Least squares regression is used to model the first innings performances of teams in test cricket in order to establish batting and bowling ratings, a common home advan- tage and a country effect. Logistic regression techniques are then used to model match outcomes based on a team’s first innings lead, innings duration, home advantage, bat- ting and bowling ratings and the country effect. It is shown that the factors that impact most significantly on the outcome of a match are a team’s first innings lead home team performance and innings duration. A team’s first innings lead is found to more likely shape a win rather than a draw or a loss whereas the longer the duration of the first innings the more likely a match will end in a draw. It is shown that the home team, on average, needs to establish a lead in excess of 93 runs to have a better than even chance of winning, whereas the away team needs to establish a lead in excess of 115 runs to have the same chance. There is a better than an even chance of a draw for a first innings duration in excess of 1165 minutes (or approximately 277 overs). It is also shown that the home team is more likely to win a match rather than lose or draw, which suggests that the home team has a distinct winning advantage over the away team. There is some evidence suggesting that teams gained an advantage by batting last.