Match

Richmond Kickers vs Christos: result 0-1 and analysis

US Open Cup2nd RoundKick-off on May 17, 2017 at 11:00 PM (UTC)City Stadium, Richmond, Virginia

Richmond Kickers
0-1
Christos

Full time

What was the result of Richmond Kickers vs Christos?

Christos won 0-1 on May 17, 2017.

Goalscorers

  • 79′171849Christos

Official lineup for Richmond Kickers vs Christos

The starting elevens fielded at kick-off.

Richmond Kickers

  1. 11A. Grant
  1. 5Conor Shanosky
  2. 9Oliver Thomal Minatel
  3. 1M. De Bellis
  4. 2W. Yomby
  5. 10S. Jane
  6. 12F. Wyatt
  7. 20M. Minutillo
  8. 24J. Eskay
  9. 31B. Troyer
  1. 18A. Lee

Christos

  1. 6L. Houapeu
  2. 9P. Caringi
  1. 5D. Baxter
  2. 8K. Forbess
  3. 10E. Joe
  4. 17C. Albrecht
  5. 18J. Glos
  6. 23M. Kansaye
  7. 7C. Fisher
  8. 11J. Perrerira
  1. 99P. Saunders
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Richmond Kickers have 3 wins, 4 draws and 8 defeats; Christos have 1, 0 and 0.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Richmond Kickers
DateOpponentScoreCompetition
May 13, 2017Penn(home)0-0USL Championship
May 6, 2017FC Cincinnati(home)1-1USL Championship
Apr 29, 2017Tampa Bay Rowdies(away)0-1USL Championship
Apr 22, 2017Pittsburgh Riverhounds(home)2-1USL Championship
Apr 15, 2017Ottawa Fury(home)0-1USL Championship
Christos
DateOpponentScoreCompetition
May 10, 2017Fredericksburg(away)3-0US Open Cup

How many goals should we expect?

Richmond Kickers score 0.5 and concede 1.0 goals per match over their last 15; Christos score 3.0 and concede 0.0.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Richmond Kickers0.51.044/152/15
Christos3.00.010/11/1

Over the last 15 matches in all competitions.

A question about Richmond Kickers vs Christos?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.

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

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