What GMs Should Expect From an Analytics Consultant

# What GMs Should Expect From an Analytics Consultant Hockey General Managers live in a world of tight timelines, incomplete information and public scrutiny. When you bring in an analytics consultant, the goal is simple: **better decisions, made with more confidence, in less time.** This article is written from our perspective at The Hockey Brain Consulting after working with sports organizations that range from junior clubs to pro teams. It outlines what you, as a GM or sports director, should expect from an analytics partner—and what to be careful about. --- ## 1. Clear link to your real decisions The first question for any analytics consultant should be: > **“Which concrete decisions will this work help us with?”** Good answers sound like: - Roster construction and contract decisions. - Draft and recruitment prioritization. - Evaluating trade targets or free agents. - Tactical planning for special teams or playoff series. - Player development planning and exit meetings. Vague answers like **“we’ll build a dashboard and see what it tells us”** are a red flag. Your consultant should proactively map their work to the decisions you and your staff actually make during the season. **Expectation**: Within the first 2–4 weeks you should have a short list of 2–3 priority decisions where analytics will be used this season—not just in theory, but on your real calendar. --- ## 2. A structured workflow, not heroic one‑off projects Many clubs have had some experience with analytics that looked like this: - Someone builds a big model or report once. - It looks impressive in a presentation. - Six months later nobody is using it. To avoid that, your consultant should push for a **repeatable workflow**, not just impressive one‑offs. That usually includes: - Regular check‑ins (weekly or biweekly) with a clear agenda. - Standard formats for reports before key milestones (draft, transfer windows, playoffs). - Agreement on who can request analysis, and how priorities are set. - A simple way for coaches and scouts to give feedback on what they actually use. **Expectation**: You know *when* you will see analytics outputs, in which *format*, and how last week’s work connects to this week’s decisions. --- ## 3. Technology that fits your reality Elite‑level analytics does not require NHL‑level infrastructure, but it does require realistic alignment with your club’s reality. Your consultant should ask questions like: - What data do you already collect today? - Which video and scouting tools do you use? - How comfortable are staff with spreadsheets, dashboards, or code‑based tools? - What is your budget and internal IT support level? From there, the tech stack should be chosen to **fit your constraints**, not to showcase the consultant’s favorite tools. Some healthy signs: - Preference for open, standard tools (Python, SQL, standard databases, mainstream BI tools). - Clear plan for how you keep access to code and data if the partnership ever ends. - Documentation that someone else could pick up in the future. **Red flag**: You are asked to lock into a completely proprietary system where you don’t fully control your own data or models. --- ## 4. Outputs that staff can actually use Analytics only creates value if it changes behaviour in the organization. Practical things to look for: - **Simple, repeatable formats**: dashboards, PDFs, one‑page player cards, short memos. - **Role‑specific views**: coaches, scouts and management shouldn’t all see the same thing. - **Language that fits hockey**: no need for complicated math terminology in a pre‑game meeting. - **Clarity about uncertainty**: what the numbers can and cannot tell you. A good consultant will sit down with your staff and ask: - “When in your week do you actually have time to look at this?” - “Which decisions are you making in this meeting?” - “What format would be easiest to use on the bench, in video, or in your scouting meetings?” **Expectation**: People in the room can explain the key metrics back in their own words—and they keep asking for the reports because they find them useful. --- ## 5. Honest discussion of limitations Every model has blind spots. Every dataset has gaps. You should expect your consultant to be explicit about this. Good partners will: - Show where the data is strong and where it is weak (leagues, seasons, specific stats). - Talk about sample size issues and noise. - Explain which outputs are more “directional” and which are robust. - Be willing to say “we don’t know yet” instead of forcing a number on every question. This matters because it builds **trust**. If staff see that the analytics side is honest about uncertainty, they will take the strong signals more seriously. --- ## 6. Integration with your hockey people Analytics works best when there is **respect in both directions**: - Analysts respect the experience and intuition of coaches and scouts. - Hockey staff are open to challenging their own assumptions with data. Consultants should help create this bridge by: - Sitting in on hockey meetings when appropriate, not just sending emails. - Encouraging questions and disagreements instead of defending the model at all costs. - Translating between “data language” and “hockey language”. In practice, that might look like: - Player cards that combine subjective scouting grades with objective metrics. - Reports that highlight “things the numbers like that scouts should re‑watch on video”. - Pre‑meeting notes that prepare coaches for which questions the analysis can answer. **Expectation**: Over time, your staff starts using analytics language naturally—because it has become part of how you talk about the game. --- ## 7. Appropriate seniority and availability Analytics is not just a technical function; it is a strategic one. You should know: - Who is actually doing the work day‑to‑day? - Who makes judgment calls when trade‑offs appear? - How quickly can you reach someone when a decision is time‑sensitive? Sometimes the right setup is: - A senior lead who designs the approach and talks with you as GM. - One or more analysts who do the heavy lifting. But even then, you should have **direct access** to the senior person when needed—especially around deadlines like trade windows or the draft. --- ## 8. Red flags to watch for Based on our experience, GMs should be cautious if they see: - Over‑promising around what models can do (“we will predict every breakout star perfectly”). - Heavy focus on public social‑media‑friendly metrics, light focus on your actual questions. - Lack of transparency about data sources and methods. - No documentation or handover plan. - Resistance to integrating with your existing staff and workflows. If you feel like analytics is happening **to** your organization instead of **with** it, something is off. --- ## 9. How to get the most value as a GM There are a few simple things you can do to make the partnership more effective: - **Be explicit about priorities.** Tell your consultant what is most important this month or quarter. - **Share context.** Explain your internal constraints, politics, and decision processes. - **Give fast feedback.** Say what was useful and what wasn’t after each major deliverable. - **Protect time.** Make sure key staff actually have time to look at and discuss analytics outputs. In return, your consultant should: - Surface insights you would not have found otherwise. - Help you see patterns across seasons, not just in single games. - Make you more confident when you go into high‑stakes meetings (ownership, media, agents). --- ## 10. Summary: What “good” looks like When an analytics consulting relationship works well, you should notice: - Fewer discussions that are purely opinion vs opinion. - More decisions backed by a mix of data, video and live scouting. - Clearer language around roles, playing styles and risk. - A feeling that the club is learning faster from its own decisions. If you are considering working with The Hockey Brain Consulting or another analytics partner, use this article as a checklist. The right relationship will not remove all uncertainty from your job—but it should **give you more clarity, structure and confidence** when you make the big calls. To explore what that could look like for your organization, you can always [book a consultation](/contact) or review [our services](/services) and [workflow](/insights/end-to-end-analytics-workflow).