Betfair’s 2021 Euro & Copa América Datathon

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 11^th 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