetch info about team standings at a point in time, i.e. the ladder.
fetch_squiggle_data("standings", year = 2020, round = 1)#> # A tibble: 18 × 15
#> percentage played goals_against name behinds_for wins losses against draws
#> <dbl> <int> <int> <chr> <int> <int> <int> <int> <int>
#> 1 262. 1 4 Port … 16 1 0 29 0
#> 2 253. 1 5 Colli… 8 1 0 34 0
#> 3 153. 1 7 West … 6 1 0 51 0
#> 4 145. 1 9 Hawth… 6 1 0 62 0
#> 5 144. 1 11 Great… 3 1 0 73 0
#> 6 130. 1 12 Richm… 9 1 0 81 0
#> 7 111. 1 8 Essen… 9 1 0 57 0
#> 8 104. 1 11 Sydney 8 1 0 71 0
#> 9 104. 1 7 North… 8 1 0 54 0
#> 10 96.4 1 8 St Ki… 12 0 1 56 0
#> 11 95.9 1 11 Adela… 5 0 1 74 0
#> 12 90.5 1 9 Frema… 9 0 1 63 0
#> 13 77.1 1 16 Carlt… 9 0 1 105 0
#> 14 69.5 1 17 Geelo… 7 0 1 105 0
#> 15 68.9 1 14 Brisb… 8 0 1 90 0
#> 16 65.4 1 12 Melbo… 9 0 1 78 0
#> 17 39.5 1 13 Weste… 4 0 1 86 0
#> 18 38.2 1 10 Gold … 5 0 1 76 0
#> # ℹ 6 more variables: for. <int>, id <int>, rank <int>, pts <int>,
#> # goals_for <int>, behinds_against <int>Fetch info about one or more projected ladders generated by computer models. For the actual ladder, see standings instead.
fetch_squiggle_data("ladder", year = 2019, round = 15, source = 1)#> # A tibble: 18 × 12
#> teamid mean_rank updated percentage source sourceid swarms rank wins round
#> <int> <dbl> <chr> <dbl> <chr> <int> <chr> <int> <dbl> <int>
#> 1 1 6.11 2019-07… 111. Squig… 1 "c(\"… 6 12.7 15
#> 2 2 6.01 2019-07… 107. Squig… 1 "c(\"… 5 13 15
#> 3 3 16.7 2019-07… 82.8 Squig… 1 "c(\"… 17 6.1 15
#> 4 4 4.20 2019-07… 114 Squig… 1 "c(\"… 4 14.1 15
#> 5 5 9.98 2019-07… 99.8 Squig… 1 "c(\"… 10 10.8 15
#> 6 6 9.71 2019-07… 104. Squig… 1 "c(\"… 9 10.8 15
#> 7 7 1.21 2019-07… 138. Squig… 1 "c(\"… 1 17.3 15
#> 8 8 17.7 2019-07… 70.2 Squig… 1 "c(\"… 18 4.9 15
#> 9 9 3.26 2019-07… 129. Squig… 1 "c(\"… 2 14.4 15
#> 10 10 13.0 2019-07… 97.6 Squig… 1 "c(\"… 14 8.8 15
#> 11 11 14.8 2019-07… 85.3 Squig… 1 "c(\"… 16 8 15
#> 12 12 10.9 2019-07… 98.9 Squig… 1 "c(\"… 11 10.2 15
#> 13 13 8.24 2019-07… 107. Squig… 1 "c(\"… 8 11.5 15
#> 14 14 6.67 2019-07… 101. Squig… 1 "c(\"… 7 12.8 15
#> 15 15 13.8 2019-07… 83.2 Squig… 1 "c(\"… 15 9 15
#> 16 16 12.9 2019-07… 93.4 Squig… 1 "c(\"… 13 9.2 15
#> 17 17 4.16 2019-07… 107. Squig… 1 "c(\"… 3 14.4 15
#> 18 18 11.9 2019-07… 94.1 Squig… 1 "c(\"… 12 9.8 15
#> # ℹ 2 more variables: team <chr>, year <int>Fetch info about players using HPN Footy’s Player Approximate Value.
fetch_squiggle_data("pav",
firstname = "Dustin",
surname = "Martin",
year = 2017
)#> # A tibble: 1 × 21
#> PAV_mid_rank mPAV_def games firstname mPAV_mid year PAV_total PAV_def_rank
#> <int> <dbl> <int> <chr> <dbl> <int> <dbl> <int>
#> 1 1 -0.41 25 Dustin 2.06 2017 26.8 253
#> # ℹ 13 more variables: name <chr>, PAV_off_rank <int>, X._of_team_games <dbl>,
#> # PAV_total_rank <int>, PAV_mid <dbl>, surname <chr>, PAV_def <dbl>,
#> # team <int>, mPAV_total <dbl>, pavid <int>, mPAV_off <dbl>, PAV_off <dbl>,
#> # mPAV_rank <int>