This MT241 Unit 3 descriptive analysis sets one composite NHL club's December streak against its other seventy games and credits most of it to saves. Searches like "mt 241 unit 3 assignment example", "mt241 unit 3 sample" and "mt241 unit 3 example" land here.
What a finished MT241 Unit 3 descriptive analysis looks like
Five pages: a season summary table, a game-by-game chart, a segment table and an appendix holding a forty-line Python script that reads the game log and produces every number. The summary reports a 5-on-5 shot-attempt share of 49.2 percent and an expected-goals share of 50.8 across the season, with a median game at 50.9 and a standard deviation of 9.8 points between games. The segment table sets the twelve-game run beside the other seventy: expected-goals share 48.4 against 51.2, shooting percentage 10.3 against 7.8, save percentage .939 against .916. PDO, the sum of those last two, reads 104.2 during the run and 99.4 outside it. The chart plots each game's expected-goals share with a ten-game rolling mean, the run shaded.
How a MT241 Unit 3 example is structured
Description leads and interpretation follows, in separate sections, so a reader can check one against the other. The season comes first as a whole, because a run means nothing until the reader knows what normal looks like for this club. Every figure carries its denominator, and the script is cited beside each table, so a grader can rerun the analysis. The segment comparison follows, with the run defined by its dates and an admission that picking a stretch because it went well selects for luck. PDO is introduced as the sum of shooting and save percentages, its tendency to settle near 100 stated as a pattern in league data rather than a law. Context closes the description: seven of the twelve games were at home, against opponents with a combined points percentage of .478. The summary sentence claims only what the tables show.
The season before the streak
Eighty-two games at 5-on-5 give a 49.2 percent attempt share and 50.8 percent of expected goals. Game-to-game spread is wide, a standard deviation near 9.8 points, which sets how unusual any twelve-game stretch can look.
A script behind every figure
Pandas reads the league game log, filters to 5-on-5, computes shares, percentages and rolling means, and writes each table. The appendix prints the script so a reader can rerun it rather than trust the arithmetic.
Twelve games against seventy
During the run the club generated 48.4 percent of expected goals, slightly worse than its 51.2 elsewhere. Shooting at 10.3 percent and goaltending at .939 carried the results, both well above the club's rates outside December.
PDO as a signal, not a verdict
Shooting plus save percentage read 104.2 across the run. Team figures that high have usually drifted back toward 100 over following months, and the analysis states that as a tendency in league data, not a forecast for this club.
Schedule and a selection caveat
Seven home games and opponents with a combined .478 points percentage eased the run. Choosing a stretch because it went well also builds some good fortune into the comparison, and the paper says so beside the table.
Where marks go in MT241 Unit 3
Graders in MT241 mark down a Unit 3 analysis that adopts the columnist's frame, a team transformed, and then finds numbers to fit it; the unit asks for the season described first and the run placed inside it. Results reported without process, wins and points with no shot or chance figures, cannot separate performance from fortune. Percentages without denominators draw deductions, as does arithmetic done by hand where the prompt asked for a script or spreadsheet a reader could rerun. Many drafts compare the run with the whole season, run included, which blurs the gap they mean to measure. Treating PDO as proof the club will decline oversteps the same way the columnist did. A summary sentence longer on adjectives than on figures signals the description never settled.
Get a MT241 Unit 3 example written to your instructions
Send the season, team or dataset your Unit 3 prompt names, whether a game log it supplies or one you choose, and the rubric. The first custom analysis costs nothing and arrives in 24-48h, the whole season described before any run is singled out, and a short script included where the course expects figures computed rather than typed.
MT241 Unit 3 questions, answered
What is PDO in hockey analytics?
The sum of a team's or player's shooting percentage and save percentage, usually at 5-on-5, on a scale where 100 sits near league average. Values far above or below 100 over short stretches tend to move back toward it, because neither percentage is fully controlled by the skaters. Analysts use it as a flag for luck, not as a measure of quality.
Why include the script in a descriptive analysis?
Because MT241 treats analysis as something another person should be able to reproduce. A short script, in Python, R or a spreadsheet with visible formulas, shows how each number was made and lets a grader check a filter or a denominator. The example prints forty lines in an appendix; some sections ask for the file itself as an attachment.
How long does a stretch have to be before it means something?
Longer than most fans expect. In hockey, shot-attempt share settles faster than goal-based measures because it counts many more events, while shooting and save percentages need far larger samples. A twelve-game run can show a real change in process if shot or chance share moves, but results alone over that length mostly reflect variation.