| Course | MT241 Sport Analytics |
|---|---|
| Unit | Unit 9 |
| Paper type | Recruitment recommendation |
| Length | About 1,130 words, 7 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Business Administration |
| Updated | October 2026 |
Free sample paper for MT241 Unit 9
Three Left-Shot Defensemen and $4.5 Million: A Unit 9 Recruitment Recommendation Read Against Their Teams
[Student Name]
Purdue University Global
MT241: Sport Analytics
Unit 9 Recruitment Recommendation
[Instructor Name]
[Date]
The club, the three candidates, their teams and every figure are composite and illustrative; the sources cited are real.
The Need
Our composite club's left-shot defenseman on the second pair is leaving in free agency, and the club has about $4.5 million of room under the salary cap for next season. The coaches want a defenseman who can play about 18 minutes a night at 5-on-5, take a regular turn on the penalty kill and move the puck out of the defensive zone under pressure. The club's own data from earlier units show its biggest weakness was chances allowed after failed exits, so the need is defensive more than offensive.
The Candidates
Three left-shot defensemen fit the cap room. The table summarizes three seasons of 5-on-5 data for each.
Candidate A, 27, on a club that missed the playoffs each year: 3,410 minutes; on-ice expected goals against 2.22 per 60; his club without him 2.58 per 60; 61 points over three seasons
Candidate B, 31, on a club that won two division titles: 3,620 minutes; plus 22 last season with 38 points; on-ice expected goals against 2.31 per 60; his club without him 2.27 per 60
Candidate C, 24, on a rebuilding club: 1,020 minutes over two partial seasons; on-ice expected goals against 2.40 per 60; his club without him 2.65 per 60
Raw numbers favor Candidate B. He had the best plus-minus and the most points last season, and he played on the strongest team. But as Unit 1 showed, plus-minus counts goals while a player is on the ice, including the work of his teammates and goaltender, and a strong team lifts every player's totals.
Reading Each Player Against His Team
The fairer comparison sets each player's on-ice results beside his own team's results when he was on the bench. This removes much of the effect of the team around him.
Candidate A's club allowed 2.58 expected goals per 60 minutes without him and 2.22 with him, a reduction of 0.36. On a weak team, he made the defense noticeably better.
Candidate B's club allowed 2.27 without him and 2.31 with him. His team was slightly better at preventing chances when he sat. His plus 22 came mostly from his team's scoring and goaltending; the plus-minus trap from Unit 1 applies to him directly.
Candidate C's club allowed 2.65 without him and 2.40 with him, a reduction of 0.25, promising but based on fewer than a third of the minutes the others played.
On a strong team a defenseman can look excellent while the team plays slightly better without him.
Why Three Seasons
The comparison uses three seasons rather than one because a defenseman's on-ice numbers vary widely from year to year with partners, coaches and luck. One season of about 1,100 minutes can show a defenseman as much better or worse than he is. Three seasons give each established candidate more than 3,400 minutes, enough to reduce that noise substantially. Candidate C's 1,020 minutes carry roughly the uncertainty of a single season, so his figures are the least settled of the three.
What the Numbers Leave Out
Expected goals against measures the chances allowed while a defenseman is on the ice, but not every part of the job the coaches described. The penalty kill is one gap: Candidate A killed penalties for a club with a poor penalty kill, and his short-handed numbers are worse than his even-strength ones, though the same team adjustment suggests he was not the cause. Puck movement is another. The club's own video staff watched twenty of each candidate's games and counted successful exits under pressure; Candidate A completed about 71 percent, Candidate B 68 and Candidate C 64. Alamar (2013) argues that data should narrow a decision and the scouts' judgment should finish it, and the video count is where the two meet.
Aging
Age changes the picture for a contract that runs several years. Studies of NHL career curves suggest that skaters' results tend to peak in the mid-twenties and decline gradually after about 28, with defensemen declining steadily through their early thirties (Brander et al., 2014). Candidate B, at 31, is likely to be past his peak by the second year of a new contract. Candidate A, at 27, should hold his level for two or three more seasons. Candidate C, at 24, may still improve, but the club would be paying for growth it has not yet seen.
Cost and Contract
All three fit the cap room. Candidate A is expected to ask for about $4.2 million a year, Candidate B about $4.5 million and Candidate C about $2.8 million. Albert et al. (2017) note that front offices increasingly use analytics to judge whether a player's past results are likely to continue under a new contract, and the aging evidence is the strongest reason to limit any term offered. The recommended offer for Candidate A is four years at no more than $4.3 million a year, which keeps him under contract through his age-31 season and leaves the club a small cushion under the cap.
Recommendation
The club should sign Candidate A. He made a weak defense better by a meaningful margin over three seasons, his age fits a four-year contract, and his cost fits the cap room. Candidate B's raw numbers are the best of the three, but his team was slightly better without him and he is likely to decline over the term. Candidate C is a reasonable alternative if Candidate A signs elsewhere, but his sample is too small to rely on as the first choice.
Risk Register
Four things could make the signing fail. Each comes with an early warning sign the club can watch for.
1. His results depended on his former partner. Warning sign: his on-ice expected goals against with his new partner stays above 2.5 per 60 after 20 games.
2. His defensive numbers reflect his former coach's system. Warning sign: his share of defensive-zone starts falls sharply and his results worsen in those minutes.
3. His decline arrives early. Warning sign: his skating speed in the club's tracking data falls in the second season.
4. Injury. Warning sign: a missed month in either of his first two seasons, which would also shorten the useful part of the contract.
Conclusion
The candidate with the best raw numbers is not the best fit once each player is read against his team and his age. Candidate A offers the strongest evidence of defensive value, at an age and price the club can carry for four years.
References
Alamar, B. C. (2013). Sports analytics: A guide for coaches, managers, and other decision makers. Columbia University Press.
Albert, J., Glickman, M. E., Swartz, T. B., & Koning, R. H. (Eds.). (2017). Handbook of statistical methods and analyses in sports. CRC Press. https://doi.org/10.1201/9781315166070
Brander, J. A., Egan, E. J., & Yeung, L. (2014). Estimating the effects of age on NHL player performance. Journal of Quantitative Analysis in Sports, 10(2), 241-259. https://doi.org/10.1515/jqas-2013-0085
MT241 Unit 9 instructions, in plain terms
Unit 9 asks students to recommend a player acquisition from a short list, using data to judge each candidate against the team's need and budget. Start by stating the need, the position, the role and the cap room. The prompt expects candidates compared fairly, which usually means adjusting for the teams they played on and using more than one season. Age and contract length should enter the decision, and a recommendation must name one player and terms. Stronger papers list the ways the signing could fail and how the club would notice early. About six pages is typical, in APA 7 with tables, citing the course text and at least two sources on player evaluation or aging.
Inside the MT241 Unit 9 example
The recommendation opens on the departing defenseman, the cap room and a defensive need tied to failed exits. The candidate table sets out minutes, on-ice and off-ice expected goals against and points, and a paragraph recalls the Unit 1 lesson on plus-minus. Each player is then read against his own team, with the highlighted line on a strong team that plays better without its defenseman and a margin note on why the off-ice figure matters. Sections explain the three-season window, what the numbers miss, including exit percentages from the video staff and Alamar on scouts, and aging with Brander and colleagues. Cost and contract terms lead to the recommendation, and a risk register with warning signs ends with a final note.
Reading the MT241 Unit 9 grading rubric
Recruitment papers are marked on fit to the stated need, fairness of the comparison, use of age and contract evidence, and the quality of the recommendation. Comparisons earn more when each candidate is read against his team than when raw totals are ranked. Using several seasons and saying why shows awareness of noise. Graders reward attention to aging and to the length and cost of the contract, since a signing is a multi-year decision. The recommendation should name a player and terms and explain why the alternatives fall short. A risk register with measurable warning signs, clear tables and accurate APA references complete the rubric.
MT241 Unit 9 help from the desk
Many students rank candidates on points or plus-minus alone, which favors players on strong teams. Another weakness is ignoring age, so a 31-year-old's last season is treated as a guide to the next four. Some papers recommend the best player without checking the cap room or role. Others list risks with no way to detect them. Be consistent about whether figures are per 60 or totals, and say how many minutes sit behind each candidate's numbers, since a short sample can make a young player look better or worse than he is. If your prompt gives real free agents, our writers can help you pull their on-ice and off-ice figures and build the register of risks around them.
Get an MT241 Unit 9 example written to your instructions
Unit 9 cases vary: a free agent, a draft pick, a transfer target, a college recruit. Say which yours is and send the candidates and data it provides, plus the rubric. A first custom recommendation, free and back in 24-48h, reads each candidate in team context, commits to one, and sets out the risks with signs to watch. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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MT241 Unit 9 questions, answered
Why use three seasons of data for a signing decision?
Because on-ice results over one season move a lot with luck, linemates and goaltending, while a contract commits money over several. Three seasons average out some of that variation and show whether a player's results travel across changing circumstances. Weighting recent seasons more heavily is common. The example uses three, and flags the candidate with too few minutes to judge.
What is a relative or off-ice comparison?
A player's team's results while he is on the ice compared with its results while he is off, over the same games. It corrects partly for team quality: a defenseman on a strong club may post good raw figures that his team matches without him. The measure has limits, since it also reflects who replaces him, but it separates players from teams better than raw totals do.
Should a recruitment paper recommend against every candidate if all are flawed?
Only if the case allows passing, and many do. More often the assignment wants the best available option with its weaknesses stated honestly, which is what front offices actually face. The example picks one candidate, limits the term to reduce aging risk and lists the signs that would show the signing going wrong. A no-signing recommendation needs the same rigor.
Where can I find a free MT241 Unit 9 sample paper?
You can read the whole MT241 Unit 9 recruitment recommendation on this page. It compares three free-agent defensemen against their own teams' off-ice figures, weighs age and cost and recommends a four-year deal.
Why does the MT241 Unit 9 sample pass on the player with plus 22?
Because his strong team allowed slightly fewer chances when he sat, so his plus-minus mostly reflects the club around him, and at 31 he is likely to decline during a new contract.