model
{
	Tau <- 20
	for (j in 1:N.loser) {
		B1 ~ dbern(win1[j])
		B2[j] ~ dbern(win2[j])
		logit(win1[j]) <- x[T.b1, Loser[j]] - x[T.b1, Winner1[j]]
		logit(win2[j]) <- x[T.b2[j], Loser[j]] - x[T.b2[j], Winner2[j]]
		for (t in 1:T.max) {
			x[t, Loser[j]] ~ dnorm(meanL[t], Tau)
			x[t, Winner1[j]] ~ dnorm(0.0, Tau)
		}
	}
	meanL[T.b1] <- 0.0
	meanL[T.b1 + 1] <- ab
	for (t in 3:T.max) {
		meanL[t] <- meanL[t - 1] * a
	}
	logit(a) <- logit.a
	logit.a ~ dnorm(0.0, 1.0E-4)
	ab ~ dnorm(0.0, 1.0E-4)
}