Update: Forecasts and Outcomes, March 13-19
J James Reade
20/03/2015
This document summarises the forecast outcomes for the most set of forecasts for English football match outcomes, following on from recent weeks, and it provides outcomes for forecasts of matches over the last week as detailed in this document.
Two sets of forecasts are constructed, one using a simple linear regression method for a dependent variable taking the values 0 for an away win, 0.5 for a draw, and 1 for a home win. This linear regression method only yields a number which can be interpreted as a probability of an outcome occurring. The second, ordered logit method, treats each outcome in an ordered manner, from away win, to draw, to home win, and estimates a probability for each outcome.
The purpose of this document is to evaluate these forecasts, and begin to form a longer-term narrative about them.
Outcomes
To consider outcomes; we must load up the specific outcomes file for matches forecast over the weekend:
dates <- c("2015-01-30","2015-02-06","2015-02-13","2015-02-20","2015-02-27","2015-03-06","2015-03-13")
date.1 <- dates[NROW(dates)]
recent.forecast.outcomes <- read.csv(paste("forecast_outcomes_",date.1,".csv",sep=""),stringsAsFactors=F)
forecast.matches <- read.csv(paste("forecasts_",date.1,".csv",sep=""))
forecast.matches <- forecast.matches[is.na(forecast.matches$outcome)==F,]
forecast.outcomes <- merge(forecast.matches[,c("match_id","outcome","Ph","Pd","Pa")],
recent.forecast.outcomes,by=c("match_id"),
suffixes=c(".forc",".final"))
forecast.outcomes <- forecast.outcomes[is.na(forecast.outcomes$outcome.final)==F,]
all.forecast.outcomes <- data.frame()
loc <- "/home/readejj/Dropbox/Teaching/Reading/ec313/2015/Football-forecasts/"
for(i in dates) {
temp.0 <- read.csv(paste(loc,"forecast_outcomes_",i,".csv",sep=""),stringsAsFactors=F)
temp.0$X <-NULL
temp.0$forc.week <- i
temp.1 <- read.csv(paste(loc,"forecasts_",i,".csv",sep=""))
temp.1$X <-NULL
temp.1 <- temp.1[is.na(temp.1$outcome)==F,]
if(!("Ph" %in% colnames(temp.1))) {
temp.1$Ph <- NA
temp.1$Pd <- NA
temp.1$Pa <- NA
}
if(!("tier" %in% colnames(temp.0))) {
temp.0$tier <- NA
}
temp.2 <- merge(temp.1[,c("match_id","outcome","Ph","Pd","Pa")],
temp.0[,c("match_id","date","division","team1",
"goals1","goals2","team2","outcome",
"season","tier","forc.week")],
by=c("match_id"),suffixes=c(".forc",".final"))
all.forecast.outcomes <- rbind(temp.2[is.na(temp.2$outcome.final)==F,],all.forecast.outcomes)
}outcomeplot <- function(div) {
matches <- forecast.outcomes[forecast.outcomes$division==div,]
matches$id <- 1:NROW(matches)
par(mar=c(9,4,4,5)+.1)
plot(matches$id,matches$outcome.forc,xaxt="n",xlab="",ylim=range(0,1),
main=paste("Forecasts of Weekend ",div," Matches",sep=""),
ylab="Probability of Outcome")
lines(matches$id,matches$Ph,col=2,pch=15,type="p")
lines(matches$id,matches$Pd,col=3,pch=16,type="p")
lines(matches$id,matches$Pa,col=4,pch=17,type="p")
legend("topleft",ncol=4,pch=c(1,15,16,17),col=c(1:4),
legend=c("OLS","OL (home)","OL (draw)","OL (away)"),bty="n")
abline(h=0.5,lty=2)
abline(h=0.6,lty=3)
abline(h=0.7,lty=2)
abline(h=0.4,lty=3)
for(i in 1:NROW(matches)) {
if(matches$outcome.final[i]==1) {
lines(matches$id[i],matches$outcome.final[i],col=2,type="p",pch=0)
lines(rep(i,2),c(matches$Ph[i],matches$outcome.final[i]),type="l",lty=2,col="red")
} else if (matches$outcome.final[i]==0.5) {
lines(matches$id[i],matches$outcome.final[i],col=3,type="p",pch=1)
lines(rep(i,2),c(matches$Pd[i],matches$outcome.final[i]),type="l",lty=2,col="green")
} else {
lines(matches$id[i],matches$outcome.final[i],col=4,type="p",pch=2)
lines(rep(i,2),c(matches$Pa[i],matches$outcome.final[i]),type="l",lty=2,col="blue")
}
}
axis(1,at=matches$id,labels=paste(matches$team1,matches$team2,sep=" v "),las=2,cex.axis=0.65)
}We also load up previous weeks’ forecasts and outcomes in order that we can begin to determine trends over time. This week was one particularly filled with surprise results, but that does not necessarily mean our forecast model need be amended. More, it reflects that football is intrinsically a very uncertain game. This, of course, is not to say that the model cannot be improved upon.
First, our Premier League forecasts:
outcomeplot("English Premier")
Outcomes are hollowed variants of their predicted probabilities; red empty circles are home wins, marked on at 1, green empty circles are draws, marked on at 0.5, and blue empty triangles are away wins. All are linked to their associated probability. This drawing doesn’t quite reflect actual forecast errors since each outcome is 1 if it happened, but nonetheless illustrates the weekend’s outcomes.
Next, our Championship forecasts:
outcomeplot("English Championship")
Next, our League One forecasts:
outcomeplot("English League One")
Next, our League Two forecasts:
outcomeplot("English League Two")
Next, our Football Conference forecasts:
outcomeplot("Football Conference")
Tabular Version
Numerically it is important to evaluate forecast errors.
For the OLS model:
forecast.outcomes$error <- forecast.outcomes$outcome.final - forecast.outcomes$outcome.forc
forecast.outcomes$error2 <- forecast.outcomes$error^2
forecast.outcomes$aerror <- abs(forecast.outcomes$error)
#summary(forecast.outcomes[forecast.outcomes$tier<=5,c("error","error2","aerror")])
summary(forecast.outcomes[,c("error","error2","aerror")])## error error2 aerror
## Min. :-0.77659 Min. :0.0000238 Min. :0.004877
## 1st Qu.:-0.49458 1st Qu.:0.0356949 1st Qu.:0.188929
## Median :-0.09206 Median :0.1374032 Median :0.370679
## Mean :-0.10999 Mean :0.1794764 Mean :0.367013
## 3rd Qu.: 0.25841 3rd Qu.:0.2731278 3rd Qu.:0.522601
## Max. : 0.73313 Max. :0.6030880 Max. :0.776587For the ordered logit we must consider the three outcomes distinctly; for the home win:
forecast.outcomes$error.h <- forecast.outcomes$outcome.final - forecast.outcomes$Ph
forecast.outcomes$error.d <- as.numeric(forecast.outcomes$outcome.final==0.5) - forecast.outcomes$Pd
forecast.outcomes$error.a <- as.numeric(forecast.outcomes$outcome.final==0) - forecast.outcomes$Pa
forecast.outcomes$error.h2 <- forecast.outcomes$error.h^2
forecast.outcomes$error.d2 <- forecast.outcomes$error.d^2
forecast.outcomes$error.a2 <- forecast.outcomes$error.a^2
forecast.outcomes$aerror.h <- abs(forecast.outcomes$error.h)
forecast.outcomes$aerror.d <- abs(forecast.outcomes$error.d)
forecast.outcomes$aerror.a <- abs(forecast.outcomes$error.a)
#summary(forecast.outcomes[forecast.outcomes$tier<=5,c("error","error2","aerror")])
summary(forecast.outcomes[,c("error.h","error.d","error.a")])## error.h error.d error.a
## Min. :-0.67930 Min. :-0.28876 Min. :-0.62200
## 1st Qu.:-0.33910 1st Qu.:-0.27874 1st Qu.:-0.28633
## Median : 0.04603 Median :-0.23986 Median :-0.13806
## Mean : 0.02124 Mean : 0.03914 Mean : 0.08584
## 3rd Qu.: 0.37143 3rd Qu.: 0.71345 3rd Qu.: 0.62750
## Max. : 0.84382 Max. : 0.80695 Max. : 0.87429Considering here just the mean errors, the forecasts for home wins were biased downward much more than those for either the draw or away win; a positive forecast error suggests that the event occurs more often than the model predicts. Until we consider more forecasts, it is difficult to say whether this is simply an artifact of one particular week.
We can consider also, by division, forecast errors for our linear regression model:
library(knitr)
aggs <- aggregate(forecast.outcomes[,c("error","error2","aerror")],
by=list(forecast.outcomes$division),FUN=mean,na.rm=T)
kable(aggs[c(4,1,2,3,5),])| Group.1 | error | error2 | aerror | |
|---|---|---|---|---|
| 4 | English FA Cup | 0.4066898 | 0.1653966 | 0.4066898 |
| 1 | Conference North | 0.3249273 | 0.1055778 | 0.3249273 |
| 2 | Conference South | 0.3161500 | 0.0999508 | 0.3161500 |
| 3 | English Championship | -0.1041715 | 0.1325534 | 0.3147237 |
| 5 | English League One | -0.1827473 | 0.2146822 | 0.4039176 |
The error column is the mean forecast error, the error2 column is the mean squared forecast error, and the aerror column is the absolute forecast error.
We do the same for each outcome for the ordered probit model:
library(knitr)
aggs <- aggregate(forecast.outcomes[,c("error.h","error.h2","aerror.h")],
by=list(forecast.outcomes$division),FUN=mean,na.rm=T)
colnames(aggs) <- gsub("Group.1","Home win",colnames(aggs))
kable(aggs[c(4,1,2,3,5),])| Home win | error.h | error.h2 | aerror.h | |
|---|---|---|---|---|
| 4 | English FA Cup | 0.5386706 | 0.2901660 | 0.5386706 |
| 1 | Conference North | 0.4459522 | 0.1988734 | 0.4459522 |
| 2 | Conference South | 0.4280749 | 0.1832481 | 0.4280749 |
| 3 | English Championship | 0.0254027 | 0.1183597 | 0.3036271 |
| 5 | English League One | -0.0526060 | 0.1865225 | 0.3884213 |
aggs <- aggregate(forecast.outcomes[,c("error.d","error.d2","aerror.d")],
by=list(forecast.outcomes$division),FUN=mean,na.rm=T)
colnames(aggs) <- gsub("Group.1","Draw",colnames(aggs))
kable(aggs[c(4,1,2,3,5),])| Draw | error.d | error.d2 | aerror.d | |
|---|---|---|---|---|
| 4 | English FA Cup | -0.2763350 | 0.0763611 | 0.2763350 |
| 1 | Conference North | -0.2490700 | 0.0620359 | 0.2490700 |
| 2 | Conference South | -0.2424309 | 0.0587727 | 0.2424309 |
| 3 | English Championship | 0.1004408 | 0.2359350 | 0.4202624 |
| 5 | English League One | 0.0083516 | 0.1925225 | 0.3795346 |
aggs <- aggregate(forecast.outcomes[,c("error.a","error.a2","aerror.a")],
by=list(forecast.outcomes$division),FUN=mean,na.rm=T)
colnames(aggs) <- gsub("Group.1","Away win",colnames(aggs))
kable(aggs[c(4,1,2,3,5),])| Away win | error.a | error.a2 | aerror.a | |
|---|---|---|---|---|
| 4 | English FA Cup | -0.2623356 | 0.0688200 | 0.2623356 |
| 1 | Conference North | -0.1968822 | 0.0387626 | 0.1968822 |
| 2 | Conference South | -0.1856441 | 0.0344637 | 0.1856441 |
| 3 | English Championship | 0.0480696 | 0.2054340 | 0.3913458 |
| 5 | English League One | 0.1746892 | 0.2825975 | 0.4628295 |
We can also look at errors across weeks:
all.forecast.outcomes$error.h <- all.forecast.outcomes$outcome.final - all.forecast.outcomes$Ph
all.forecast.outcomes$error.d <- as.numeric(all.forecast.outcomes$outcome.final==0.5) - all.forecast.outcomes$Pd
all.forecast.outcomes$error.a <- as.numeric(all.forecast.outcomes$outcome.final==0) - all.forecast.outcomes$Pa
all.forecast.outcomes$error.h2 <- all.forecast.outcomes$error.h^2
all.forecast.outcomes$error.d2 <- all.forecast.outcomes$error.d^2
all.forecast.outcomes$error.a2 <- all.forecast.outcomes$error.a^2
all.forecast.outcomes$aerror.h <- abs(all.forecast.outcomes$error.h)
all.forecast.outcomes$aerror.d <- abs(all.forecast.outcomes$error.d)
all.forecast.outcomes$aerror.a <- abs(all.forecast.outcomes$error.a)
aggs.h <- aggregate(all.forecast.outcomes[,c("error.h","error.h2","aerror.h")],
by=list(all.forecast.outcomes$forc.week),FUN=mean,na.rm=T)
aggs.d <- aggregate(all.forecast.outcomes[,c("error.d","error.d2","aerror.d")],
by=list(all.forecast.outcomes$forc.week),FUN=mean,na.rm=T)
aggs.a <- aggregate(all.forecast.outcomes[,c("error.a","error.a2","aerror.a")],
by=list(all.forecast.outcomes$forc.week),FUN=mean,na.rm=T)
plot(as.Date(aggs.h$Group.1),aggs.h$error.h,type="o",main="Forecast Errors Each Week",
ylab="Forecast Error",xlab="Date",
ylim=range(c(aggs.h$error.h,aggs.d$error.d,aggs.a$error.a),na.rm=T),col="red")
lines(as.Date(aggs.d$Group.1),aggs.d$error.d,type="o",col="green")
lines(as.Date(aggs.a$Group.1),aggs.a$error.a,type="o",col="blue")
plot(as.Date(aggs.h$Group.1),aggs.h$error.h2,type="o",main="Squared Forecast Errors Each Week",
ylab="Forecast Error",xlab="Date",
ylim=range(c(aggs.h$error.h2,aggs.d$error.d2,aggs.a$error.a2),na.rm=T),col="red")
lines(as.Date(aggs.d$Group.1),aggs.d$error.d2,type="o",col="green")
lines(as.Date(aggs.a$Group.1),aggs.a$error.a2,type="o",col="blue")
plot(as.Date(aggs.h$Group.1),aggs.h$aerror.h,type="o",main="Absolute Forecast Errors Each Week",
ylab="Forecast Error",xlab="Date",
ylim=range(c(aggs.h$aerror.h,aggs.d$aerror.d,aggs.a$aerror.a),na.rm=T),col="red")
lines(as.Date(aggs.d$Group.1),aggs.d$aerror.d,type="o",col="green")
lines(as.Date(aggs.a$Group.1),aggs.a$aerror.a,type="o",col="blue")
Finally, we list all the forecasts again with outcomes:
kable(forecast.outcomes[order(forecast.outcomes$date,forecast.outcomes$division),
c("date","division","team1","goals1","goals2","team2",
"outcome.forc","Ph","Pd","Pa","outcome.final","error","error2","aerror")],digits=3)| date | division | team1 | goals1 | goals2 | team2 | outcome.forc | Ph | Pd | Pa | outcome.final | error | error2 | aerror | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 70 | 2015-03-13 | English League Two | Newport Co | 1 | 1 | Cheltenham | 0.723 | 0.609 | 0.227 | 0.163 | 0.5 | -0.223 | 0.050 | 0.223 |
| 102 | 2015-03-14 | Conference North | Bradford PA | 1 | 0 | Stalybridge | 0.675 | 0.554 | 0.249 | 0.197 | 1.0 | 0.325 | 0.106 | 0.325 |
| 101 | 2015-03-14 | Conference South | Hayes & Y | 3 | 0 | Farnborough | 0.684 | 0.572 | 0.242 | 0.186 | 1.0 | 0.316 | 0.100 | 0.316 |
| 12 | 2015-03-14 | English Championship | Leeds | 0 | 0 | Nottm Forest | 0.629 | 0.494 | 0.268 | 0.238 | 0.5 | -0.129 | 0.017 | 0.129 |
| 15 | 2015-03-14 | English Championship | Watford | 4 | 1 | Reading | 0.828 | 0.740 | 0.163 | 0.097 | 1.0 | 0.172 | 0.030 | 0.172 |
| 20 | 2015-03-14 | English Championship | Charlton | 1 | 3 | Blackburn | 0.530 | 0.378 | 0.288 | 0.334 | 0.0 | -0.530 | 0.281 | 0.530 |
| 21 | 2015-03-14 | English Championship | Birmingham | 1 | 1 | Huddersfield | 0.789 | 0.681 | 0.194 | 0.125 | 0.5 | -0.289 | 0.083 | 0.289 |
| 24 | 2015-03-14 | English Championship | Middlesbro | 4 | 1 | Ipswich | 0.690 | 0.570 | 0.243 | 0.187 | 1.0 | 0.310 | 0.096 | 0.310 |
| 26 | 2015-03-14 | English Championship | Rotherham | 1 | 2 | Wigan | 0.516 | 0.358 | 0.289 | 0.354 | 0.0 | -0.516 | 0.266 | 0.516 |
| 27 | 2015-03-14 | English Championship | Bolton | 2 | 0 | Millwall | 0.778 | 0.673 | 0.198 | 0.129 | 1.0 | 0.222 | 0.049 | 0.222 |
| 28 | 2015-03-14 | English Championship | Norwich | 1 | 1 | Derby | 0.701 | 0.586 | 0.237 | 0.177 | 0.5 | -0.201 | 0.040 | 0.201 |
| 29 | 2015-03-14 | English Championship | Bournemouth | 4 | 0 | Blackpool | 0.898 | 0.823 | 0.116 | 0.061 | 1.0 | 0.102 | 0.010 | 0.102 |
| 32 | 2015-03-14 | English Championship | Sheff Wed | 1 | 1 | Fulham | 0.653 | 0.526 | 0.259 | 0.215 | 0.5 | -0.153 | 0.023 | 0.153 |
| 33 | 2015-03-14 | English Championship | Brighton | 1 | 1 | Wolves | 0.505 | 0.352 | 0.289 | 0.359 | 0.5 | -0.005 | 0.000 | 0.005 |
| 34 | 2015-03-14 | English Championship | Brentford | 1 | 2 | Cardiff | 0.642 | 0.514 | 0.262 | 0.224 | 0.0 | -0.642 | 0.413 | 0.642 |
| 36 | 2015-03-14 | English League One | Port Vale | 0 | 1 | Swindon | 0.544 | 0.398 | 0.287 | 0.315 | 0.0 | -0.544 | 0.296 | 0.544 |
| 38 | 2015-03-14 | English League One | Doncaster | 0 | 2 | Peterborough | 0.562 | 0.415 | 0.285 | 0.301 | 0.0 | -0.562 | 0.316 | 0.562 |
| 41 | 2015-03-14 | English League One | Scunthorpe | 1 | 1 | Sheff Utd | 0.572 | 0.430 | 0.282 | 0.287 | 0.5 | -0.072 | 0.005 | 0.072 |
| 46 | 2015-03-14 | English League One | Notts Co | 1 | 1 | Bradford | 0.449 | 0.290 | 0.283 | 0.427 | 0.5 | 0.051 | 0.003 | 0.051 |
| 49 | 2015-03-14 | English League One | Oldham | 1 | 3 | Barnsley | 0.465 | 0.309 | 0.286 | 0.405 | 0.0 | -0.465 | 0.216 | 0.465 |
| 50 | 2015-03-14 | English League One | Colchester | 2 | 3 | Crawley | 0.543 | 0.395 | 0.287 | 0.318 | 0.0 | -0.543 | 0.295 | 0.543 |
| 51 | 2015-03-14 | English League One | Preston | 5 | 1 | Crewe | 0.810 | 0.727 | 0.170 | 0.102 | 1.0 | 0.190 | 0.036 | 0.190 |
| 52 | 2015-03-14 | English League One | Bristol C | 0 | 0 | Gillingham | 0.765 | 0.668 | 0.200 | 0.131 | 0.5 | -0.265 | 0.070 | 0.265 |
| 53 | 2015-03-14 | English League One | Fleetwood | 1 | 0 | Rochdale | 0.501 | 0.343 | 0.289 | 0.369 | 1.0 | 0.499 | 0.249 | 0.499 |
| 54 | 2015-03-14 | English League One | Walsall | 1 | 1 | MK Dons | 0.761 | 0.655 | 0.207 | 0.138 | 0.5 | -0.261 | 0.068 | 0.261 |
| 55 | 2015-03-14 | English League One | Chesterfield | 2 | 3 | Coventry | 0.754 | 0.645 | 0.211 | 0.143 | 0.0 | -0.754 | 0.569 | 0.754 |
| 56 | 2015-03-14 | English League One | Leyton Orient | 3 | 0 | Yeovil | 0.666 | 0.547 | 0.251 | 0.201 | 1.0 | 0.334 | 0.111 | 0.334 |
| 58 | 2015-03-14 | English League Two | Northampton | 1 | 0 | Tranmere | 0.826 | 0.723 | 0.172 | 0.104 | 1.0 | 0.174 | 0.030 | 0.174 |
| 59 | 2015-03-14 | English League Two | Wycombe | 1 | 0 | Shrewsbury | 0.554 | 0.403 | 0.286 | 0.311 | 1.0 | 0.446 | 0.199 | 0.446 |
| 60 | 2015-03-14 | English League Two | York | 0 | 0 | Carlisle | 0.678 | 0.559 | 0.247 | 0.194 | 0.5 | -0.178 | 0.032 | 0.178 |
| 62 | 2015-03-14 | English League Two | Morecambe | 0 | 1 | Hartlepool | 0.680 | 0.568 | 0.244 | 0.188 | 0.0 | -0.680 | 0.462 | 0.680 |
| 63 | 2015-03-14 | English League Two | Cambridge U | 1 | 1 | Stevenage | 0.475 | 0.322 | 0.287 | 0.391 | 0.5 | 0.025 | 0.001 | 0.025 |
| 64 | 2015-03-14 | English League Two | Dag & Red | 1 | 3 | Southend | 0.525 | 0.374 | 0.288 | 0.338 | 0.0 | -0.525 | 0.276 | 0.525 |
| 65 | 2015-03-14 | English League Two | Exeter | 3 | 2 | AFC W’bledon | 0.671 | 0.545 | 0.252 | 0.203 | 1.0 | 0.329 | 0.109 | 0.329 |
| 66 | 2015-03-14 | English League Two | Mansfield | 0 | 1 | Bury | 0.544 | 0.395 | 0.287 | 0.318 | 0.0 | -0.544 | 0.296 | 0.544 |
| 67 | 2015-03-14 | English League Two | Burton | 3 | 0 | Accrington | 0.769 | 0.666 | 0.202 | 0.133 | 1.0 | 0.231 | 0.053 | 0.231 |
| 75 | 2015-03-14 | English League Two | Portsmouth | 2 | 0 | Luton | 0.515 | 0.362 | 0.289 | 0.349 | 1.0 | 0.485 | 0.235 | 0.485 |
| 78 | 2015-03-14 | English League Two | Oxford | 0 | 0 | Plymouth | 0.567 | 0.420 | 0.284 | 0.296 | 0.5 | -0.067 | 0.004 | 0.067 |
| 1 | 2015-03-14 | English Premier | C Palace | 3 | 1 | QPR | 0.720 | 0.609 | 0.228 | 0.164 | 1.0 | 0.280 | 0.078 | 0.280 |
| 4 | 2015-03-14 | English Premier | West Brom | 1 | 0 | Stoke | 0.448 | 0.291 | 0.283 | 0.426 | 1.0 | 0.552 | 0.305 | 0.552 |
| 5 | 2015-03-14 | English Premier | Arsenal | 3 | 0 | West Ham | 0.820 | 0.721 | 0.173 | 0.105 | 1.0 | 0.180 | 0.032 | 0.180 |
| 6 | 2015-03-14 | English Premier | Sunderland | 0 | 4 | Aston Villa | 0.528 | 0.378 | 0.288 | 0.334 | 0.0 | -0.528 | 0.279 | 0.528 |
| 7 | 2015-03-14 | English Premier | Burnley | 1 | 0 | Man City | 0.267 | 0.156 | 0.222 | 0.622 | 1.0 | 0.733 | 0.537 | 0.733 |
| 11 | 2015-03-14 | English Premier | Leicester | 0 | 0 | Hull | 0.546 | 0.398 | 0.287 | 0.315 | 0.5 | -0.046 | 0.002 | 0.046 |
| 82 | 2015-03-14 | Football Conference | Halifax | 2 | 2 | Bristol R | 0.421 | 0.263 | 0.277 | 0.460 | 0.5 | 0.079 | 0.006 | 0.079 |
| 83 | 2015-03-14 | Football Conference | Gateshead | 2 | 1 | Macclesfield | 0.511 | 0.358 | 0.289 | 0.354 | 1.0 | 0.489 | 0.239 | 0.489 |
| 84 | 2015-03-14 | Football Conference | Telford | 1 | 3 | Woking | 0.334 | 0.200 | 0.251 | 0.549 | 0.0 | -0.334 | 0.112 | 0.334 |
| 85 | 2015-03-14 | Football Conference | Aldershot | 1 | 2 | Southport | 0.625 | 0.494 | 0.268 | 0.238 | 0.0 | -0.625 | 0.390 | 0.625 |
| 87 | 2015-03-14 | Football Conference | Altrincham | 1 | 4 | Wrexham | 0.579 | 0.432 | 0.282 | 0.286 | 0.0 | -0.579 | 0.335 | 0.579 |
| 88 | 2015-03-14 | Football Conference | Dartford | 0 | 1 | Alfreton | 0.487 | 0.333 | 0.288 | 0.378 | 0.0 | -0.487 | 0.237 | 0.487 |
| 89 | 2015-03-14 | Football Conference | Nuneaton | 0 | 0 | Torquay | 0.520 | 0.372 | 0.288 | 0.339 | 0.5 | -0.020 | 0.000 | 0.020 |
| 90 | 2015-03-14 | Football Conference | Eastleigh | 1 | 2 | Barnet | 0.608 | 0.473 | 0.274 | 0.253 | 0.0 | -0.608 | 0.369 | 0.608 |
| 91 | 2015-03-14 | Football Conference | Forest Green | 1 | 1 | Braintree | 0.783 | 0.679 | 0.195 | 0.126 | 0.5 | -0.283 | 0.080 | 0.283 |
| 94 | 2015-03-14 | Football Conference | Kidderminster | 0 | 2 | Dover | 0.595 | 0.451 | 0.279 | 0.270 | 0.0 | -0.595 | 0.354 | 0.595 |
| 97 | 2015-03-14 | Football Conference | Lincoln | 0 | 2 | Welling | 0.742 | 0.631 | 0.218 | 0.151 | 0.0 | -0.742 | 0.550 | 0.742 |
| 98 | 2015-03-14 | Football Conference | Chester | 2 | 2 | Grimsby | 0.452 | 0.296 | 0.284 | 0.420 | 0.5 | 0.048 | 0.002 | 0.048 |
| 103 | 2015-03-14 | Ryman Premier | Canvey Isl. | 2 | 2 | Margate | 0.474 | 0.315 | 0.287 | 0.399 | 0.5 | 0.026 | 0.001 | 0.026 |
| 104 | 2015-03-14 | Ryman Premier | Maidstone | 2 | 1 | Lewes | 0.779 | 0.698 | 0.185 | 0.116 | 1.0 | 0.221 | 0.049 | 0.221 |
| 2 | 2015-03-15 | English Premier | Everton | 3 | 0 | Newcastle | 0.501 | 0.350 | 0.289 | 0.361 | 1.0 | 0.499 | 0.249 | 0.499 |
| 3 | 2015-03-15 | English Premier | Chelsea | 1 | 1 | Southampton | 0.762 | 0.656 | 0.206 | 0.138 | 0.5 | -0.262 | 0.069 | 0.262 |
| 10 | 2015-03-15 | English Premier | Man Utd | 3 | 0 | Tottenham | 0.654 | 0.531 | 0.257 | 0.212 | 1.0 | 0.346 | 0.120 | 0.346 |
| 105 | 2015-03-16 | English FA Cup | Reading | 3 | 0 | Bradford | 0.593 | 0.461 | 0.276 | 0.262 | 1.0 | 0.407 | 0.165 | 0.407 |
| 106 | 2015-03-16 | English FA Cup | Reading | 3 | 0 | Bradford | 0.593 | 0.461 | 0.276 | 0.262 | 1.0 | 0.407 | 0.165 | 0.407 |
| 8 | 2015-03-16 | English Premier | Swansea | 0 | 1 | Liverpool | 0.370 | 0.219 | 0.260 | 0.520 | 0.0 | -0.370 | 0.137 | 0.370 |
| 9 | 2015-03-16 | English Premier | Swansea | 0 | 1 | Liverpool | 0.370 | 0.219 | 0.260 | 0.520 | 0.0 | -0.370 | 0.137 | 0.370 |
| 13 | 2015-03-17 | English Championship | Cardiff | 1 | 1 | Bournemouth | 0.347 | 0.206 | 0.254 | 0.540 | 0.5 | 0.153 | 0.023 | 0.153 |
| 14 | 2015-03-17 | English Championship | Wigan | 0 | 2 | Watford | 0.374 | 0.232 | 0.266 | 0.502 | 0.0 | -0.374 | 0.140 | 0.374 |
| 16 | 2015-03-17 | English Championship | Wolves | 3 | 0 | Sheff Wed | 0.610 | 0.470 | 0.274 | 0.255 | 1.0 | 0.390 | 0.152 | 0.390 |
| 18 | 2015-03-17 | English Championship | Derby | 0 | 1 | Middlesbro | 0.496 | 0.341 | 0.288 | 0.371 | 0.0 | -0.496 | 0.246 | 0.496 |
| 19 | 2015-03-17 | English Championship | Blackburn | 2 | 3 | Brentford | 0.704 | 0.585 | 0.237 | 0.178 | 0.0 | -0.704 | 0.496 | 0.704 |
| 22 | 2015-03-17 | English Championship | Blackpool | 0 | 3 | Charlton | 0.289 | 0.164 | 0.228 | 0.607 | 0.0 | -0.289 | 0.084 | 0.289 |
| 25 | 2015-03-17 | English Championship | Millwall | 0 | 0 | Brighton | 0.401 | 0.245 | 0.271 | 0.484 | 0.5 | 0.099 | 0.010 | 0.099 |
| 30 | 2015-03-17 | English Championship | Huddersfield | 2 | 2 | Norwich | 0.312 | 0.182 | 0.240 | 0.577 | 0.5 | 0.188 | 0.036 | 0.188 |
| 31 | 2015-03-17 | English Championship | Ipswich | 1 | 0 | Bolton | 0.552 | 0.412 | 0.285 | 0.303 | 1.0 | 0.448 | 0.201 | 0.448 |
| 35 | 2015-03-17 | English League One | Chesterfield | 3 | 0 | Gillingham | 0.599 | 0.459 | 0.277 | 0.264 | 1.0 | 0.401 | 0.161 | 0.401 |
| 37 | 2015-03-17 | English League One | Oldham | 1 | 3 | MK Dons | 0.756 | 0.651 | 0.209 | 0.141 | 0.0 | -0.756 | 0.572 | 0.756 |
| 39 | 2015-03-17 | English League One | Preston | 2 | 0 | Peterborough | 0.629 | 0.503 | 0.266 | 0.231 | 1.0 | 0.371 | 0.138 | 0.371 |
| 40 | 2015-03-17 | English League One | Leyton Orient | 0 | 0 | Barnsley | 0.440 | 0.287 | 0.282 | 0.431 | 0.5 | 0.060 | 0.004 | 0.060 |
| 42 | 2015-03-17 | English League One | Notts Co | 1 | 2 | Rochdale | 0.425 | 0.267 | 0.278 | 0.455 | 0.0 | -0.425 | 0.180 | 0.425 |
| 43 | 2015-03-17 | English League One | Port Vale | 2 | 3 | Crawley | 0.728 | 0.619 | 0.223 | 0.158 | 0.0 | -0.728 | 0.530 | 0.728 |
| 44 | 2015-03-17 | English League One | Bristol C | 3 | 0 | Crewe | 0.848 | 0.773 | 0.145 | 0.082 | 1.0 | 0.152 | 0.023 | 0.152 |
| 45 | 2015-03-17 | English League One | Doncaster | 1 | 2 | Swindon | 0.640 | 0.509 | 0.264 | 0.227 | 0.0 | -0.640 | 0.410 | 0.640 |
| 47 | 2015-03-17 | English League One | Fleetwood | 0 | 2 | Coventry | 0.668 | 0.540 | 0.254 | 0.206 | 0.0 | -0.668 | 0.446 | 0.668 |
| 48 | 2015-03-17 | English League One | Colchester | 2 | 0 | Yeovil | 0.515 | 0.362 | 0.289 | 0.349 | 1.0 | 0.485 | 0.235 | 0.485 |
| 57 | 2015-03-17 | English League One | Walsall | 1 | 1 | Sheff Utd | 0.562 | 0.415 | 0.285 | 0.300 | 0.5 | -0.062 | 0.004 | 0.062 |
| 61 | 2015-03-17 | English League Two | Newport Co | 1 | 0 | Luton | 0.582 | 0.436 | 0.281 | 0.283 | 1.0 | 0.418 | 0.175 | 0.418 |
| 68 | 2015-03-17 | English League Two | Wycombe | 2 | 2 | Accrington | 0.782 | 0.683 | 0.193 | 0.124 | 0.5 | -0.282 | 0.080 | 0.282 |
| 69 | 2015-03-17 | English League Two | Mansfield | 2 | 1 | AFC W’bledon | 0.733 | 0.616 | 0.224 | 0.160 | 1.0 | 0.267 | 0.072 | 0.267 |
| 71 | 2015-03-17 | English League Two | Morecambe | 1 | 4 | Shrewsbury | 0.415 | 0.258 | 0.275 | 0.467 | 0.0 | -0.415 | 0.172 | 0.415 |
| 72 | 2015-03-17 | English League Two | Portsmouth | 2 | 2 | Cheltenham | 0.653 | 0.529 | 0.258 | 0.213 | 0.5 | -0.153 | 0.023 | 0.153 |
| 73 | 2015-03-17 | English League Two | York | 0 | 1 | Bury | 0.469 | 0.313 | 0.286 | 0.400 | 0.0 | -0.469 | 0.220 | 0.469 |
| 74 | 2015-03-17 | English League Two | Exeter | 0 | 0 | Stevenage | 0.469 | 0.313 | 0.286 | 0.401 | 0.5 | 0.031 | 0.001 | 0.031 |
| 76 | 2015-03-17 | English League Two | Northampton | 0 | 2 | Carlisle | 0.777 | 0.679 | 0.195 | 0.126 | 0.0 | -0.777 | 0.603 | 0.777 |
| 77 | 2015-03-17 | English League Two | Dag & Red | 2 | 0 | Plymouth | 0.591 | 0.450 | 0.279 | 0.272 | 1.0 | 0.409 | 0.167 | 0.409 |
| 79 | 2015-03-17 | English League Two | Oxford | 0 | 2 | Hartlepool | 0.715 | 0.608 | 0.228 | 0.164 | 0.0 | -0.715 | 0.511 | 0.715 |
| 81 | 2015-03-17 | English League Two | Cambridge U | 1 | 2 | Tranmere | 0.740 | 0.629 | 0.219 | 0.152 | 0.0 | -0.740 | 0.548 | 0.740 |
| 86 | 2015-03-17 | Football Conference | Chester | 1 | 2 | Dartford | 0.743 | 0.631 | 0.218 | 0.151 | 0.0 | -0.743 | 0.551 | 0.743 |
| 92 | 2015-03-17 | Football Conference | Halifax | 1 | 1 | Barnet | 0.423 | 0.266 | 0.277 | 0.457 | 0.5 | 0.077 | 0.006 | 0.077 |
| 93 | 2015-03-17 | Football Conference | Telford | 0 | 1 | Gateshead | 0.414 | 0.266 | 0.277 | 0.456 | 0.0 | -0.414 | 0.171 | 0.414 |
| 95 | 2015-03-17 | Football Conference | Alfreton | 0 | 0 | Lincoln | 0.612 | 0.478 | 0.272 | 0.250 | 0.5 | -0.112 | 0.012 | 0.112 |
| 96 | 2015-03-17 | Football Conference | Torquay | 1 | 5 | Braintree | 0.586 | 0.444 | 0.280 | 0.276 | 0.0 | -0.586 | 0.343 | 0.586 |
| 99 | 2015-03-17 | Football Conference | Dover | 2 | 1 | Altrincham | 0.552 | 0.413 | 0.285 | 0.302 | 1.0 | 0.448 | 0.201 | 0.448 |
| 100 | 2015-03-17 | Football Conference | Eastleigh | 2 | 2 | Wrexham | 0.747 | 0.644 | 0.212 | 0.144 | 0.5 | -0.247 | 0.061 | 0.247 |
| 17 | 2015-03-18 | English Championship | Nottm Forest | 2 | 0 | Rotherham | 0.664 | 0.548 | 0.251 | 0.201 | 1.0 | 0.336 | 0.113 | 0.336 |
| 23 | 2015-03-18 | English Championship | Fulham | 0 | 3 | Leeds | 0.490 | 0.334 | 0.288 | 0.377 | 0.0 | -0.490 | 0.240 | 0.490 |
| 80 | 2015-03-18 | English League Two | Burton | 2 | 1 | Southend | 0.591 | 0.448 | 0.279 | 0.273 | 1.0 | 0.409 | 0.168 | 0.409 |