Quick '20 vs Ajax: result 1-1 and analysis
Friendlies ClubsClub Friendlies 1Kick-off on July 6, 2021 at 12:00 AM (UTC)Sportpark De Vondersweijde, Oldenzaal
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What was the result of Quick '20 vs Ajax?
Quick '20 and Ajax drew 1-1 on July 6, 2021.
Goalscorers
- 45′M. KudusAjax
- 80′I. WeversQuick '20
Official lineup for Quick '20 vs Ajax
The starting elevens fielded at kick-off.
Quick '20
- 7Frank Eulderink
- 6R. Snelders
- 20J. Kip
- 8M. Braam
- 9D. Rickhoff
- 2Cas Goorhuis Oude Sanderink
- 3J. Leenders
- 4Yannick Heskamp
- 5Tim Zwienenberg
- 10L. Keizer
- 1C. ter Braak
Ajax
- 7David Neres
- 9Danilo
- 2Y. Regeer
- 3E. Llansana
- 6K. Fitz-Jim
- 8K. Taylor
- 10D. Tadić
- 11M. Kudus
- 4L. Magallán
- 5Y. Baas
- 1J. Gorter
What is the recent form of both teams?
Over their last 4 matches in all competitions, Quick '20 have 1 win, 0 draws and 3 defeats; Ajax have 12, 2 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 18, 2018 | DVS 33 Ermelo(home) | 2-6 | KNVB Beker |
| Aug 23, 2017 | Csv Apeldoorn(home) | 0-1 | KNVB Beker |
| Aug 24, 2016 | JVC Cuijk(home) | 1-3 | KNVB Beker |
| Aug 17, 2016 | WV-HEDW(away) | 3-0 | KNVB Beker |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 3, 2021 | Koninklijke HFC(home) | 6-0 | Friendlies Clubs |
| May 16, 2021 | Vitesse(away) | 3-1 | Eredivisie |
| May 13, 2021 | VVV Venlo(home) | 3-1 | Eredivisie |
| May 9, 2021 | Feyenoord(away) | 3-0 | Eredivisie |
| May 2, 2021 | Emmen(home) | 4-0 | Eredivisie |
How many goals should we expect?
Quick '20 score 1.5 and concede 2.5 goals per match over their last 4; Ajax score 2.5 and concede 0.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Quick '20 | 1.5 | 2.5 | 1 | 2/4 | 3/4 |
| Ajax | 2.5 | 0.5 | 8 | 7/15 | 9/15 |
Over the last 4 matches in all competitions.
A question about Quick '20 vs Ajax?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy