Do you think you have what it takes to predict the outcome of every match of the 2021 Euro and Copa America football tournaments?
Betfair is giving you the chance to show off your data modelling skills by building a predictive model for this year’s Euro and Copa America football tournaments!
We’re challenging you to use your modelling skills to your advantage, be that by building your first predictive sports model, improving on an existing design or have a go something different by adapting your data skills from other fields.
This year’s Euro and Copa America tournaments will be running simultaneously throughout June and July, presenting a perfect opportunity for keen sports and data enthusiasts to get involved and put your skills to the test against the masses in order to compete for ultimate glory!
Submissions close at 11:59pm AEST on Friday June 11th 2021 – time to get modelling!
Thank You to all who participated in Betfair’s Euro & Copa América Datathon! Reach out to datathon@betfair.com.au to stay informed about future Betfair Datathons and other competitions.
Prize winners will be contacted shortly via contact details supplied at registration.
Final leaderboard – please note that entries marked “(i/e)” are not eligible for prizes:
* The Betfair_Market_Odds entry takes the last traded price of head-to-head markets before kick-off for each team and the draw within a match and converts them to implied probabilities.
** You can find a code walkthrough in R for the Betfair_Basic_Elo and Elo_100 entries on the Betfair Automation Hub.
*** The World_Football_Elo_Ratings model is based on the pre-tournament elo ratings found at eloratings.net.
Rank | Model Name | Combined Log Loss | Euro Log Loss | Copa America Log Loss | Matches Scored |
---|---|---|---|---|---|
1 | biscuits | 0.7705382708414321 | 0.7973073149546842 | 0.721780369063723 | 79 |
2 | camos | 0.7826445253123128 | 0.8216374240465514 | 0.7116217454749495 | 79 |
3 | bingbongslon | 0.7859084272748551 | 0.8231767607623172 | 0.7180268198512634 | 79 |
4 | MBD_Likelihood_Estimation | 0.7903489122564166 | 0.7965541104412299 | 0.7790465869912208 | 79 |
5 | PotShots | 0.7914306182598086 | 0.8139687956777264 | 0.7503789379628869 | 79 |
6 | elodragi | 0.7914583098362438 | 0.8251344252819285 | 0.7301196709887467 | 79 |
7 | p2tp | 0.7920428007917959 | 0.821863351716297 | 0.737726797322169 | 79 |
8 | HelloElo | 0.7921717150325185 | 0.8052358712169317 | 0.7683762876966227 | 79 |
9 | FalconsAFC | 0.7926311892550005 | 0.8235329242080895 | 0.7363458863047312 | 79 |
10 | dodgy1 | 0.7927661556319335 | 0.8214687449862587 | 0.7404864393079841 | 79 |
11 | JT_sokkah | 0.7937699893704118 | 0.8256483613286792 | 0.7357058118749961 | 79 |
12 | belilabud | 0.7941517077607942 | 0.8345643694259731 | 0.7205429311563614 | 79 |
13 | ML_rookie | 0.7947631244562297 | 0.8177538626955332 | 0.7528871369489266 | 79 |
14 | Jason9000 | 0.7950741872431717 | 0.8351202301970233 | 0.7221331804343705 | 79 |
15 | OnePointTwentyOneGigawatts | 0.7951969218467424 | 0.8061983751321946 | 0.7751585605053832 | 79 |
16 | XWang | 0.7955612709983727 | 0.7697212408602612 | 0.8426270401785046 | 79 |
17 | willingly | 0.7957390180271291 | 0.8146925514119541 | 0.7612165107904836 | 79 |
18 | modelsAreForNerds | 0.796482986782254 | 0.8108280097842145 | 0.7703545520286832 | 79 |
19 | Betfair_Basic_Elo** (i/e) | 0.797159755420267 | 0.8151782661491083 | 0.764340325164163 | 79 |
20 | Elo100** (i/e) | 0.7987096305056234 | 0.8037842549788061 | 0.7894665645008976 | 79 |
21 | kenz_til_the_enz | 0.8022127940586186 | 0.8206639179215439 | 0.7686053898797189 | 79 |
22 | milktea | 0.803441190263712 | 0.8317212312315174 | 0.7519311156437807 | 79 |
23 | CSF | 0.8065283734458433 | 0.8259758299854398 | 0.7711062204630068 | 79 |
24 | Saint_Lenny (i/e) | 0.8083159173346812 | 0.8419868066318978 | 0.7469867975433223 | 79 |
25 | Betfair_Market_Odds* (i/e) | 0.8088742604598474 | 0.8537832712389296 | 0.7270757051122334 | 79 |
26 | World_Football_Elo_Ratings*** (i/e) | 0.8110103900331952 | 0.8255731236291077 | 0.7844854109834976 | 79 |
27 | NoThoughtsHeadEmpty | 0.8121467622749501 | 0.827932022958239 | 0.7833950374589596 | 79 |
28 | astaloshi | 0.8145766157373197 | 0.851270004943248 | 0.747742228255093 | 79 |
29 | craigjohnson | 0.8191148283444161 | 0.8237702721763593 | 0.8106352699362338 | 79 |
30 | YHD | 0.8205062530233639 | 0.8417860725003632 | 0.7817465818331153 | 79 |
31 | ixl | 0.8212574656964107 | 0.8356825304556769 | 0.794983240599176 | 79 |
32 | jspen | 0.8214099546899187 | 0.8644692127230239 | 0.7429805918439054 | 79 |
33 | AJCOLLETT | 0.8234090133211434 | 0.8396403723975283 | 0.7938447521462991 | 79 |
34 | weak_learner | 0.8265648230092298 | 0.8553776725661656 | 0.774084275601954 | 79 |
35 | Fourier17 | 0.8312938367486451 | 0.8385752971358655 | 0.8180311767576368 | 79 |
36 | thomasatkins | 0.8319235482526507 | 0.8133420118243667 | 0.865768489604168 | 79 |
37 | MAM | 0.8419123902888526 | 0.8920497520710253 | 0.7505907670427521 | 79 |
38 | JQ_elo | 0.8650189195796677 | 0.8865877475365004 | 0.8257328400868654 | 79 |
39 | nine_min_model | 0.8770319337728729 | 0.9177043712172509 | 0.8029499941420416 | 79 |
40 | GlenHickey | 0.9002560356450022 | 0.9425324064358912 | 0.8232526459901687 | 79 |
41 | jacobholden229 | 0.903262210205102 | 0.904956677652673 | 0.9001758587827406 | 79 |
42 | BTS | 0.9090598007873711 | 0.889482432267765 | 0.944718579162368 | 79 |
43 | DAA | 0.9122528137704206 | 0.9511940690761778 | 0.84132409874922 | 79 |
44 | Adam_Elo | 0.9127280695282063 | 0.8750251585870639 | 0.9814012287424296 | 79 |
45 | boonie | 0.9562094547420199 | 0.8840542372378273 | 1.0876350294817996 | 79 |
46 | georgeMaksour | 0.9640297413914155 | 1.0273431420217645 | 0.8487089045289943 | 79 |
47 | LinearThinking | 0.9663955302417361 | 0.9104134180564113 | 1.0683629488650064 | 79 |
48 | geoff_c | 0.9788459540660631 | 0.9922709896473565 | 0.9543932106858498 | 79 |
49 | MessiSuccessi | 0.980565485248433 | 0.9793578453225711 | 0.982765115113396 | 79 |
50 | Engerland | 1.0129748779926606 | 1.0195125528646638 | 1.0010669701900834 | 79 |
51 | sandrock | 1.1531545514998585 | 1.1743171798373022 | 1.1146083355995144 | 79 |
52 | Very_Random | 1.271020461433728 | 1.2651325618778237 | 1.2817448499105533 | 79 |
53 | Timeseries | 1.6594432212235033 | 1.736785821751317 | 1.5185691988335566 | 79 |
54 | Overconfident_Tipster | 1.7013643694629157 | 1.5465345391363339 | 1.9833758461291895 | 79 |
55 | beastars | 1.9044705477434967 | 1.8562463431033993 | 1.9923074919093875 | 79 |