The　bootstrap　interval　is　an　efficient　procedure　to　estimate　parameters.　The　coverage　probability　and　expected　length　are　crucial　to　evaluate　the　reliability　and　accuracy　of　a　confidence　interval.　How　to　compute　them　for　a　bootstrap　interval　at　a　given　parameter　configuration　for　a　fixed　sample　size?　In　this　paper,　we　offer　the　first　attempt　at　computing　the　two　quantities　of　percentile　bootstrap　intervals　by　exact　probabilistic　calculation.　This　method　is　applied　to　ten　basic　bootstrap　intervals　for　six　important　parameters.　Interestingly,　we　find　that　some　1-alpha　bootstrap　intervals　are　narrower　than　the　optimal　1-alpha　z-interval　or　t-interval.