Match

Paidha Black Angels vs Vipers: result 0-1 and analysis

Premier LeagueRegular Season - 29Kick-off on May 1, 2019 at 01:30 PM (UTC)Barokoro Ground, Zombo

Paidha Black Angels
0-1
Vipers

Full time

What was the result of Paidha Black Angels vs Vipers?

Vipers won 0-1 on May 1, 2019.

What is the recent form of both teams?

Over their last 15 matches in all competitions, Paidha Black Angels have 1 win, 5 draws and 9 defeats; Vipers have 6, 6 and 3.

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

Paidha Black Angels
DateOpponentScoreCompetition
Apr 24, 2019Onduparaka(home)1-1Premier League
Apr 16, 2019Busoga United(away)0-2Premier League
Apr 9, 2019KCCA(home)0-2Premier League
Apr 2, 2019Express(away)0-2Premier League
Mar 13, 2019Police(away)2-4Premier League
Vipers
DateOpponentScoreCompetition
Apr 23, 2019Police(away)2-1Premier League
Apr 19, 2019URA(home)1-2Premier League
Apr 10, 2019Mbarara City(away)0-0Premier League
Apr 4, 2019KCCA(away)1-1Premier League
Mar 27, 2019Maroons(home)2-0Premier League

What does the head-to-head say?

In the last meeting: 0 Paidha Black Angels wins, 0 draws, 1 Vipers win.

DateScoreCompetition
Nov 23, 2018Vipers 2-1 Paidha Black AngelsPremier League

Last archived meeting: Vipers vs Paidha Black Angels on Nov 23, 2018

How many goals should we expect?

Paidha Black Angels score 0.7 and concede 1.7 goals per match over their last 15; Vipers score 1.2 and concede 0.8.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Paidha Black Angels0.71.727/155/15
Vipers1.20.878/155/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2026 standings
#ClubPWDLGFGAPts
7Vipers942315414

A question about Paidha Black Angels vs Vipers?

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

Other matches in the same round

Ready to know everything about football?