The Problem
The Old Way
SUBJECTIVE COACH SELECTION
RELY ON REPUTATION OR PAST CLUBS
HIGH TURNOVER + INDEMNITY COSTS
NO BENCHMARKING OR CONTEXT
The New Way
QUANTITATIVE, MULTI-FACTOR SCORING
PREDICTIVE FIT + TACTICAL MATCHING
MODELED STABILITY AND RISK SCORING
DYNAMIC CLUSTERING AND COACH PROFILING
Technical Description
Input Collection
Retrieve coach performance history, tactical profile, club fit data, contract info.
Baseline Scoring (CPer0)
Calculate deviation from expected performance:
CPer0 = 1 + (PointsObtained − PointsExpected) / PointsExpected
Adjustment Factors
Adjustment Factors.
Multiply by:
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Cfam (club familiarity bonus)
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Cstab (contractual stability score)
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Csim (tactical similarity to club model)
Final Ranking & Alerts
Rank coaches for hiring or renewal, flag risk-prone profiles.
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Details:
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Coach A (+7): Highest projected impact — strong candidate for hiring or retention.
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Coach E (+5): Also significantly above average — strong upside.
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Coach B/D (+4/+2): Moderate improvement potential — stable and positive.
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Coach C (-1): Negative projected impact — likely not a good fit or underperforming historically.
Conclusion: This visual provides a clear, quantitative summary of how different coaches are expected to influence team performance, helping decision-makers prioritize high-impact hires and avoid risky options.
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CPer Score vs. Expected Points Impact (with Baseline)
This dual-axis chart compares each coach’s CPer score (blue bars) against their projected point impact (green line):
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Coach A leads with a 1.67 CPer and +7 point impact — outstanding choice.
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Coach C delivers solid balance (1.04 CPer, +4 points).
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Coach B is marginal (+2 points, below-average CPer).
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Coach D scores lowest (0.65 CPer, -3 points) — high risk.
Key Insight: CPer reliably predicts which coaches generate above-average returns vs. expected performance — helping clubs make smarter hiring or renewal calls.
"Hiring the right coach is a science — WINNING makes it a decision, not a gamble."
Our model blends tactical data, performance metrics, and financial logic to help clubs make smarter, faster, and more sustainable decisions.
Other Objetives
Define Coach Profiles
Cluster coaches by style, results, and adaptability for better benchmarking.
Descriptive
Comparative
Evaluate Financial & Contractual Impact
Account for rotation risk, average termination costs, and financial exposure.
Strategic
Preventative
Optimize Strategic Decisions
Support board decisions with a single score that blends sporting and financial metrics.
Holistic
Actionable
Forecast Short-Term Impact (10–20 Matches)
Highlight rising coaches with strong recent momentum.
Timely
Opportunity-Driven
Benchmarking & Continuous Improvement
Continuously compare all coaches against evolving ideal profiles.
Objective
Adaptive