Clutch Data
@clutchdata_
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🏀 Advanced basketball analytics solutions to improve organizations' decision making and maximize their success in any league 🌍 📊
Joined April 2022
🏀 Introducing Clutch Data Score: A Game-Changing Metric in Basketball Analytics! 🚀📊 After a long period of work, today we are launching the Clutch Data Score (CDS) with some insights for #Euroleague The goal is to have a metric that allows us, as faithfully as possible, to capture the value of a player considering not only offensive aspects but also defensive ones. • How is the Clutch Data Score calculated? The metric is inspired by the work of Shea and Baker and is composed of two parts. On one hand, there is the offensive component: Efficient Offensive Production (EOP), which takes into account the player's point generation (through points and assists) and also the efficiency in achieving them. On the other hand, the defensive component: Defensive Points Saved (DPS), which analyzes the user's impact on the opponent's eFG%, TOV%, and ORB% by comparing this performance when on the court and off. A brief outline of how the metric is composed is as follows: • Top Clutch Data Score performers in Euroleague If we take the 2023-24 Euroleague season, Jan Vesely records a CDS per game of 23.5 (15.8 from Offense and 7.7 from Defense). He is followed by Mike James with 22.9 and Keenan Evans with 20.4. • Top Improvers in Clutch Data Score We also analyze the improvement of the CDS of all players from last season to this one. In this aspect, we find Mike James with an improvement of 10.9, followed by Johannes Thiemann of Alba Berlin with 10.2, and Jan Vesely with 9.9. • Improvement compared to PIR From our point of view, this metric is much more comprehensive than PIR since by considering the player's defensive impact more accurately, as well as offensive efficiency, it reaches a more accurate value. PIR, while easy to interpret and calculate, has some weaknesses: - Subjectivity: The weight assigned to each component in the formula may be subjective and might not capture certain intangibles that contribute to a player's impact. - Equal Weighting: PIR treats all positive and negative actions equally, which may not accurately reflect the actual importance of each contribution. - Doesn't Capture Team Dynamics: It focuses on individual performance and may not fully consider how a player's actions contribute to team dynamics. When we analyze CDS vs PIR, we see that the latter overestimates players with high DPS and, at the same time, underestimates those with high Offensive Efficiency. Keep in touch with us as we'll be updating this metric for other leagues and also analyzing the top performers for each month. 📈🔍 Stay tuned for more insights and exciting developments!
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@JogaSportivo @EuroLeague @GIGANTESbasket @TheUpset_media @TheHateful8_gr @ZakkasGeorge @augis04 @mstef80 @chrisalucard @stavrakas13 @eurohoopsGR This shows the difference between NRtg Home and Guest. Partizan have more or less the same NRtg no matters the condition, which in the end is something very positive for the team. Take a look here:
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@Kaspar_Hauser87 @EuroLeague @GIGANTESbasket @TheUpset_media @TheHateful8_gr @ZakkasGeorge @augis04 @mstef80 @chrisalucard @stavrakas13 @eurohoopsGR That's a very valid point!
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@Petar93551212 @EuroLeague @GIGANTESbasket @TheUpset_media @TheHateful8_gr @ZakkasGeorge @augis04 @mstef80 @chrisalucard @stavrakas13 @eurohoopsGR For SoS we use the winning percentage of the remaining opponents, considering home/away conditions. Also we consider the winning percentage of the opponents' opponents and a time decay adjustment (putting more weight in the last games compared to the first ones)
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@pao_pantou 💪🚀
🍀 IS OAKA THE HOTTEST ARENA IN EUROPE? The numbers tell an incredible story – Panathinaikos transforms at OAKA with a league-leading +24.1 net rating differential compared to away games. The detailed breakdown is striking: 🏠 Home: +18.1 net rating (130.7 ORtg, 112.6 DRtg) ✈️ Away: -6.0 net rating (110.3 ORtg, 116.3 DRtg) 📈 Differential: +24.1 net rating swing This massive home advantage towers over other strong home courts: 🇩🇪 Bayern: +19.3 🇪🇸 Baskonia: +17.5 🇬🇷 Olympiacos: +17.1 On the flip end, only two teams perform worse at home: 🇷🇸 Partizan: -0.7 🇫🇷 Paris: -1.5 #EuroLeague #EveryGameMatters
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@videxjr @EuroLeague @GIGANTESbasket @TheUpset_media @Sh_Cl_Pod @chrisalucard @euroleague_time @EuroLeagueFr @EurohoopsES @mstef80 @augis04 You’re right it’s incorrect in the post 🤦🏼♂️
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@Ioakeim_Thanop @EuroLeague @GIGANTESbasket @TheUpset_media @Sh_Cl_Pod @chrisalucard @euroleague_time @EuroLeagueFr @EurohoopsES @mstef80 @augis04 From our friend @Figurei8ht
Only 8 rounds to go and the battle for the playoffs in @EuroLeague is heating up🔥 Below are the projected wins by position: 🟢 Top 4: 21 Wins (seeded - direct to PO) 🟠 Top 6: 20 Wins (unseeded - direct to PO) 🟤 Top 10: 18 Wins (play-in) The projected difference from 7th to 10th position is only 1 win.. Prediction model by @g_giase with 10k sims on a weighted probability of: ✅ Elo rankings (past 2 seasons) ✅ Net Advanced Rating (Offensive - Defensive) of this season, split by home/away games. #EveryGameMatters #EuroLeague #Simulation
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📊 During these two long weeks until #EuroLeague returns, let's analyze the Strength of Schedule for the final sprint (last 8 rounds)! Toughest remaining paths: 1⃣ Zalgiris (61.6% SoS) 2⃣ Monaco (57.7%) 3⃣ Bayern (55.9%) Most favorable schedules: 1⃣ Efes (38.2%) 2⃣ Olympiacos (40.7%) 3⃣Partizan (47.7%) 📍 Numbers account for both opponents' strength AND home/away dynamics Interesting: League leader Olympiacos has 2nd-easiest schedule in their title push! 👀
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RT @Sergio_Vegas: 📹🏀| ¡NUEVO VÍDEO! ¡ANÁLISIS! El mejor Juancho de siempre con @clutchdata_: 🚀 ¡Pieza clave en el Panathinaikos! 💣 ¿En qu…
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@MakisPilouris @EuroLeague @GIGANTESbasket @TheUpset_media @Sh_Cl_Pod @chrisalucard @augis04 @euroleague_time @EurohoopsES @mstef80 Thanks a lot mate!
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@jordito46843815 @FCBbasket @SalvatoRRR_OMG @palauresist @JijantesFC @OutBasket @EuroLeague @EurohoopsES @GIGANTESbasket @TheUpset_media Si, quedó mal el chart y el texto - acá está el correcto:
Jan Vessely is the second-best in CDS per game, not per 30 minutes played. Thanks @OlympiacosBC_FR for noticing we uploaded the incorrect chart.
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